id	sid	tid	token	lemma	pos
ajst-31230	1	1	academic	academic	ADJ
ajst-31230	1	2	journal	journal	NOUN
ajst-31230	1	3	of	of	ADP
ajst-31230	1	4	science	science	NOUN
ajst-31230	1	5	and	and	CCONJ
ajst-31230	1	6	technology	technology	NOUN
ajst-31230	1	7	issn	issn	NOUN
ajst-31230	1	8	:	:	PUNCT
ajst-31230	1	9	2771	2771	NUM
ajst-31230	1	10	-	-	SYM
ajst-31230	1	11	3032	3032	NUM
ajst-31230	1	12	|	|	NOUN
ajst-31230	1	13	vol	vol	NOUN
ajst-31230	1	14	.	.	PROPN
ajst-31230	1	15	15	15	NUM
ajst-31230	1	16	,	,	PUNCT
ajst-31230	1	17	no	no	INTJ
ajst-31230	1	18	.	.	NOUN
ajst-31230	1	19	3	3	NUM
ajst-31230	1	20	,	,	PUNCT
ajst-31230	1	21	2025	2025	NUM
ajst-31230	1	22	124	124	NUM
ajst-31230	1	23	a	a	DET
ajst-31230	1	24	lightweight	lightweight	ADJ
ajst-31230	1	25	method	method	NOUN
ajst-31230	1	26	integrating	integrate	VERB
ajst-31230	1	27	dynamic	dynamic	ADJ
ajst-31230	1	28	frequency‐	frequency‐	PROPN
ajst-31230	1	29	aware	aware	ADJ
ajst-31230	1	30	convolution	convolution	NOUN
ajst-31230	1	31	and	and	CCONJ
ajst-31230	1	32	softpool	softpool	VERB
ajst-31230	1	33	for	for	ADP
ajst-31230	1	34	abnormal	abnormal	ADJ
ajst-31230	1	35	sound	sound	NOUN
ajst-31230	1	36	detection	detection	NOUN
ajst-31230	1	37	in	in	ADP
ajst-31230	1	38	wind	wind	NOUN
ajst-31230	1	39	turbines	turbine	NOUN
ajst-31230	1	40	qingzheng	qingzheng	PROPN
ajst-31230	1	41	li	li	PROPN
ajst-31230	1	42	school	school	PROPN
ajst-31230	1	43	of	of	ADP
ajst-31230	1	44	information	information	NOUN
ajst-31230	1	45	and	and	CCONJ
ajst-31230	1	46	control	control	PROPN
ajst-31230	1	47	engineering	engineering	PROPN
ajst-31230	1	48	,	,	PUNCT
ajst-31230	1	49	jilin	jilin	PROPN
ajst-31230	1	50	chemical	chemical	PROPN
ajst-31230	1	51	university	university	PROPN
ajst-31230	1	52	,	,	PUNCT
ajst-31230	1	53	jilin	jilin	PROPN
ajst-31230	1	54	,	,	PUNCT
ajst-31230	1	55	china	china	PROPN
ajst-31230	1	56	abstract	abstract	NOUN
ajst-31230	1	57	:	:	PUNCT
ajst-31230	1	58	aiming	aim	VERB
ajst-31230	1	59	at	at	ADP
ajst-31230	1	60	the	the	DET
ajst-31230	1	61	problems	problem	NOUN
ajst-31230	1	62	of	of	ADP
ajst-31230	1	63	insufficient	insufficient	ADJ
ajst-31230	1	64	feature	feature	NOUN
ajst-31230	1	65	expression	expression	NOUN
ajst-31230	1	66	capability	capability	NOUN
ajst-31230	1	67	and	and	CCONJ
ajst-31230	1	68	high	high	ADJ
ajst-31230	1	69	model	model	NOUN
ajst-31230	1	70	computation	computation	NOUN
ajst-31230	1	71	complexity	complexity	NOUN
ajst-31230	1	72	in	in	ADP
ajst-31230	1	73	traditional	traditional	ADJ
ajst-31230	1	74	wind	wind	NOUN
ajst-31230	1	75	turbine	turbine	NOUN
ajst-31230	1	76	group	group	NOUN
ajst-31230	1	77	abnormal	abnormal	ADJ
ajst-31230	1	78	sound	sound	NOUN
ajst-31230	1	79	detection	detection	NOUN
ajst-31230	1	80	methods	method	NOUN
ajst-31230	1	81	,	,	PUNCT
ajst-31230	1	82	this	this	DET
ajst-31230	1	83	paper	paper	NOUN
ajst-31230	1	84	proposes	propose	VERB
ajst-31230	1	85	a	a	DET
ajst-31230	1	86	lightweight	lightweight	ADJ
ajst-31230	1	87	detection	detection	NOUN
ajst-31230	1	88	method	method	NOUN
ajst-31230	1	89	based	base	VERB
ajst-31230	1	90	on	on	ADP
ajst-31230	1	91	improved	improved	ADJ
ajst-31230	1	92	mobilenetv3	mobilenetv3	PROPN
ajst-31230	1	93	network	network	NOUN
ajst-31230	1	94	.	.	PUNCT
ajst-31230	2	1	first	first	ADV
ajst-31230	2	2	,	,	PUNCT
ajst-31230	2	3	the	the	DET
ajst-31230	2	4	sincnet	sincnet	NOUN
ajst-31230	2	5	bandpass	bandpass	NOUN
ajst-31230	2	6	filter	filter	NOUN
ajst-31230	2	7	and	and	CCONJ
ajst-31230	2	8	mel	mel	PROPN
ajst-31230	2	9	spectrum	spectrum	PROPN
ajst-31230	2	10	are	be	AUX
ajst-31230	2	11	integrated	integrate	VERB
ajst-31230	2	12	to	to	PART
ajst-31230	2	13	construct	construct	VERB
ajst-31230	2	14	multidimensional	multidimensional	ADJ
ajst-31230	2	15	acoustic	acoustic	ADJ
ajst-31230	2	16	features	feature	NOUN
ajst-31230	2	17	,	,	PUNCT
ajst-31230	2	18	taking	take	VERB
ajst-31230	2	19	into	into	ADP
ajst-31230	2	20	account	account	NOUN
ajst-31230	2	21	the	the	DET
ajst-31230	2	22	original	original	ADJ
ajst-31230	2	23	signal	signal	NOUN
ajst-31230	2	24	time	time	NOUN
ajst-31230	2	25	-	-	PUNCT
ajst-31230	2	26	domain	domain	NOUN
ajst-31230	2	27	features	feature	NOUN
ajst-31230	2	28	and	and	CCONJ
ajst-31230	2	29	frequency	frequency	NOUN
ajst-31230	2	30	-	-	PUNCT
ajst-31230	2	31	domain	domain	NOUN
ajst-31230	2	32	features	feature	NOUN
ajst-31230	2	33	.	.	PUNCT
ajst-31230	3	1	second	second	ADJ
ajst-31230	3	2	,	,	PUNCT
ajst-31230	3	3	a	a	DET
ajst-31230	3	4	dynamic	dynamic	ADJ
ajst-31230	3	5	frequency	frequency	NOUN
ajst-31230	3	6	-	-	PUNCT
ajst-31230	3	7	aware	aware	ADJ
ajst-31230	3	8	convolution	convolution	NOUN
ajst-31230	3	9	(	(	PUNCT
ajst-31230	3	10	dfc	dfc	NOUN
ajst-31230	3	11	)	)	PUNCT
ajst-31230	3	12	module	module	NOUN
ajst-31230	3	13	is	be	AUX
ajst-31230	3	14	introduced	introduce	VERB
ajst-31230	3	15	into	into	ADP
ajst-31230	3	16	the	the	DET
ajst-31230	3	17	mobilenetv3	mobilenetv3	NOUN
ajst-31230	3	18	network	network	NOUN
ajst-31230	3	19	architecture	architecture	NOUN
ajst-31230	3	20	to	to	PART
ajst-31230	3	21	adaptively	adaptively	ADV
ajst-31230	3	22	adjust	adjust	VERB
ajst-31230	3	23	the	the	DET
ajst-31230	3	24	parameters	parameter	NOUN
ajst-31230	3	25	of	of	ADP
ajst-31230	3	26	the	the	DET
ajst-31230	3	27	convolution	convolution	NOUN
ajst-31230	3	28	kernel	kernel	NOUN
ajst-31230	3	29	through	through	ADP
ajst-31230	3	30	the	the	DET
ajst-31230	3	31	frequency	frequency	NOUN
ajst-31230	3	32	-	-	PUNCT
ajst-31230	3	33	domain	domain	NOUN
ajst-31230	3	34	attention	attention	NOUN
ajst-31230	3	35	mechanism	mechanism	NOUN
ajst-31230	3	36	to	to	PART
ajst-31230	3	37	strengthen	strengthen	VERB
ajst-31230	3	38	the	the	DET
ajst-31230	3	39	frequency	frequency	NOUN
ajst-31230	3	40	feature	feature	NOUN
ajst-31230	3	41	capture	capture	NOUN
ajst-31230	3	42	of	of	ADP
ajst-31230	3	43	abnormal	abnormal	ADJ
ajst-31230	3	44	sounds	sound	NOUN
ajst-31230	3	45	;	;	PUNCT
ajst-31230	3	46	the	the	DET
ajst-31230	3	47	feature	feature	NOUN
ajst-31230	3	48	downsampling	downsample	VERB
ajst-31230	3	49	process	process	NOUN
ajst-31230	3	50	is	be	AUX
ajst-31230	3	51	optimized	optimize	VERB
ajst-31230	3	52	by	by	ADP
ajst-31230	3	53	combining	combine	VERB
ajst-31230	3	54	with	with	ADP
ajst-31230	3	55	softpool	softpool	NOUN
ajst-31230	3	56	to	to	PART
ajst-31230	3	57	reduce	reduce	VERB
ajst-31230	3	58	the	the	DET
ajst-31230	3	59	loss	loss	NOUN
ajst-31230	3	60	of	of	ADP
ajst-31230	3	61	high	high	ADJ
ajst-31230	3	62	-	-	PUNCT
ajst-31230	3	63	frequency	frequency	NOUN
ajst-31230	3	64	information	information	NOUN
ajst-31230	3	65	.	.	PUNCT
ajst-31230	4	1	on	on	ADP
ajst-31230	4	2	the	the	DET
ajst-31230	4	3	dataset	dataset	NOUN
ajst-31230	4	4	of	of	ADP
ajst-31230	4	5	danish	danish	PROPN
ajst-31230	4	6	university	university	PROPN
ajst-31230	4	7	of	of	ADP
ajst-31230	4	8	science	science	NOUN
ajst-31230	4	9	and	and	CCONJ
ajst-31230	4	10	technology	technology	NOUN
ajst-31230	4	11	,	,	PUNCT
ajst-31230	4	12	the	the	DET
ajst-31230	4	13	auc	auc	NOUN
ajst-31230	4	14	reaches	reach	VERB
ajst-31230	4	15	94.71	94.71	NUM
ajst-31230	4	16	%	%	NOUN
ajst-31230	4	17	,	,	PUNCT
ajst-31230	4	18	and	and	CCONJ
ajst-31230	4	19	the	the	DET
ajst-31230	4	20	number	number	NOUN
ajst-31230	4	21	of	of	ADP
ajst-31230	4	22	parameters	parameter	NOUN
ajst-31230	4	23	is	be	AUX
ajst-31230	4	24	only	only	ADV
ajst-31230	4	25	2.38	2.38	NUM
ajst-31230	4	26	m	m	NOUN
ajst-31230	4	27	,	,	PUNCT
ajst-31230	4	28	which	which	PRON
ajst-31230	4	29	is	be	AUX
ajst-31230	4	30	62.3	62.3	NUM
ajst-31230	4	31	%	%	NOUN
ajst-31230	4	32	lower	low	ADJ
ajst-31230	4	33	than	than	ADP
ajst-31230	4	34	the	the	DET
ajst-31230	4	35	mainstream	mainstream	NOUN
ajst-31230	4	36	model	model	NOUN
ajst-31230	4	37	resnet-18	resnet-18	PROPN
ajst-31230	4	38	,	,	PUNCT
ajst-31230	4	39	providing	provide	VERB
ajst-31230	4	40	a	a	DET
ajst-31230	4	41	high	high	ADJ
ajst-31230	4	42	-	-	PUNCT
ajst-31230	4	43	precision	precision	NOUN
ajst-31230	4	44	edge	edge	NOUN
ajst-31230	4	45	-	-	PUNCT
ajst-31230	4	46	end	end	NOUN
ajst-31230	4	47	solution	solution	NOUN
ajst-31230	4	48	for	for	ADP
ajst-31230	4	49	wind	wind	NOUN
ajst-31230	4	50	turbine	turbine	NOUN
ajst-31230	4	51	status	status	NOUN
ajst-31230	4	52	monitoring	monitoring	NOUN
ajst-31230	4	53	.	.	PUNCT
ajst-31230	5	1	keywords	keyword	NOUN
ajst-31230	5	2	:	:	PUNCT
ajst-31230	5	3	wind	wind	NOUN
ajst-31230	5	4	turbines	turbine	NOUN
ajst-31230	5	5	,	,	PUNCT
ajst-31230	5	6	abnormal	abnormal	ADJ
ajst-31230	5	7	sound	sound	NOUN
ajst-31230	5	8	detection	detection	NOUN
ajst-31230	5	9	,	,	PUNCT
ajst-31230	5	10	mobilenetv3	mobilenetv3	PROPN
ajst-31230	5	11	.	.	PUNCT
ajst-31230	6	1	1	1	X
ajst-31230	6	2	.	.	X
ajst-31230	6	3	introduction	introduction	NOUN
ajst-31230	6	4	wind	wind	NOUN
ajst-31230	6	5	turbines	turbine	NOUN
ajst-31230	6	6	,	,	PUNCT
ajst-31230	6	7	as	as	ADP
ajst-31230	6	8	core	core	NOUN
ajst-31230	6	9	equipment	equipment	NOUN
ajst-31230	6	10	in	in	ADP
ajst-31230	6	11	clean	clean	ADJ
ajst-31230	6	12	energy	energy	NOUN
ajst-31230	6	13	generation	generation	NOUN
ajst-31230	6	14	,	,	PUNCT
ajst-31230	6	15	have	have	VERB
ajst-31230	6	16	operational	operational	ADJ
ajst-31230	6	17	stability	stability	NOUN
ajst-31230	6	18	that	that	PRON
ajst-31230	6	19	directly	directly	ADV
ajst-31230	6	20	impacts	impact	VERB
ajst-31230	6	21	power	power	NOUN
ajst-31230	6	22	generation	generation	NOUN
ajst-31230	6	23	efficiency	efficiency	NOUN
ajst-31230	6	24	and	and	CCONJ
ajst-31230	6	25	maintenance	maintenance	NOUN
ajst-31230	6	26	costs	cost	NOUN
ajst-31230	6	27	.	.	PUNCT
ajst-31230	7	1	traditional	traditional	ADJ
ajst-31230	7	2	vibration	vibration	NOUN
ajst-31230	7	3	monitoring	monitoring	NOUN
ajst-31230	7	4	methods	method	NOUN
ajst-31230	7	5	are	be	AUX
ajst-31230	7	6	susceptible	susceptible	ADJ
ajst-31230	7	7	to	to	ADP
ajst-31230	7	8	environmental	environmental	ADJ
ajst-31230	7	9	interference	interference	NOUN
ajst-31230	7	10	and	and	CCONJ
ajst-31230	7	11	incur	incur	VERB
ajst-31230	7	12	high	high	ADJ
ajst-31230	7	13	installation	installation	NOUN
ajst-31230	7	14	and	and	CCONJ
ajst-31230	7	15	maintenance	maintenance	NOUN
ajst-31230	7	16	expenses	expense	NOUN
ajst-31230	7	17	.	.	PUNCT
ajst-31230	8	1	industrial	industrial	ADJ
ajst-31230	8	2	noise	noise	NOUN
ajst-31230	8	3	exhibits	exhibit	VERB
ajst-31230	8	4	complex	complex	ADJ
ajst-31230	8	5	characteristics	characteristic	NOUN
ajst-31230	8	6	such	such	ADJ
ajst-31230	8	7	as	as	ADP
ajst-31230	8	8	wind	wind	NOUN
ajst-31230	8	9	noise	noise	NOUN
ajst-31230	8	10	and	and	CCONJ
ajst-31230	8	11	electromagnetic	electromagnetic	ADJ
ajst-31230	8	12	interference	interference	NOUN
ajst-31230	8	13	,	,	PUNCT
ajst-31230	8	14	rendering	render	VERB
ajst-31230	8	15	conventional	conventional	ADJ
ajst-31230	8	16	detection	detection	NOUN
ajst-31230	8	17	methods	method	NOUN
ajst-31230	8	18	insufficiently	insufficiently	ADV
ajst-31230	8	19	sensitive	sensitive	ADJ
ajst-31230	8	20	to	to	ADP
ajst-31230	8	21	high	high	ADJ
ajst-31230	8	22	-	-	PUNCT
ajst-31230	8	23	frequency	frequency	NOUN
ajst-31230	8	24	anomalies	anomaly	NOUN
ajst-31230	8	25	and	and	CCONJ
ajst-31230	8	26	unknown	unknown	ADJ
ajst-31230	8	27	fault	fault	NOUN
ajst-31230	8	28	types	type	NOUN
ajst-31230	8	29	.	.	PUNCT
ajst-31230	9	1	in	in	ADP
ajst-31230	9	2	contrast	contrast	NOUN
ajst-31230	9	3	,	,	PUNCT
ajst-31230	9	4	acoustic	acoustic	ADJ
ajst-31230	9	5	analysis	analysis	NOUN
ajst-31230	9	6	technology	technology	NOUN
ajst-31230	9	7	enables	enable	VERB
ajst-31230	9	8	non	non	ADJ
ajst-31230	9	9	-	-	ADJ
ajst-31230	9	10	contact	contact	ADJ
ajst-31230	9	11	detection	detection	NOUN
ajst-31230	9	12	by	by	ADP
ajst-31230	9	13	capturing	capture	VERB
ajst-31230	9	14	operational	operational	ADJ
ajst-31230	9	15	sounds	sound	NOUN
ajst-31230	9	16	,	,	PUNCT
ajst-31230	9	17	effectively	effectively	ADV
ajst-31230	9	18	identifying	identify	VERB
ajst-31230	9	19	mechanical	mechanical	ADJ
ajst-31230	9	20	damage	damage	NOUN
ajst-31230	9	21	.	.	PUNCT
ajst-31230	10	1	abnormal	abnormal	ADJ
ajst-31230	10	2	sound	sound	NOUN
ajst-31230	10	3	detection	detection	NOUN
ajst-31230	10	4	(	(	PUNCT
ajst-31230	10	5	asd)systems	asd)systems	PROPN
ajst-31230	10	6	,	,	PUNCT
ajst-31230	10	7	based	base	VERB
ajst-31230	10	8	on	on	ADP
ajst-31230	10	9	acoustic	acoustic	ADJ
ajst-31230	10	10	signal	signal	NOUN
ajst-31230	10	11	analysis	analysis	NOUN
ajst-31230	10	12	and	and	CCONJ
ajst-31230	10	13	pattern	pattern	NOUN
ajst-31230	10	14	recognition	recognition	NOUN
ajst-31230	10	15	technologies	technology	NOUN
ajst-31230	10	16	,	,	PUNCT
ajst-31230	10	17	have	have	AUX
ajst-31230	10	18	gained	gain	VERB
ajst-31230	10	19	widespread	widespread	ADJ
ajst-31230	10	20	attention	attention	NOUN
ajst-31230	10	21	in	in	ADP
ajst-31230	10	22	the	the	DET
ajst-31230	10	23	field	field	NOUN
ajst-31230	10	24	of	of	ADP
ajst-31230	10	25	industrial	industrial	ADJ
ajst-31230	10	26	intelligent	intelligent	ADJ
ajst-31230	10	27	monitoring	monitoring	NOUN
ajst-31230	10	28	.	.	PUNCT
ajst-31230	11	1	this	this	DET
ajst-31230	11	2	recognition	recognition	NOUN
ajst-31230	11	3	stems	stem	VERB
ajst-31230	11	4	from	from	ADP
ajst-31230	11	5	their	their	PRON
ajst-31230	11	6	nonintrusive	nonintrusive	ADJ
ajst-31230	11	7	monitoring	monitoring	NOUN
ajst-31230	11	8	nature	nature	NOUN
ajst-31230	11	9	,	,	PUNCT
ajst-31230	11	10	real	real	ADJ
ajst-31230	11	11	-	-	PUNCT
ajst-31230	11	12	time	time	NOUN
ajst-31230	11	13	responsiveness	responsiveness	NOUN
ajst-31230	11	14	,	,	PUNCT
ajst-31230	11	15	and	and	CCONJ
ajst-31230	11	16	adaptability	adaptability	NOUN
ajst-31230	11	17	to	to	ADP
ajst-31230	11	18	complex	complex	ADJ
ajst-31230	11	19	acoustic	acoustic	ADJ
ajst-31230	11	20	environments	environment	NOUN
ajst-31230	11	21	.	.	PUNCT
ajst-31230	12	1	currently	currently	ADV
ajst-31230	12	2	,	,	PUNCT
ajst-31230	12	3	asd	asd	PROPN
ajst-31230	12	4	has	have	AUX
ajst-31230	12	5	been	be	AUX
ajst-31230	12	6	successfully	successfully	ADV
ajst-31230	12	7	applied	apply	VERB
ajst-31230	12	8	in	in	ADP
ajst-31230	12	9	diverse	diverse	ADJ
ajst-31230	12	10	scenarios	scenario	NOUN
ajst-31230	12	11	including	include	VERB
ajst-31230	12	12	livestock	livestock	NOUN
ajst-31230	12	13	health	health	NOUN
ajst-31230	12	14	monitoring	monitoring	NOUN
ajst-31230	12	15	,	,	PUNCT
ajst-31230	12	16	industrial	industrial	ADJ
ajst-31230	12	17	equipment	equipment	NOUN
ajst-31230	12	18	condition	condition	NOUN
ajst-31230	12	19	assessment	assessment	NOUN
ajst-31230	12	20	,	,	PUNCT
ajst-31230	12	21	and	and	CCONJ
ajst-31230	12	22	medical	medical	ADJ
ajst-31230	12	23	diagnostic	diagnostic	ADJ
ajst-31230	12	24	assistance	assistance	NOUN
ajst-31230	12	25	.	.	PUNCT
ajst-31230	13	1	in	in	ADP
ajst-31230	13	2	wind	wind	NOUN
ajst-31230	13	3	turbine	turbine	NOUN
ajst-31230	13	4	abnormal	abnormal	ADJ
ajst-31230	13	5	sound	sound	NOUN
ajst-31230	13	6	detection	detection	NOUN
ajst-31230	13	7	,	,	PUNCT
ajst-31230	13	8	supervised	supervised	ADJ
ajst-31230	13	9	methods	method	NOUN
ajst-31230	13	10	rely	rely	VERB
ajst-31230	13	11	on	on	ADP
ajst-31230	13	12	labeled	label	VERB
ajst-31230	13	13	fault	fault	NOUN
ajst-31230	13	14	samples	sample	NOUN
ajst-31230	13	15	and	and	CCONJ
ajst-31230	13	16	achieve	achieve	VERB
ajst-31230	13	17	high	high	ADJ
ajst-31230	13	18	accuracy	accuracy	NOUN
ajst-31230	13	19	for	for	ADP
ajst-31230	13	20	known	known	ADJ
ajst-31230	13	21	anomalies	anomaly	NOUN
ajst-31230	13	22	,	,	PUNCT
ajst-31230	13	23	but	but	CCONJ
ajst-31230	13	24	they	they	PRON
ajst-31230	13	25	face	face	VERB
ajst-31230	13	26	two	two	NUM
ajst-31230	13	27	major	major	ADJ
ajst-31230	13	28	limitations	limitation	NOUN
ajst-31230	13	29	,	,	PUNCT
ajst-31230	13	30	the	the	DET
ajst-31230	13	31	acquisition	acquisition	NOUN
ajst-31230	13	32	of	of	ADP
ajst-31230	13	33	abnormal	abnormal	ADJ
ajst-31230	13	34	samples	sample	NOUN
ajst-31230	13	35	through	through	ADP
ajst-31230	13	36	destructive	destructive	ADJ
ajst-31230	13	37	experiments	experiment	NOUN
ajst-31230	13	38	is	be	AUX
ajst-31230	13	39	costly	costly	ADJ
ajst-31230	13	40	and	and	CCONJ
ajst-31230	13	41	impractical	impractical	ADJ
ajst-31230	13	42	for	for	ADP
ajst-31230	13	43	industrial	industrial	ADJ
ajst-31230	13	44	applications	application	NOUN
ajst-31230	13	45	,	,	PUNCT
ajst-31230	13	46	model	model	NOUN
ajst-31230	13	47	performance	performance	NOUN
ajst-31230	13	48	significantly	significantly	ADV
ajst-31230	13	49	degrades	degrade	VERB
ajst-31230	13	50	after	after	ADP
ajst-31230	13	51	cross	cross	ADJ
ajst-31230	13	52	-	-	ADJ
ajst-31230	13	53	condition	condition	ADJ
ajst-31230	13	54	transfer	transfer	NOUN
ajst-31230	13	55	due	due	ADP
ajst-31230	13	56	to	to	ADP
ajst-31230	13	57	domain	domain	NOUN
ajst-31230	13	58	shifts	shift	NOUN
ajst-31230	13	59	in	in	ADP
ajst-31230	13	60	operational	operational	ADJ
ajst-31230	13	61	environments	environment	NOUN
ajst-31230	13	62	.	.	PUNCT
ajst-31230	14	1	in	in	ADP
ajst-31230	14	2	contrast	contrast	NOUN
ajst-31230	14	3	,	,	PUNCT
ajst-31230	14	4	unsupervised	unsupervised	ADJ
ajst-31230	14	5	methods	method	NOUN
ajst-31230	14	6	only	only	ADV
ajst-31230	14	7	require	require	VERB
ajst-31230	14	8	normal	normal	ADJ
ajst-31230	14	9	sound	sound	NOUN
ajst-31230	14	10	data	datum	NOUN
ajst-31230	14	11	for	for	ADP
ajst-31230	14	12	modeling	modeling	NOUN
ajst-31230	14	13	,	,	PUNCT
ajst-31230	14	14	effectively	effectively	ADV
ajst-31230	14	15	overcoming	overcome	VERB
ajst-31230	14	16	data	datum	NOUN
ajst-31230	14	17	scarcity	scarcity	NOUN
ajst-31230	14	18	constraints	constraint	NOUN
ajst-31230	14	19	.	.	PUNCT
ajst-31230	15	1	for	for	ADP
ajst-31230	15	2	instance	instance	NOUN
ajst-31230	15	3	,	,	PUNCT
ajst-31230	15	4	autoencoders	autoencoder	NOUN
ajst-31230	15	5	can	can	AUX
ajst-31230	15	6	detect	detect	VERB
ajst-31230	15	7	blade	blade	NOUN
ajst-31230	15	8	cracks	crack	NOUN
ajst-31230	15	9	through	through	ADP
ajst-31230	15	10	reconstruction	reconstruction	NOUN
ajst-31230	15	11	error	error	NOUN
ajst-31230	15	12	analysis	analysis	NOUN
ajst-31230	15	13	while	while	SCONJ
ajst-31230	15	14	integrating	integrate	VERB
ajst-31230	15	15	noise	noise	NOUN
ajst-31230	15	16	suppression	suppression	NOUN
ajst-31230	15	17	techniques	technique	NOUN
ajst-31230	15	18	to	to	PART
ajst-31230	15	19	mitigate	mitigate	VERB
ajst-31230	15	20	wind	wind	NOUN
ajst-31230	15	21	noise	noise	NOUN
ajst-31230	15	22	-	-	PUNCT
ajst-31230	15	23	induced	induce	VERB
ajst-31230	15	24	misclassification	misclassification	NOUN
ajst-31230	15	25	.	.	PUNCT
ajst-31230	16	1	this	this	DET
ajst-31230	16	2	study	study	NOUN
ajst-31230	16	3	adopts	adopt	VERB
ajst-31230	16	4	an	an	DET
ajst-31230	16	5	unsupervised	unsupervised	ADJ
ajst-31230	16	6	approach	approach	NOUN
ajst-31230	16	7	because	because	SCONJ
ajst-31230	16	8	industrial	industrial	ADJ
ajst-31230	16	9	scenarios	scenario	NOUN
ajst-31230	16	10	inherently	inherently	ADV
ajst-31230	16	11	provide	provide	VERB
ajst-31230	16	12	abundant	abundant	ADJ
ajst-31230	16	13	normal	normal	ADJ
ajst-31230	16	14	operation	operation	NOUN
ajst-31230	16	15	data	datum	NOUN
ajst-31230	16	16	,	,	PUNCT
ajst-31230	16	17	and	and	CCONJ
ajst-31230	16	18	such	such	ADJ
ajst-31230	16	19	methods	method	NOUN
ajst-31230	16	20	enable	enable	VERB
ajst-31230	16	21	identification	identification	NOUN
ajst-31230	16	22	of	of	ADP
ajst-31230	16	23	unknown	unknown	ADJ
ajst-31230	16	24	anomalies	anomaly	NOUN
ajst-31230	16	25	without	without	ADP
ajst-31230	16	26	dependency	dependency	NOUN
ajst-31230	16	27	on	on	ADP
ajst-31230	16	28	predefined	predefine	VERB
ajst-31230	16	29	fault	fault	NOUN
ajst-31230	16	30	categories	category	NOUN
ajst-31230	16	31	,	,	PUNCT
ajst-31230	16	32	addressing	address	VERB
ajst-31230	16	33	the	the	DET
ajst-31230	16	34	critical	critical	ADJ
ajst-31230	16	35	challenges	challenge	NOUN
ajst-31230	16	36	of	of	ADP
ajst-31230	16	37	supervised	supervise	VERB
ajst-31230	16	38	models.the	models.the	DET
ajst-31230	16	39	unsupervised	unsupervised	ADJ
ajst-31230	16	40	anomaly	anomaly	NOUN
ajst-31230	16	41	sound	sound	NOUN
ajst-31230	16	42	system	system	NOUN
ajst-31230	16	43	monitoring	monitor	VERB
ajst-31230	16	44	framework	framework	NOUN
ajst-31230	16	45	is	be	AUX
ajst-31230	16	46	illustrated	illustrate	VERB
ajst-31230	16	47	in	in	ADP
ajst-31230	16	48	figure	figure	NOUN
ajst-31230	16	49	1	1	NUM
ajst-31230	16	50	.	.	PUNCT
ajst-31230	16	51	figure	figure	NOUN
ajst-31230	16	52	1	1	NUM
ajst-31230	16	53	.	.	PUNCT
ajst-31230	16	54	unsupervised	unsupervised	ADJ
ajst-31230	16	55	anomalous	anomalous	ADJ
ajst-31230	16	56	sound	sound	NOUN
ajst-31230	16	57	system	system	NOUN
ajst-31230	16	58	monitoring	monitor	VERB
ajst-31230	16	59	framework	framework	NOUN
ajst-31230	16	60	acoustic	acoustic	ADJ
ajst-31230	16	61	feature	feature	NOUN
ajst-31230	16	62	extraction	extraction	NOUN
ajst-31230	16	63	techniques	technique	NOUN
ajst-31230	16	64	have	have	AUX
ajst-31230	16	65	undergone	undergo	VERB
ajst-31230	16	66	continuous	continuous	ADJ
ajst-31230	16	67	evolution	evolution	NOUN
ajst-31230	16	68	from	from	ADP
ajst-31230	16	69	traditional	traditional	ADJ
ajst-31230	16	70	methods	method	NOUN
ajst-31230	16	71	to	to	ADP
ajst-31230	16	72	deep	deep	ADJ
ajst-31230	16	73	learning	learning	NOUN
ajst-31230	16	74	approaches	approach	NOUN
ajst-31230	16	75	.	.	PUNCT
ajst-31230	17	1	in	in	ADP
ajst-31230	17	2	anomaly	anomaly	NOUN
ajst-31230	17	3	detection	detection	NOUN
ajst-31230	17	4	tasks	task	NOUN
ajst-31230	17	5	,	,	PUNCT
ajst-31230	17	6	feature	feature	NOUN
ajst-31230	17	7	extraction	extraction	NOUN
ajst-31230	17	8	plays	play	VERB
ajst-31230	17	9	a	a	DET
ajst-31230	17	10	critical	critical	ADJ
ajst-31230	17	11	role	role	NOUN
ajst-31230	17	12	.	.	PUNCT
ajst-31230	18	1	early	early	ADV
ajst-31230	18	2	widely	widely	ADV
ajst-31230	18	3	adopted	adopt	VERB
ajst-31230	18	4	mel	mel	PROPN
ajst-31230	18	5	125	125	NUM
ajst-31230	18	6	frequency	frequency	NOUN
ajst-31230	18	7	cepstral	cepstral	ADJ
ajst-31230	18	8	coefficients	coefficient	NOUN
ajst-31230	18	9	(	(	PUNCT
ajst-31230	18	10	mfcc	mfcc	NOUN
ajst-31230	18	11	)	)	PUNCT
ajst-31230	18	12	,	,	PUNCT
ajst-31230	18	13	though	though	SCONJ
ajst-31230	18	14	computationally	computationally	ADV
ajst-31230	18	15	efficient	efficient	ADJ
ajst-31230	18	16	,	,	PUNCT
ajst-31230	18	17	demonstrated	demonstrate	VERB
ajst-31230	18	18	limitations	limitation	NOUN
ajst-31230	18	19	in	in	ADP
ajst-31230	18	20	highfrequency	highfrequency	NOUN
ajst-31230	18	21	feature	feature	NOUN
ajst-31230	18	22	preservation	preservation	NOUN
ajst-31230	18	23	due	due	ADP
ajst-31230	18	24	to	to	ADP
ajst-31230	18	25	their	their	PRON
ajst-31230	18	26	anthropomorphic	anthropomorphic	ADJ
ajst-31230	18	27	auditory	auditory	ADJ
ajst-31230	18	28	modeling	modeling	NOUN
ajst-31230	18	29	bias	bias	NOUN
ajst-31230	18	30	toward	toward	ADP
ajst-31230	18	31	low	low	ADJ
ajst-31230	18	32	-	-	PUNCT
ajst-31230	18	33	frequency	frequency	NOUN
ajst-31230	18	34	characteristics	characteristic	NOUN
ajst-31230	18	35	.	.	PUNCT
ajst-31230	19	1	this	this	DET
ajst-31230	19	2	deficiency	deficiency	NOUN
ajst-31230	19	3	becomes	becomes	AUX
ajst-31230	19	4	particularly	particularly	ADV
ajst-31230	19	5	pronounced	pronounce	VERB
ajst-31230	19	6	in	in	ADP
ajst-31230	19	7	noisy	noisy	ADJ
ajst-31230	19	8	industrial	industrial	ADJ
ajst-31230	19	9	environments	environment	NOUN
ajst-31230	19	10	,	,	PUNCT
ajst-31230	19	11	significantly	significantly	ADV
ajst-31230	19	12	constraining	constrain	VERB
ajst-31230	19	13	the	the	DET
ajst-31230	19	14	robustness	robustness	NOUN
ajst-31230	19	15	of	of	ADP
ajst-31230	19	16	conventional	conventional	ADJ
ajst-31230	19	17	approaches	approach	NOUN
ajst-31230	19	18	.	.	PUNCT
ajst-31230	20	1	to	to	PART
ajst-31230	20	2	address	address	VERB
ajst-31230	20	3	high	high	ADJ
ajst-31230	20	4	-	-	PUNCT
ajst-31230	20	5	frequency	frequency	NOUN
ajst-31230	20	6	information	information	NOUN
ajst-31230	20	7	loss	loss	NOUN
ajst-31230	20	8	,	,	PUNCT
ajst-31230	20	9	researchers	researcher	NOUN
ajst-31230	20	10	have	have	AUX
ajst-31230	20	11	introduced	introduce	VERB
ajst-31230	20	12	deep	deep	ADJ
ajst-31230	20	13	learning	learning	NOUN
ajst-31230	20	14	-	-	PUNCT
ajst-31230	20	15	based	base	VERB
ajst-31230	20	16	solutions	solution	NOUN
ajst-31230	20	17	like	like	ADP
ajst-31230	20	18	sincnet	sincnet	NOUN
ajst-31230	20	19	,	,	PUNCT
ajst-31230	20	20	which	which	PRON
ajst-31230	20	21	employs	employ	VERB
ajst-31230	20	22	learnable	learnable	ADJ
ajst-31230	20	23	bandpass	bandpass	NOUN
ajst-31230	20	24	filters	filter	NOUN
ajst-31230	20	25	to	to	PART
ajst-31230	20	26	substantially	substantially	ADV
ajst-31230	20	27	enhance	enhance	VERB
ajst-31230	20	28	the	the	DET
ajst-31230	20	29	capture	capture	NOUN
ajst-31230	20	30	of	of	ADP
ajst-31230	20	31	critical	critical	ADJ
ajst-31230	20	32	high	high	ADJ
ajst-31230	20	33	-	-	PUNCT
ajst-31230	20	34	frequency	frequency	NOUN
ajst-31230	20	35	features	feature	NOUN
ajst-31230	20	36	.	.	PUNCT
ajst-31230	21	1	this	this	DET
ajst-31230	21	2	study	study	NOUN
ajst-31230	21	3	adopts	adopt	VERB
ajst-31230	21	4	a	a	DET
ajst-31230	21	5	hybrid	hybrid	ADJ
ajst-31230	21	6	strategy	strategy	NOUN
ajst-31230	21	7	integrating	integrate	VERB
ajst-31230	21	8	log	log	NOUN
ajst-31230	21	9	-	-	PUNCT
ajst-31230	21	10	mel	mel	NOUN
ajst-31230	21	11	spectrograms	spectrogram	NOUN
ajst-31230	21	12	with	with	ADP
ajst-31230	21	13	sincnet	sincnet	PROPN
ajst-31230	21	14	spectrograms	spectrogram	NOUN
ajst-31230	21	15	.	.	PUNCT
ajst-31230	22	1	this	this	DET
ajst-31230	22	2	synergistic	synergistic	ADJ
ajst-31230	22	3	combination	combination	NOUN
ajst-31230	22	4	leverages	leverage	NOUN
ajst-31230	22	5	log	log	NOUN
ajst-31230	22	6	-	-	PUNCT
ajst-31230	22	7	mel	mel	PROPN
ajst-31230	22	8	’s	’s	PART
ajst-31230	22	9	superior	superior	ADJ
ajst-31230	22	10	low	low	ADJ
ajst-31230	22	11	-	-	PUNCT
ajst-31230	22	12	frequency	frequency	NOUN
ajst-31230	22	13	sound	sound	NOUN
ajst-31230	22	14	capture	capture	NOUN
ajst-31230	22	15	capability	capability	NOUN
ajst-31230	22	16	in	in	ADP
ajst-31230	22	17	industrial	industrial	ADJ
ajst-31230	22	18	production	production	NOUN
ajst-31230	22	19	environments	environment	NOUN
ajst-31230	22	20	and	and	CCONJ
ajst-31230	22	21	sincnet	sincnet	NOUN
ajst-31230	22	22	’s	’s	PART
ajst-31230	22	23	high	high	ADJ
ajst-31230	22	24	-	-	PUNCT
ajst-31230	22	25	frequency	frequency	NOUN
ajst-31230	22	26	resolution	resolution	NOUN
ajst-31230	22	27	advantages	advantage	NOUN
ajst-31230	22	28	,	,	PUNCT
ajst-31230	22	29	effectively	effectively	ADV
ajst-31230	22	30	enhancing	enhance	VERB
ajst-31230	22	31	feature	feature	NOUN
ajst-31230	22	32	representation	representation	NOUN
ajst-31230	22	33	in	in	ADP
ajst-31230	22	34	complex	complex	ADJ
ajst-31230	22	35	acoustic	acoustic	ADJ
ajst-31230	22	36	scenarios	scenario	NOUN
ajst-31230	22	37	[	[	X
ajst-31230	22	38	1	1	NUM
ajst-31230	22	39	]	]	PUNCT
ajst-31230	22	40	.	.	PUNCT
ajst-31230	23	1	with	with	ADP
ajst-31230	23	2	the	the	DET
ajst-31230	23	3	development	development	NOUN
ajst-31230	23	4	of	of	ADP
ajst-31230	23	5	machine	machine	NOUN
ajst-31230	23	6	learning	learn	VERB
ajst-31230	23	7	technology	technology	NOUN
ajst-31230	23	8	,	,	PUNCT
ajst-31230	23	9	many	many	ADJ
ajst-31230	23	10	studies	study	NOUN
ajst-31230	23	11	on	on	ADP
ajst-31230	23	12	abnormal	abnormal	ADJ
ajst-31230	23	13	sound	sound	NOUN
ajst-31230	23	14	detection	detection	NOUN
ajst-31230	23	15	in	in	ADP
ajst-31230	23	16	wind	wind	NOUN
ajst-31230	23	17	turbines	turbine	NOUN
ajst-31230	23	18	have	have	AUX
ajst-31230	23	19	adopted	adopt	VERB
ajst-31230	23	20	deep	deep	ADJ
ajst-31230	23	21	learning	learning	NOUN
ajst-31230	23	22	methods	method	NOUN
ajst-31230	23	23	.	.	PUNCT
ajst-31230	24	1	for	for	ADP
ajst-31230	24	2	example	example	NOUN
ajst-31230	24	3	,	,	PUNCT
ajst-31230	24	4	zhang	zhang	PROPN
ajst-31230	24	5	et	et	PROPN
ajst-31230	24	6	al	al	PROPN
ajst-31230	24	7	[	[	X
ajst-31230	24	8	2	2	NUM
ajst-31230	24	9	]	]	PUNCT
ajst-31230	24	10	proposed	propose	VERB
ajst-31230	24	11	a	a	DET
ajst-31230	24	12	gearbox	gearbox	NOUN
ajst-31230	24	13	fault	fault	NOUN
ajst-31230	24	14	detection	detection	NOUN
ajst-31230	24	15	method	method	NOUN
ajst-31230	24	16	based	base	VERB
ajst-31230	24	17	on	on	ADP
ajst-31230	24	18	time	time	NOUN
ajst-31230	24	19	-	-	PUNCT
ajst-31230	24	20	frequency	frequency	NOUN
ajst-31230	24	21	analysis	analysis	NOUN
ajst-31230	24	22	,	,	PUNCT
ajst-31230	24	23	which	which	PRON
ajst-31230	24	24	effectively	effectively	ADV
ajst-31230	24	25	dealt	deal	VERB
ajst-31230	24	26	with	with	ADP
ajst-31230	24	27	the	the	DET
ajst-31230	24	28	problem	problem	NOUN
ajst-31230	24	29	of	of	ADP
ajst-31230	24	30	weak	weak	ADJ
ajst-31230	24	31	fault	fault	NOUN
ajst-31230	24	32	feature	feature	NOUN
ajst-31230	24	33	extraction	extraction	NOUN
ajst-31230	24	34	in	in	ADP
ajst-31230	24	35	high	high	ADJ
ajst-31230	24	36	-	-	PUNCT
ajst-31230	24	37	noise	noise	NOUN
ajst-31230	24	38	environments.wang	environments.wang	X
ajst-31230	24	39	et	et	NOUN
ajst-31230	24	40	al	al	PROPN
ajst-31230	25	1	[	[	X
ajst-31230	25	2	3	3	NUM
ajst-31230	25	3	]	]	PUNCT
ajst-31230	25	4	realized	realize	VERB
ajst-31230	25	5	anomaly	anomaly	NOUN
ajst-31230	25	6	detection	detection	NOUN
ajst-31230	25	7	of	of	ADP
ajst-31230	25	8	wind	wind	NOUN
ajst-31230	25	9	turbine	turbine	NOUN
ajst-31230	25	10	gearboxes	gearbox	NOUN
ajst-31230	25	11	by	by	ADP
ajst-31230	25	12	reconstructing	reconstruct	VERB
ajst-31230	25	13	the	the	DET
ajst-31230	25	14	error	error	NOUN
ajst-31230	25	15	using	use	VERB
ajst-31230	25	16	a	a	DET
ajst-31230	25	17	deep	deep	ADJ
ajst-31230	25	18	selfencoder	selfencoder	NOUN
ajst-31230	25	19	,	,	PUNCT
ajst-31230	25	20	but	but	CCONJ
ajst-31230	25	21	it	it	PRON
ajst-31230	25	22	was	be	AUX
ajst-31230	25	23	still	still	ADV
ajst-31230	25	24	deficient	deficient	ADJ
ajst-31230	25	25	in	in	ADP
ajst-31230	25	26	high	high	ADJ
ajst-31230	25	27	-	-	PUNCT
ajst-31230	25	28	frequency	frequency	NOUN
ajst-31230	25	29	feature	feature	NOUN
ajst-31230	25	30	capture.deng	capture.deng	PROPN
ajst-31230	25	31	et	et	NOUN
ajst-31230	25	32	al	al	PROPN
ajst-31230	26	1	[	[	X
ajst-31230	26	2	4	4	X
ajst-31230	26	3	]	]	PUNCT
ajst-31230	26	4	designed	design	VERB
ajst-31230	26	5	a	a	DET
ajst-31230	26	6	lightweight	lightweight	ADJ
ajst-31230	26	7	convolutional	convolutional	ADJ
ajst-31230	26	8	neural	neural	ADJ
ajst-31230	26	9	network	network	NOUN
ajst-31230	26	10	for	for	ADP
ajst-31230	26	11	real	real	ADJ
ajst-31230	26	12	-	-	PUNCT
ajst-31230	26	13	time	time	NOUN
ajst-31230	26	14	industrial	industrial	ADJ
ajst-31230	26	15	anomaly	anomaly	NOUN
ajst-31230	26	16	detection	detection	NOUN
ajst-31230	26	17	,	,	PUNCT
ajst-31230	26	18	but	but	CCONJ
ajst-31230	26	19	the	the	DET
ajst-31230	26	20	robustness	robustness	NOUN
ajst-31230	26	21	in	in	ADP
ajst-31230	26	22	complex	complex	ADJ
ajst-31230	26	23	noise	noise	NOUN
ajst-31230	26	24	environments	environment	NOUN
ajst-31230	26	25	needs	need	VERB
ajst-31230	26	26	to	to	PART
ajst-31230	26	27	be	be	AUX
ajst-31230	26	28	improved.mobilenetv3	improved.mobilenetv3	ADJ
ajst-31230	26	29	,	,	PUNCT
ajst-31230	26	30	as	as	ADP
ajst-31230	26	31	a	a	DET
ajst-31230	26	32	lightweight	lightweight	ADJ
ajst-31230	26	33	convolutional	convolutional	ADJ
ajst-31230	26	34	neural	neural	ADJ
ajst-31230	26	35	network	network	NOUN
ajst-31230	26	36	,	,	PUNCT
ajst-31230	26	37	achieves	achieve	VERB
ajst-31230	26	38	efficient	efficient	ADJ
ajst-31230	26	39	feature	feature	NOUN
ajst-31230	26	40	extraction	extraction	NOUN
ajst-31230	26	41	while	while	SCONJ
ajst-31230	26	42	maintaining	maintain	VERB
ajst-31230	26	43	computational	computational	ADJ
ajst-31230	26	44	efficiency	efficiency	NOUN
ajst-31230	26	45	through	through	ADP
ajst-31230	26	46	techniques	technique	NOUN
ajst-31230	26	47	such	such	ADJ
ajst-31230	26	48	as	as	ADP
ajst-31230	26	49	depth	depth	NOUN
ajst-31230	26	50	-	-	PUNCT
ajst-31230	26	51	separable	separable	NOUN
ajst-31230	26	52	convolution	convolution	NOUN
ajst-31230	26	53	and	and	CCONJ
ajst-31230	26	54	dynamic	dynamic	ADJ
ajst-31230	26	55	frequency	frequency	NOUN
ajst-31230	26	56	-	-	PUNCT
ajst-31230	26	57	aware	aware	ADJ
ajst-31230	26	58	convolution	convolution	NOUN
ajst-31230	26	59	.	.	PUNCT
ajst-31230	27	1	dynamic	dynamic	ADJ
ajst-31230	27	2	frequencyaware	frequencyaware	NOUN
ajst-31230	27	3	convolution	convolution	NOUN
ajst-31230	27	4	can	can	AUX
ajst-31230	27	5	dynamically	dynamically	ADV
ajst-31230	27	6	adjust	adjust	VERB
ajst-31230	27	7	the	the	DET
ajst-31230	27	8	shape	shape	NOUN
ajst-31230	27	9	and	and	CCONJ
ajst-31230	27	10	size	size	NOUN
ajst-31230	27	11	of	of	ADP
ajst-31230	27	12	the	the	DET
ajst-31230	27	13	convolution	convolution	NOUN
ajst-31230	27	14	kernel	kernel	NOUN
ajst-31230	27	15	according	accord	VERB
ajst-31230	27	16	to	to	ADP
ajst-31230	27	17	the	the	DET
ajst-31230	27	18	frequency	frequency	NOUN
ajst-31230	27	19	distribution	distribution	NOUN
ajst-31230	27	20	of	of	ADP
ajst-31230	27	21	the	the	DET
ajst-31230	27	22	input	input	NOUN
ajst-31230	27	23	signal	signal	NOUN
ajst-31230	27	24	to	to	PART
ajst-31230	27	25	better	well	ADV
ajst-31230	27	26	capture	capture	VERB
ajst-31230	27	27	the	the	DET
ajst-31230	27	28	timefrequency	timefrequency	NOUN
ajst-31230	27	29	features.the	features.the	DET
ajst-31230	27	30	network	network	NOUN
ajst-31230	27	31	structure	structure	NOUN
ajst-31230	27	32	of	of	ADP
ajst-31230	27	33	mobilenetv3	mobilenetv3	PROPN
ajst-31230	27	34	fused	fuse	VERB
ajst-31230	27	35	with	with	ADP
ajst-31230	27	36	dynamic	dynamic	ADJ
ajst-31230	27	37	frequency	frequency	NOUN
ajst-31230	27	38	-	-	PUNCT
ajst-31230	27	39	aware	aware	ADJ
ajst-31230	27	40	convolution	convolution	NOUN
ajst-31230	27	41	has	have	VERB
ajst-31230	27	42	stronger	strong	ADJ
ajst-31230	27	43	robustness	robustness	NOUN
ajst-31230	27	44	and	and	CCONJ
ajst-31230	27	45	feature	feature	NOUN
ajst-31230	27	46	extraction	extraction	NOUN
ajst-31230	27	47	ability	ability	NOUN
ajst-31230	27	48	in	in	ADP
ajst-31230	27	49	complex	complex	ADJ
ajst-31230	27	50	noise	noise	NOUN
ajst-31230	27	51	environments.therefore	environments.therefore	NOUN
ajst-31230	27	52	,	,	PUNCT
ajst-31230	27	53	in	in	ADP
ajst-31230	27	54	this	this	DET
ajst-31230	27	55	paper	paper	NOUN
ajst-31230	27	56	,	,	PUNCT
ajst-31230	27	57	mobilenetv3	mobilenetv3	PROPN
ajst-31230	27	58	is	be	AUX
ajst-31230	27	59	chosen	choose	VERB
ajst-31230	27	60	as	as	ADP
ajst-31230	27	61	the	the	DET
ajst-31230	27	62	base	base	NOUN
ajst-31230	27	63	network	network	NOUN
ajst-31230	27	64	and	and	CCONJ
ajst-31230	27	65	combined	combine	VERB
ajst-31230	27	66	with	with	ADP
ajst-31230	27	67	the	the	DET
ajst-31230	27	68	dynamic	dynamic	ADJ
ajst-31230	27	69	frequency	frequency	NOUN
ajst-31230	27	70	-	-	PUNCT
ajst-31230	27	71	aware	aware	ADJ
ajst-31230	27	72	convolution	convolution	NOUN
ajst-31230	27	73	to	to	PART
ajst-31230	27	74	improve	improve	VERB
ajst-31230	27	75	the	the	DET
ajst-31230	27	76	performance	performance	NOUN
ajst-31230	27	77	of	of	ADP
ajst-31230	27	78	abnormal	abnormal	ADJ
ajst-31230	27	79	sound	sound	NOUN
ajst-31230	27	80	detection	detection	NOUN
ajst-31230	27	81	of	of	ADP
ajst-31230	27	82	wind	wind	NOUN
ajst-31230	27	83	turbines	turbine	NOUN
ajst-31230	27	84	.	.	PUNCT
ajst-31230	28	1	softpool	softpool	NOUN
ajst-31230	28	2	performs	perform	VERB
ajst-31230	28	3	weighted	weight	VERB
ajst-31230	28	4	aggregation	aggregation	NOUN
ajst-31230	28	5	of	of	ADP
ajst-31230	28	6	the	the	DET
ajst-31230	28	7	activation	activation	NOUN
ajst-31230	28	8	values	value	NOUN
ajst-31230	28	9	within	within	ADP
ajst-31230	28	10	the	the	DET
ajst-31230	28	11	pooling	pool	VERB
ajst-31230	28	12	window	window	NOUN
ajst-31230	28	13	through	through	ADP
ajst-31230	28	14	the	the	DET
ajst-31230	28	15	softmax	softmax	NOUN
ajst-31230	28	16	function	function	NOUN
ajst-31230	28	17	,	,	PUNCT
ajst-31230	28	18	which	which	PRON
ajst-31230	28	19	retains	retain	VERB
ajst-31230	28	20	more	more	ADV
ajst-31230	28	21	high	high	ADJ
ajst-31230	28	22	-	-	PUNCT
ajst-31230	28	23	frequency	frequency	NOUN
ajst-31230	28	24	detailed	detailed	ADJ
ajst-31230	28	25	features	feature	NOUN
ajst-31230	28	26	compared	compare	VERB
ajst-31230	28	27	to	to	ADP
ajst-31230	28	28	traditional	traditional	ADJ
ajst-31230	28	29	pooling	pooling	NOUN
ajst-31230	28	30	methods	method	NOUN
ajst-31230	28	31	[	[	X
ajst-31230	28	32	5	5	NUM
ajst-31230	28	33	]	]	PUNCT
ajst-31230	28	34	.	.	PUNCT
ajst-31230	29	1	this	this	DET
ajst-31230	29	2	method	method	NOUN
ajst-31230	29	3	shows	show	VERB
ajst-31230	29	4	the	the	DET
ajst-31230	29	5	advantage	advantage	NOUN
ajst-31230	29	6	of	of	ADP
ajst-31230	29	7	sensitivity	sensitivity	NOUN
ajst-31230	29	8	to	to	PART
ajst-31230	29	9	transient	transient	VERB
ajst-31230	29	10	components	component	NOUN
ajst-31230	29	11	in	in	ADP
ajst-31230	29	12	acoustic	acoustic	ADJ
ajst-31230	29	13	signal	signal	NOUN
ajst-31230	29	14	processing	processing	NOUN
ajst-31230	29	15	,	,	PUNCT
ajst-31230	29	16	and	and	CCONJ
ajst-31230	29	17	is	be	AUX
ajst-31230	29	18	especially	especially	ADV
ajst-31230	29	19	suitable	suitable	ADJ
ajst-31230	29	20	for	for	ADP
ajst-31230	29	21	feature	feature	NOUN
ajst-31230	29	22	extraction	extraction	NOUN
ajst-31230	29	23	in	in	ADP
ajst-31230	29	24	non	non	ADJ
ajst-31230	29	25	-	-	ADJ
ajst-31230	29	26	smooth	smooth	ADJ
ajst-31230	29	27	scenes	scene	NOUN
ajst-31230	29	28	.	.	PUNCT
ajst-31230	30	1	aiming	aim	VERB
ajst-31230	30	2	at	at	ADP
ajst-31230	30	3	the	the	DET
ajst-31230	30	4	problem	problem	NOUN
ajst-31230	30	5	that	that	SCONJ
ajst-31230	30	6	high	high	ADJ
ajst-31230	30	7	-	-	PUNCT
ajst-31230	30	8	frequency	frequency	NOUN
ajst-31230	30	9	transient	transient	NOUN
ajst-31230	30	10	impulses	impulse	NOUN
ajst-31230	30	11	are	be	AUX
ajst-31230	30	12	easily	easily	ADV
ajst-31230	30	13	lost	lose	VERB
ajst-31230	30	14	in	in	ADP
ajst-31230	30	15	the	the	DET
ajst-31230	30	16	abnormal	abnormal	ADJ
ajst-31230	30	17	sound	sound	NOUN
ajst-31230	30	18	of	of	ADP
ajst-31230	30	19	wind	wind	NOUN
ajst-31230	30	20	turbines	turbine	NOUN
ajst-31230	30	21	,	,	PUNCT
ajst-31230	30	22	this	this	DET
ajst-31230	30	23	paper	paper	NOUN
ajst-31230	30	24	adopts	adopt	VERB
ajst-31230	30	25	softpool	softpool	NOUN
ajst-31230	30	26	instead	instead	ADV
ajst-31230	30	27	of	of	ADP
ajst-31230	30	28	the	the	DET
ajst-31230	30	29	global	global	ADJ
ajst-31230	30	30	pooling	pool	VERB
ajst-31230	30	31	layer	layer	NOUN
ajst-31230	30	32	in	in	ADP
ajst-31230	30	33	the	the	DET
ajst-31230	30	34	mobilenetv3	mobilenetv3	PROPN
ajst-31230	30	35	network	network	NOUN
ajst-31230	30	36	to	to	PART
ajst-31230	30	37	strengthen	strengthen	VERB
ajst-31230	30	38	the	the	DET
ajst-31230	30	39	model	model	NOUN
ajst-31230	30	40	's	's	PART
ajst-31230	30	41	parsing	parsing	NOUN
ajst-31230	30	42	ability	ability	NOUN
ajst-31230	30	43	for	for	ADP
ajst-31230	30	44	key	key	ADJ
ajst-31230	30	45	acoustic	acoustic	ADJ
ajst-31230	30	46	features	feature	NOUN
ajst-31230	30	47	.	.	PUNCT
ajst-31230	31	1	in	in	ADP
ajst-31230	31	2	summary	summary	NOUN
ajst-31230	31	3	,	,	PUNCT
ajst-31230	31	4	this	this	DET
ajst-31230	31	5	paper	paper	NOUN
ajst-31230	31	6	chooses	choose	VERB
ajst-31230	31	7	to	to	PART
ajst-31230	31	8	use	use	VERB
ajst-31230	31	9	a	a	DET
ajst-31230	31	10	new	new	ADJ
ajst-31230	31	11	combination	combination	NOUN
ajst-31230	31	12	of	of	ADP
ajst-31230	31	13	acoustic	acoustic	ADJ
ajst-31230	31	14	features	feature	NOUN
ajst-31230	31	15	in	in	ADP
ajst-31230	31	16	sound	sound	ADJ
ajst-31230	31	17	extraction	extraction	NOUN
ajst-31230	31	18	by	by	ADP
ajst-31230	31	19	fusing	fuse	VERB
ajst-31230	31	20	mel	mel	PROPN
ajst-31230	31	21	spectrograms	spectrograms	PROPN
ajst-31230	31	22	and	and	CCONJ
ajst-31230	31	23	sincnet	sincnet	PROPN
ajst-31230	31	24	spectrograms	spectrogram	NOUN
ajst-31230	31	25	into	into	ADP
ajst-31230	31	26	ms	ms	PROPN
ajst-31230	31	27	spectrograms	spectrogram	NOUN
ajst-31230	31	28	,	,	PUNCT
ajst-31230	31	29	which	which	PRON
ajst-31230	31	30	is	be	AUX
ajst-31230	31	31	a	a	DET
ajst-31230	31	32	method	method	NOUN
ajst-31230	31	33	that	that	PRON
ajst-31230	31	34	can	can	AUX
ajst-31230	31	35	be	be	AUX
ajst-31230	31	36	better	well	ADV
ajst-31230	31	37	adapted	adapt	VERB
ajst-31230	31	38	to	to	ADP
ajst-31230	31	39	the	the	DET
ajst-31230	31	40	noisy	noisy	ADJ
ajst-31230	31	41	environment	environment	NOUN
ajst-31230	31	42	in	in	ADP
ajst-31230	31	43	the	the	DET
ajst-31230	31	44	working	work	VERB
ajst-31230	31	45	environment	environment	NOUN
ajst-31230	31	46	of	of	ADP
ajst-31230	31	47	wind	wind	NOUN
ajst-31230	31	48	turbines	turbine	NOUN
ajst-31230	31	49	.	.	PUNCT
ajst-31230	32	1	in	in	ADP
ajst-31230	32	2	terms	term	NOUN
ajst-31230	32	3	of	of	ADP
ajst-31230	32	4	neural	neural	ADJ
ajst-31230	32	5	network	network	NOUN
ajst-31230	32	6	,	,	PUNCT
ajst-31230	32	7	this	this	DET
ajst-31230	32	8	paper	paper	NOUN
ajst-31230	32	9	proposes	propose	VERB
ajst-31230	32	10	an	an	DET
ajst-31230	32	11	improved	improved	ADJ
ajst-31230	32	12	machine	machine	NOUN
ajst-31230	32	13	anomalous	anomalous	ADJ
ajst-31230	32	14	sound	sound	NOUN
ajst-31230	32	15	detection	detection	NOUN
ajst-31230	32	16	network	network	NOUN
ajst-31230	32	17	dsmobilenetv3	dsmobilenetv3	NOUN
ajst-31230	32	18	,	,	PUNCT
ajst-31230	32	19	which	which	PRON
ajst-31230	32	20	enhances	enhance	VERB
ajst-31230	32	21	the	the	DET
ajst-31230	32	22	feature	feature	NOUN
ajst-31230	32	23	processing	processing	NOUN
ajst-31230	32	24	capability	capability	NOUN
ajst-31230	32	25	and	and	CCONJ
ajst-31230	32	26	robustness	robustness	NOUN
ajst-31230	32	27	of	of	ADP
ajst-31230	32	28	the	the	DET
ajst-31230	32	29	network	network	NOUN
ajst-31230	32	30	by	by	ADP
ajst-31230	32	31	adding	add	VERB
ajst-31230	32	32	dynamic	dynamic	ADJ
ajst-31230	32	33	frequency	frequency	NOUN
ajst-31230	32	34	-	-	PUNCT
ajst-31230	32	35	aware	aware	ADJ
ajst-31230	32	36	convolution	convolution	NOUN
ajst-31230	32	37	and	and	CCONJ
ajst-31230	32	38	combining	combine	VERB
ajst-31230	32	39	with	with	ADP
ajst-31230	32	40	softpool	softpool	NOUN
ajst-31230	32	41	pooling	pool	VERB
ajst-31230	32	42	method	method	NOUN
ajst-31230	32	43	.	.	PUNCT
ajst-31230	33	1	the	the	DET
ajst-31230	33	2	technology	technology	NOUN
ajst-31230	33	3	roadmap	roadmap	NOUN
ajst-31230	33	4	is	be	AUX
ajst-31230	33	5	shown	show	VERB
ajst-31230	33	6	in	in	ADP
ajst-31230	33	7	figure	figure	NOUN
ajst-31230	33	8	.	.	PUNCT
ajst-31230	34	1	2	2	X
ajst-31230	34	2	.	.	X
ajst-31230	34	3	figure	figure	NOUN
ajst-31230	34	4	2	2	NUM
ajst-31230	34	5	.	.	PUNCT
ajst-31230	34	6	technology	technology	NOUN
ajst-31230	34	7	roadmap	roadmap	NOUN
ajst-31230	34	8	2	2	NUM
ajst-31230	34	9	.	.	PUNCT
ajst-31230	34	10	methods	method	NOUN
ajst-31230	34	11	2.1	2.1	NUM
ajst-31230	34	12	.	.	PUNCT
ajst-31230	35	1	feature	feature	NOUN
ajst-31230	35	2	extraction	extraction	NOUN
ajst-31230	35	3	the	the	DET
ajst-31230	35	4	log	log	NOUN
ajst-31230	35	5	-	-	PUNCT
ajst-31230	35	6	mel	mel	PROPN
ajst-31230	35	7	spectrogram	spectrogram	PROPN
ajst-31230	35	8	highlights	highlight	NOUN
ajst-31230	35	9	low	low	ADJ
ajst-31230	35	10	-	-	PUNCT
ajst-31230	35	11	frequency	frequency	NOUN
ajst-31230	35	12	harmonic	harmonic	ADJ
ajst-31230	35	13	features	feature	NOUN
ajst-31230	35	14	based	base	VERB
ajst-31230	35	15	on	on	ADP
ajst-31230	35	16	the	the	DET
ajst-31230	35	17	human	human	ADJ
ajst-31230	35	18	ear	ear	NOUN
ajst-31230	35	19	's	's	PART
ajst-31230	35	20	auditory	auditory	ADJ
ajst-31230	35	21	characteristics	characteristic	NOUN
ajst-31230	35	22	,	,	PUNCT
ajst-31230	35	23	but	but	CCONJ
ajst-31230	35	24	its	its	PRON
ajst-31230	35	25	fixed	fix	VERB
ajst-31230	35	26	filter	filter	NOUN
ajst-31230	35	27	has	have	VERB
ajst-31230	35	28	insufficient	insufficient	ADJ
ajst-31230	35	29	resolution	resolution	NOUN
ajst-31230	35	30	in	in	ADP
ajst-31230	35	31	the	the	DET
ajst-31230	35	32	high	high	ADJ
ajst-31230	35	33	-	-	PUNCT
ajst-31230	35	34	frequency	frequency	NOUN
ajst-31230	35	35	band	band	NOUN
ajst-31230	35	36	,	,	PUNCT
ajst-31230	35	37	making	make	VERB
ajst-31230	35	38	it	it	PRON
ajst-31230	35	39	difficult	difficult	ADJ
ajst-31230	35	40	to	to	PART
ajst-31230	35	41	capture	capture	VERB
ajst-31230	35	42	transient	transient	ADJ
ajst-31230	35	43	impact	impact	NOUN
ajst-31230	35	44	signals	signal	NOUN
ajst-31230	35	45	,	,	PUNCT
ajst-31230	35	46	while	while	SCONJ
ajst-31230	35	47	the	the	DET
ajst-31230	35	48	sincnet	sincnet	NOUN
ajst-31230	35	49	spectrogram	spectrogram	NOUN
ajst-31230	35	50	enhances	enhance	VERB
ajst-31230	35	51	high	high	ADJ
ajst-31230	35	52	-	-	PUNCT
ajst-31230	35	53	frequency	frequency	NOUN
ajst-31230	35	54	feature	feature	NOUN
ajst-31230	35	55	resolution	resolution	NOUN
ajst-31230	35	56	under	under	ADP
ajst-31230	35	57	noisy	noisy	ADJ
ajst-31230	35	58	environments	environment	NOUN
ajst-31230	35	59	by	by	ADP
ajst-31230	35	60	directly	directly	ADV
ajst-31230	35	61	modeling	model	VERB
ajst-31230	35	62	band	band	NOUN
ajst-31230	35	63	parameters	parameter	NOUN
ajst-31230	35	64	through	through	ADP
ajst-31230	35	65	learnable	learnable	ADJ
ajst-31230	35	66	band	band	NOUN
ajst-31230	35	67	-	-	PUNCT
ajst-31230	35	68	pass	pass	NOUN
ajst-31230	35	69	filters	filter	NOUN
ajst-31230	35	70	.	.	PUNCT
ajst-31230	36	1	the	the	DET
ajst-31230	36	2	ms	ms	PROPN
ajst-31230	36	3	spectrogram	spectrogram	NOUN
ajst-31230	36	4	is	be	AUX
ajst-31230	36	5	formed	form	VERB
ajst-31230	36	6	by	by	ADP
ajst-31230	36	7	combining	combine	VERB
ajst-31230	36	8	the	the	DET
ajst-31230	36	9	advantages	advantage	NOUN
ajst-31230	36	10	of	of	ADP
ajst-31230	36	11	the	the	DET
ajst-31230	36	12	two	two	NUM
ajst-31230	36	13	:	:	PUNCT
ajst-31230	36	14	log	log	PROPN
ajst-31230	36	15	-	-	PUNCT
ajst-31230	36	16	mel	mel	PROPN
ajst-31230	36	17	retains	retain	VERB
ajst-31230	36	18	the	the	DET
ajst-31230	36	19	low	low	ADJ
ajst-31230	36	20	-	-	PUNCT
ajst-31230	36	21	frequency	frequency	NOUN
ajst-31230	36	22	energy	energy	NOUN
ajst-31230	36	23	structure	structure	NOUN
ajst-31230	36	24	,	,	PUNCT
ajst-31230	36	25	and	and	CCONJ
ajst-31230	36	26	sincnet	sincnet	NOUN
ajst-31230	36	27	strengthens	strengthen	VERB
ajst-31230	36	28	the	the	DET
ajst-31230	36	29	high	high	ADJ
ajst-31230	36	30	-	-	PUNCT
ajst-31230	36	31	frequency	frequency	NOUN
ajst-31230	36	32	transient	transient	NOUN
ajst-31230	36	33	response	response	NOUN
ajst-31230	36	34	,	,	PUNCT
ajst-31230	36	35	forming	form	VERB
ajst-31230	36	36	a	a	DET
ajst-31230	36	37	feature	feature	NOUN
ajst-31230	36	38	expression	expression	NOUN
ajst-31230	36	39	that	that	PRON
ajst-31230	36	40	is	be	AUX
ajst-31230	36	41	complementary	complementary	ADJ
ajst-31230	36	42	to	to	ADP
ajst-31230	36	43	the	the	DET
ajst-31230	36	44	wide	wide	ADJ
ajst-31230	36	45	-	-	PUNCT
ajst-31230	36	46	frequency	frequency	NOUN
ajst-31230	36	47	coverage	coverage	NOUN
ajst-31230	36	48	and	and	CCONJ
ajst-31230	36	49	local	local	ADJ
ajst-31230	36	50	sensitivity	sensitivity	NOUN
ajst-31230	36	51	,	,	PUNCT
ajst-31230	36	52	and	and	CCONJ
ajst-31230	36	53	enhancing	enhance	VERB
ajst-31230	36	54	the	the	DET
ajst-31230	36	55	robustness	robustness	NOUN
ajst-31230	36	56	of	of	ADP
ajst-31230	36	57	the	the	DET
ajst-31230	36	58	detection	detection	NOUN
ajst-31230	36	59	of	of	ADP
ajst-31230	36	60	the	the	DET
ajst-31230	36	61	wind	wind	NOUN
ajst-31230	36	62	turbine	turbine	NOUN
ajst-31230	36	63	's	's	PART
ajst-31230	36	64	complex	complex	ADJ
ajst-31230	36	65	working	work	VERB
ajst-31230	36	66	conditions.the	conditions.the	DET
ajst-31230	36	67	extraction	extraction	NOUN
ajst-31230	36	68	process	process	NOUN
ajst-31230	36	69	of	of	ADP
ajst-31230	36	70	the	the	DET
ajst-31230	36	71	ms	ms	PROPN
ajst-31230	36	72	spectrogram	spectrogram	NOUN
ajst-31230	36	73	is	be	AUX
ajst-31230	36	74	shown	show	VERB
ajst-31230	36	75	in	in	ADP
ajst-31230	36	76	figure	figure	NOUN
ajst-31230	36	77	.	.	PUNCT
ajst-31230	37	1	3	3	X
ajst-31230	37	2	.	.	X
ajst-31230	37	3	figure	figure	NOUN
ajst-31230	37	4	3	3	NUM
ajst-31230	37	5	.	.	PUNCT
ajst-31230	38	1	ms	ms	NOUN
ajst-31230	38	2	spectrogram	spectrogram	NOUN
ajst-31230	38	3	extraction	extraction	NOUN
ajst-31230	38	4	process	process	NOUN
ajst-31230	38	5	126	126	NUM
ajst-31230	38	6	2.1.1	2.1.1	NUM
ajst-31230	38	7	.	.	PUNCT
ajst-31230	39	1	log	log	NOUN
ajst-31230	39	2	-	-	PUNCT
ajst-31230	39	3	mel	mel	PROPN
ajst-31230	39	4	extraction	extraction	NOUN
ajst-31230	39	5	log	log	NOUN
ajst-31230	39	6	-	-	PUNCT
ajst-31230	39	7	mel	mel	NOUN
ajst-31230	39	8	spectrograms	spectrogram	NOUN
ajst-31230	39	9	are	be	AUX
ajst-31230	39	10	suitable	suitable	ADJ
ajst-31230	39	11	for	for	ADP
ajst-31230	39	12	sound	sound	ADJ
ajst-31230	39	13	detection	detection	NOUN
ajst-31230	39	14	in	in	ADP
ajst-31230	39	15	industrial	industrial	ADJ
ajst-31230	39	16	production	production	NOUN
ajst-31230	39	17	environments	environment	NOUN
ajst-31230	39	18	,	,	PUNCT
ajst-31230	39	19	and	and	CCONJ
ajst-31230	39	20	in	in	ADP
ajst-31230	39	21	wind	wind	NOUN
ajst-31230	39	22	turbine	turbine	NOUN
ajst-31230	39	23	abnormal	abnormal	ADJ
ajst-31230	39	24	sound	sound	NOUN
ajst-31230	39	25	detection	detection	NOUN
ajst-31230	39	26	,	,	PUNCT
ajst-31230	39	27	log	log	NOUN
ajst-31230	39	28	-	-	PUNCT
ajst-31230	39	29	mel	mel	NOUN
ajst-31230	39	30	spectrograms	spectrogram	NOUN
ajst-31230	39	31	are	be	AUX
ajst-31230	39	32	used	use	VERB
ajst-31230	39	33	as	as	ADP
ajst-31230	39	34	audio	audio	ADJ
ajst-31230	39	35	feature	feature	NOUN
ajst-31230	39	36	representations	representation	NOUN
ajst-31230	39	37	,	,	PUNCT
ajst-31230	39	38	which	which	PRON
ajst-31230	39	39	are	be	AUX
ajst-31230	39	40	required	require	VERB
ajst-31230	39	41	to	to	PART
ajst-31230	39	42	be	be	AUX
ajst-31230	39	43	able	able	ADJ
ajst-31230	39	44	to	to	PART
ajst-31230	39	45	capture	capture	VERB
ajst-31230	39	46	the	the	DET
ajst-31230	39	47	key	key	ADJ
ajst-31230	39	48	information	information	NOUN
ajst-31230	39	49	of	of	ADP
ajst-31230	39	50	the	the	DET
ajst-31230	39	51	sound	sound	NOUN
ajst-31230	39	52	signal	signal	NOUN
ajst-31230	39	53	.	.	PUNCT
ajst-31230	40	1	its	its	PRON
ajst-31230	40	2	extraction	extraction	NOUN
ajst-31230	40	3	process	process	NOUN
ajst-31230	40	4	firstly	firstly	ADV
ajst-31230	40	5	,	,	PUNCT
ajst-31230	40	6	the	the	DET
ajst-31230	40	7	original	original	ADJ
ajst-31230	40	8	audio	audio	NOUN
ajst-31230	40	9	signal	signal	NOUN
ajst-31230	40	10	is	be	AUX
ajst-31230	40	11	divided	divide	VERB
ajst-31230	40	12	into	into	ADP
ajst-31230	40	13	frames	frame	NOUN
ajst-31230	40	14	,	,	PUNCT
ajst-31230	40	15	and	and	CCONJ
ajst-31230	40	16	the	the	DET
ajst-31230	40	17	long	long	ADJ
ajst-31230	40	18	signal	signal	NOUN
ajst-31230	40	19	is	be	AUX
ajst-31230	40	20	divided	divide	VERB
ajst-31230	40	21	into	into	ADP
ajst-31230	40	22	short	short	ADJ
ajst-31230	40	23	-	-	PUNCT
ajst-31230	40	24	time	time	NOUN
ajst-31230	40	25	frames	frame	NOUN
ajst-31230	40	26	,	,	PUNCT
ajst-31230	40	27	and	and	CCONJ
ajst-31230	40	28	the	the	DET
ajst-31230	40	29	length	length	NOUN
ajst-31230	40	30	of	of	ADP
ajst-31230	40	31	each	each	DET
ajst-31230	40	32	frame	frame	NOUN
ajst-31230	40	33	is	be	AUX
ajst-31230	40	34	n	n	PRON
ajst-31230	40	35	sampling	sample	VERB
ajst-31230	40	36	points.next	points.next	PRON
ajst-31230	40	37	,	,	PUNCT
ajst-31230	40	38	a	a	DET
ajst-31230	40	39	hamming	hamming	NOUN
ajst-31230	40	40	window	window	NOUN
ajst-31230	40	41			PROPN
ajst-31230	40	42	nw	nw	PUNCT
ajst-31230	40	43	is	be	AUX
ajst-31230	40	44	applied	apply	VERB
ajst-31230	40	45	to	to	ADP
ajst-31230	40	46	each	each	DET
ajst-31230	40	47	frame	frame	NOUN
ajst-31230	40	48	to	to	PART
ajst-31230	40	49	minimize	minimize	VERB
ajst-31230	40	50	the	the	DET
ajst-31230	40	51	spectral	spectral	ADJ
ajst-31230	40	52	leakage	leakage	NOUN
ajst-31230	40	53	,	,	PUNCT
ajst-31230	40	54	denoted	denote	VERB
ajst-31230	40	55	by	by	ADP
ajst-31230	40	56	the	the	DET
ajst-31230	40	57	formula	formula	NOUN
ajst-31230	40	58	(	(	PUNCT
ajst-31230	40	59	1	1	NUM
ajst-31230	40	60	):	):	PUNCT
ajst-31230	40	61			NOUN
ajst-31230	40	62			SYM
ajst-31230	40	63	1	1	NUM
ajst-31230	40	64	1	1	NUM
ajst-31230	40	65	2	2	NUM
ajst-31230	40	66	460540	460540	NUM
ajst-31230	40	67			PROPN
ajst-31230	40	68			NOUN
ajst-31230	40	69			PRON
ajst-31230	40	70			PROPN
ajst-31230	40	71			PROPN
ajst-31230	40	72			PROPN
ajst-31230	40	73			PROPN
ajst-31230	40	74			PROPN
ajst-31230	40	75	nn0	nn0	PROPN
ajst-31230	40	76	,	,	PUNCT
ajst-31230	40	77	n	n	CCONJ
ajst-31230	40	78	n	n	PRON
ajst-31230	40	79	cos	cos	PROPN
ajst-31230	40	80	..	..	PROPN
ajst-31230	40	81	nw	nw	PROPN
ajst-31230	40	82			PROPN
ajst-31230	40	83	(	(	PUNCT
ajst-31230	40	84	1	1	NUM
ajst-31230	40	85	)	)	PUNCT
ajst-31230	40	86	then	then	ADV
ajst-31230	40	87	,	,	PUNCT
ajst-31230	40	88	the	the	DET
ajst-31230	40	89	fast	fast	ADJ
ajst-31230	40	90	fourier	fourier	NOUN
ajst-31230	40	91	transform	transform	NOUN
ajst-31230	40	92	is	be	AUX
ajst-31230	40	93	applied	apply	VERB
ajst-31230	40	94	to	to	ADP
ajst-31230	40	95	the	the	DET
ajst-31230	40	96	windowed	windowed	ADJ
ajst-31230	40	97	signal	signal	NOUN
ajst-31230	40	98	to	to	PART
ajst-31230	40	99	obtain	obtain	VERB
ajst-31230	40	100	the	the	DET
ajst-31230	40	101	spectrum	spectrum	NOUN
ajst-31230	40	102	of	of	ADP
ajst-31230	40	103	each	each	DET
ajst-31230	40	104	frame	frame	NOUN
ajst-31230	40	105	.	.	PUNCT
ajst-31230	41	1			PROPN
ajst-31230	41	2	kx	kx	VERB
ajst-31230	41	3	in	in	ADP
ajst-31230	41	4	order	order	NOUN
ajst-31230	41	5	to	to	PART
ajst-31230	41	6	simulate	simulate	VERB
ajst-31230	41	7	the	the	DET
ajst-31230	41	8	human	human	ADJ
ajst-31230	41	9	auditory	auditory	ADJ
ajst-31230	41	10	system	system	NOUN
ajst-31230	41	11	's	's	PART
ajst-31230	41	12	perception	perception	NOUN
ajst-31230	41	13	of	of	ADP
ajst-31230	41	14	frequency	frequency	NOUN
ajst-31230	41	15	,	,	PUNCT
ajst-31230	41	16	the	the	DET
ajst-31230	41	17	linear	linear	ADJ
ajst-31230	41	18	spectrum	spectrum	NOUN
ajst-31230	41	19	is	be	AUX
ajst-31230	41	20	converted	convert	VERB
ajst-31230	41	21	to	to	ADP
ajst-31230	41	22	a	a	DET
ajst-31230	41	23	mel	mel	PROPN
ajst-31230	41	24	spectrum	spectrum	PROPN
ajst-31230	41	25	.	.	PUNCT
ajst-31230	42	1	the	the	DET
ajst-31230	42	2	conversion	conversion	NOUN
ajst-31230	42	3	relationship	relationship	NOUN
ajst-31230	42	4	between	between	ADP
ajst-31230	42	5	mel	mel	PROPN
ajst-31230	42	6	frequency	frequency	PROPN
ajst-31230	42	7	and	and	CCONJ
ajst-31230	42	8	actual	actual	ADJ
ajst-31230	42	9	frequency	frequency	NOUN
ajst-31230	42	10	is	be	AUX
ajst-31230	42	11	shown	show	VERB
ajst-31230	42	12	in	in	ADP
ajst-31230	42	13	equation	equation	NOUN
ajst-31230	42	14	(	(	PUNCT
ajst-31230	42	15	2	2	NUM
ajst-31230	42	16	):	):	PUNCT
ajst-31230	42	17			PROPN
ajst-31230	42	18			NUM
ajst-31230	42	19			PRON
ajst-31230	42	20			PROPN
ajst-31230	42	21			PROPN
ajst-31230	42	22			NOUN
ajst-31230	42	23			PROPN
ajst-31230	42	24	700	700	NUM
ajst-31230	42	25	12595	12595	NUM
ajst-31230	42	26	10	10	NUM
ajst-31230	42	27	f	f	PROPN
ajst-31230	42	28	logm	logm	PROPN
ajst-31230	42	29	(	(	PUNCT
ajst-31230	42	30	2	2	NUM
ajst-31230	42	31	)	)	PUNCT
ajst-31230	42	32	where	where	SCONJ
ajst-31230	42	33	f	f	PROPN
ajst-31230	42	34	is	be	AUX
ajst-31230	42	35	the	the	DET
ajst-31230	42	36	actual	actual	ADJ
ajst-31230	42	37	frequency	frequency	NOUN
ajst-31230	42	38	and	and	CCONJ
ajst-31230	42	39	m	m	NOUN
ajst-31230	42	40	is	be	AUX
ajst-31230	42	41	the	the	DET
ajst-31230	42	42	mel	mel	PROPN
ajst-31230	42	43	frequency	frequency	NOUN
ajst-31230	42	44	.	.	PUNCT
ajst-31230	43	1	the	the	DET
ajst-31230	43	2	spectrum	spectrum	NOUN
ajst-31230	43	3	is	be	AUX
ajst-31230	43	4	then	then	ADV
ajst-31230	43	5	filtered	filter	VERB
ajst-31230	43	6	by	by	ADP
ajst-31230	43	7	a	a	DET
ajst-31230	43	8	bank	bank	NOUN
ajst-31230	43	9	of	of	ADP
ajst-31230	43	10	mel	mel	PROPN
ajst-31230	43	11	filters	filter	NOUN
ajst-31230	43	12	,	,	PUNCT
ajst-31230	43	13	each	each	PRON
ajst-31230	43	14	covering	cover	VERB
ajst-31230	43	15	a	a	DET
ajst-31230	43	16	certain	certain	ADJ
ajst-31230	43	17	range	range	NOUN
ajst-31230	43	18	of	of	ADP
ajst-31230	43	19	mel	mel	PROPN
ajst-31230	43	20	frequencies	frequency	NOUN
ajst-31230	43	21	.	.	PUNCT
ajst-31230	44	1	after	after	ADP
ajst-31230	44	2	filtering	filter	VERB
ajst-31230	44	3	,	,	PUNCT
ajst-31230	44	4	the	the	DET
ajst-31230	44	5	logarithmic	logarithmic	ADJ
ajst-31230	44	6	energy	energy	NOUN
ajst-31230	44	7	of	of	ADP
ajst-31230	44	8	the	the	DET
ajst-31230	44	9	output	output	NOUN
ajst-31230	44	10	of	of	ADP
ajst-31230	44	11	each	each	DET
ajst-31230	44	12	filter	filter	NOUN
ajst-31230	44	13	is	be	AUX
ajst-31230	44	14	calculated	calculate	VERB
ajst-31230	44	15	to	to	PART
ajst-31230	44	16	obtain	obtain	VERB
ajst-31230	44	17	the	the	DET
ajst-31230	44	18	log	log	NOUN
ajst-31230	44	19	-	-	PUNCT
ajst-31230	44	20	mel	mel	PROPN
ajst-31230	44	21	spectrum	spectrum	NOUN
ajst-31230	44	22	.	.	PUNCT
ajst-31230	45	1	finally	finally	ADV
ajst-31230	45	2	,	,	PUNCT
ajst-31230	45	3	the	the	DET
ajst-31230	45	4	multiframe	multiframe	NOUN
ajst-31230	45	5	log	log	PROPN
ajst-31230	45	6	-	-	PUNCT
ajst-31230	45	7	mel	mel	PROPN
ajst-31230	45	8	spectrum	spectrum	PROPN
ajst-31230	45	9	is	be	AUX
ajst-31230	45	10	stitched	stitch	VERB
ajst-31230	45	11	into	into	ADP
ajst-31230	45	12	a	a	DET
ajst-31230	45	13	two	two	NUM
ajst-31230	45	14	-	-	PUNCT
ajst-31230	45	15	dimensional	dimensional	ADJ
ajst-31230	45	16	matrix	matrix	NOUN
ajst-31230	45	17	as	as	ADP
ajst-31230	45	18	the	the	DET
ajst-31230	45	19	log	log	NOUN
ajst-31230	45	20	-	-	PUNCT
ajst-31230	45	21	mel	mel	PROPN
ajst-31230	45	22	spectrogram	spectrogram	NOUN
ajst-31230	45	23	of	of	ADP
ajst-31230	45	24	the	the	DET
ajst-31230	45	25	audio	audio	ADJ
ajst-31230	45	26	signal	signal	NOUN
ajst-31230	45	27	[	[	X
ajst-31230	45	28	6	6	NUM
ajst-31230	45	29	]	]	PUNCT
ajst-31230	45	30	.	.	PUNCT
ajst-31230	46	1	2.1.2	2.1.2	X
ajst-31230	46	2	.	.	PUNCT
ajst-31230	46	3	sincnet	sincnet	NOUN
ajst-31230	46	4	extraction	extraction	NOUN
ajst-31230	46	5	sincnet	sincnet	NOUN
ajst-31230	46	6	is	be	AUX
ajst-31230	46	7	a	a	DET
ajst-31230	46	8	neural	neural	ADJ
ajst-31230	46	9	network	network	NOUN
ajst-31230	46	10	architecture	architecture	NOUN
ajst-31230	46	11	specialized	specialize	VERB
ajst-31230	46	12	in	in	ADP
ajst-31230	46	13	audio	audio	ADJ
ajst-31230	46	14	processing	processing	NOUN
ajst-31230	46	15	that	that	PRON
ajst-31230	46	16	provides	provide	VERB
ajst-31230	46	17	a	a	DET
ajst-31230	46	18	way	way	NOUN
ajst-31230	46	19	to	to	PART
ajst-31230	46	20	capture	capture	VERB
ajst-31230	46	21	the	the	DET
ajst-31230	46	22	timedomain	timedomain	ADJ
ajst-31230	46	23	features	feature	NOUN
ajst-31230	46	24	of	of	ADP
ajst-31230	46	25	audio	audio	ADJ
ajst-31230	46	26	signals	signal	NOUN
ajst-31230	46	27	by	by	ADP
ajst-31230	46	28	using	use	VERB
ajst-31230	46	29	sinc	sinc	PROPN
ajst-31230	46	30	function	function	NOUN
ajst-31230	46	31	-	-	PUNCT
ajst-31230	46	32	based	base	VERB
ajst-31230	46	33	filters	filter	NOUN
ajst-31230	46	34	in	in	ADP
ajst-31230	46	35	the	the	DET
ajst-31230	46	36	first	first	ADJ
ajst-31230	46	37	convolutional	convolutional	ADJ
ajst-31230	46	38	layer	layer	NOUN
ajst-31230	46	39	.	.	PUNCT
ajst-31230	47	1	unlike	unlike	ADP
ajst-31230	47	2	standard	standard	ADJ
ajst-31230	47	3	cnns	cnn	NOUN
ajst-31230	47	4	,	,	PUNCT
ajst-31230	47	5	which	which	PRON
ajst-31230	47	6	learn	learn	VERB
ajst-31230	47	7	all	all	DET
ajst-31230	47	8	elements	element	NOUN
ajst-31230	47	9	of	of	ADP
ajst-31230	47	10	each	each	DET
ajst-31230	47	11	filter	filter	NOUN
ajst-31230	47	12	,	,	PUNCT
ajst-31230	47	13	sincnet	sincnet	NOUN
ajst-31230	47	14	only	only	ADV
ajst-31230	47	15	learns	learn	VERB
ajst-31230	47	16	the	the	DET
ajst-31230	47	17	low	low	ADJ
ajst-31230	47	18	cutoff	cutoff	NOUN
ajst-31230	47	19	frequency	frequency	NOUN
ajst-31230	47	20	and	and	CCONJ
ajst-31230	47	21	the	the	DET
ajst-31230	47	22	high	high	ADJ
ajst-31230	47	23	cutoff	cutoff	NOUN
ajst-31230	47	24	frequency	frequency	NOUN
ajst-31230	47	25	of	of	ADP
ajst-31230	47	26	the	the	DET
ajst-31230	47	27	bandpass	bandpass	NOUN
ajst-31230	47	28	filter	filter	NOUN
ajst-31230	47	29	.	.	PUNCT
ajst-31230	48	1	learning	learn	VERB
ajst-31230	48	2	the	the	DET
ajst-31230	48	3	high	high	ADJ
ajst-31230	48	4	cutoff	cutoff	NOUN
ajst-31230	48	5	frequency	frequency	NOUN
ajst-31230	48	6	compensates	compensate	NOUN
ajst-31230	48	7	for	for	ADP
ajst-31230	48	8	log	log	NOUN
ajst-31230	48	9	-	-	PUNCT
ajst-31230	48	10	mel	mel	PROPN
ajst-31230	48	11	's	's	PART
ajst-31230	48	12	insensitivity	insensitivity	NOUN
ajst-31230	48	13	to	to	ADP
ajst-31230	48	14	high	high	ADJ
ajst-31230	48	15	frequencies	frequency	NOUN
ajst-31230	48	16	.	.	PUNCT
ajst-31230	49	1	the	the	DET
ajst-31230	49	2	sincnet	sincnet	NOUN
ajst-31230	49	3	workflow	workflow	NOUN
ajst-31230	49	4	mainly	mainly	ADV
ajst-31230	49	5	consists	consist	VERB
ajst-31230	49	6	of	of	ADP
ajst-31230	49	7	preprocessing	preprocessing	NOUN
ajst-31230	49	8	,	,	PUNCT
ajst-31230	49	9	designing	design	VERB
ajst-31230	49	10	a	a	DET
ajst-31230	49	11	set	set	NOUN
ajst-31230	49	12	of	of	ADP
ajst-31230	49	13	sinc	sinc	ADJ
ajst-31230	49	14	filters	filter	NOUN
ajst-31230	49	15	,	,	PUNCT
ajst-31230	49	16	and	and	CCONJ
ajst-31230	49	17	using	use	VERB
ajst-31230	49	18	the	the	DET
ajst-31230	49	19	sinc	sinc	PROPN
ajst-31230	49	20	filter	filter	PROPN
ajst-31230	49	21	bank	bank	PROPN
ajst-31230	49	22	to	to	PART
ajst-31230	49	23	convolve	convolve	VERB
ajst-31230	49	24	the	the	DET
ajst-31230	49	25	audio	audio	NOUN
ajst-31230	49	26	signal	signal	NOUN
ajst-31230	49	27	to	to	PART
ajst-31230	49	28	extract	extract	VERB
ajst-31230	49	29	features	feature	NOUN
ajst-31230	49	30	in	in	ADP
ajst-31230	49	31	each	each	DET
ajst-31230	49	32	frequency	frequency	NOUN
ajst-31230	49	33	band.the	band.the	DET
ajst-31230	49	34	sincnet	sincnet	NOUN
ajst-31230	49	35	filter	filter	NOUN
ajst-31230	49	36	feature	feature	NOUN
ajst-31230	49	37	extraction	extraction	NOUN
ajst-31230	49	38	operation	operation	NOUN
ajst-31230	49	39	is	be	AUX
ajst-31230	49	40	shown	show	VERB
ajst-31230	49	41	in	in	ADP
ajst-31230	49	42	equation	equation	NOUN
ajst-31230	49	43	(	(	PUNCT
ajst-31230	49	44	3	3	NUM
ajst-31230	49	45	):	):	PUNCT
ajst-31230	49	46			ADJ
ajst-31230	49	47			PUNCT
ajst-31230	49	48			ADJ
ajst-31230	49	49			NOUN
ajst-31230	49	50			NOUN
ajst-31230	49	51			PROPN
ajst-31230	49	52	k,	k,	PROPN
ajst-31230	49	53	...	...	PUNCT
ajst-31230	49	54	,,k	,,k	PUNCT
ajst-31230	49	55	,	,	PUNCT
ajst-31230	49	56	ngnxnx	ngnxnx	PROPN
ajst-31230	49	57	w	w	PROPN
ajst-31230	49	58	kk	kk	PROPN
ajst-31230	49	59	21	21	NUM
ajst-31230	49	60	(	(	PUNCT
ajst-31230	49	61	3	3	NUM
ajst-31230	49	62	)	)	PUNCT
ajst-31230	49	63	where	where	SCONJ
ajst-31230	49	64			ADJ
ajst-31230	49	65	nx	nx	PROPN
ajst-31230	49	66	denotes	denote	VERB
ajst-31230	49	67	the	the	DET
ajst-31230	49	68	input	input	NOUN
ajst-31230	49	69	raw	raw	ADJ
ajst-31230	49	70	sound	sound	NOUN
ajst-31230	49	71	signal	signal	NOUN
ajst-31230	49	72	,	,	PUNCT
ajst-31230	49	73	k	k	PROPN
ajst-31230	49	74	denotes	denote	VERB
ajst-31230	49	75	the	the	DET
ajst-31230	49	76	number	number	NOUN
ajst-31230	49	77	of	of	ADP
ajst-31230	49	78	sincnet	sincnet	NOUN
ajst-31230	49	79	filters	filter	NOUN
ajst-31230	49	80	,	,	PUNCT
ajst-31230	49	81	and	and	CCONJ
ajst-31230	49	82			PROPN
ajst-31230	49	83	ngwk	ngwk	PROPN
ajst-31230	49	84	denotes	denote	NOUN
ajst-31230	49	85	that	that	SCONJ
ajst-31230	49	86	it	it	PRON
ajst-31230	49	87	is	be	AUX
ajst-31230	49	88	the	the	DET
ajst-31230	49	89	kth	kth	PROPN
ajst-31230	49	90	sincnet	sincnet	NOUN
ajst-31230	49	91	filter	filter	NOUN
ajst-31230	49	92	.	.	PUNCT
ajst-31230	50	1	subsequently	subsequently	ADV
ajst-31230	50	2	,	,	PUNCT
ajst-31230	50	3	one	one	NUM
ajst-31230	50	4	-	-	PUNCT
ajst-31230	50	5	dimensional	dimensional	ADJ
ajst-31230	50	6	batch	batch	NOUN
ajst-31230	50	7	normalization	normalization	NOUN
ajst-31230	50	8	and	and	CCONJ
ajst-31230	50	9	relu	relu	NOUN
ajst-31230	50	10	nonlinear	nonlinear	ADJ
ajst-31230	50	11	activation	activation	NOUN
ajst-31230	50	12	functions	function	NOUN
ajst-31230	50	13	are	be	AUX
ajst-31230	50	14	applied	apply	VERB
ajst-31230	50	15	to	to	PART
ajst-31230	50	16	obtain	obtain	VERB
ajst-31230	50	17	the	the	DET
ajst-31230	50	18	filter	filter	NOUN
ajst-31230	50	19	outputs	output	NOUN
ajst-31230	50	20	.	.	PUNCT
ajst-31230	51	1	in	in	ADP
ajst-31230	51	2	order	order	NOUN
ajst-31230	51	3	to	to	PART
ajst-31230	51	4	make	make	VERB
ajst-31230	51	5	the	the	DET
ajst-31230	51	6	sincnet	sincnet	NOUN
ajst-31230	51	7	spectrograms	spectrogram	NOUN
ajst-31230	51	8	have	have	VERB
ajst-31230	51	9	the	the	DET
ajst-31230	51	10	same	same	ADJ
ajst-31230	51	11	dimensional	dimensional	ADJ
ajst-31230	51	12	size	size	NOUN
ajst-31230	51	13	as	as	ADP
ajst-31230	51	14	the	the	DET
ajst-31230	51	15	log	log	NOUN
ajst-31230	51	16	-	-	PUNCT
ajst-31230	51	17	meier	meier	PROPN
ajst-31230	51	18	spectrograms	spectrogram	NOUN
ajst-31230	51	19	,	,	PUNCT
ajst-31230	51	20	adaptive	adaptive	ADJ
ajst-31230	51	21	average	average	ADJ
ajst-31230	51	22	pooling	pooling	NOUN
ajst-31230	51	23	is	be	AUX
ajst-31230	51	24	used	use	VERB
ajst-31230	51	25	on	on	ADP
ajst-31230	51	26	the	the	DET
ajst-31230	51	27	output	output	NOUN
ajst-31230	51	28	of	of	ADP
ajst-31230	51	29	each	each	DET
ajst-31230	51	30	filter	filter	NOUN
ajst-31230	51	31			PROPN
ajst-31230	51	32	nxk	nxk	NOUN
ajst-31230	51	33	,	,	PUNCT
ajst-31230	51	34	which	which	PRON
ajst-31230	51	35	automatically	automatically	ADV
ajst-31230	51	36	adjusts	adjust	VERB
ajst-31230	51	37	the	the	DET
ajst-31230	51	38	size	size	NOUN
ajst-31230	51	39	of	of	ADP
ajst-31230	51	40	the	the	DET
ajst-31230	51	41	pooling	pool	VERB
ajst-31230	51	42	region	region	NOUN
ajst-31230	51	43	and	and	CCONJ
ajst-31230	51	44	the	the	DET
ajst-31230	51	45	step	step	NOUN
ajst-31230	51	46	size	size	NOUN
ajst-31230	51	47	according	accord	VERB
ajst-31230	51	48	to	to	ADP
ajst-31230	51	49	the	the	DET
ajst-31230	51	50	target	target	NOUN
ajst-31230	51	51	output	output	NOUN
ajst-31230	51	52	size	size	NOUN
ajst-31230	51	53	.	.	PUNCT
ajst-31230	52	1	the	the	DET
ajst-31230	52	2	operation	operation	NOUN
ajst-31230	52	3	procedure	procedure	NOUN
ajst-31230	52	4	is	be	AUX
ajst-31230	52	5	as	as	ADP
ajst-31230	52	6	in	in	ADP
ajst-31230	52	7	equation	equation	NOUN
ajst-31230	52	8	(	(	PUNCT
ajst-31230	52	9	4	4	NUM
ajst-31230	52	10	):	):	PUNCT
ajst-31230	52	11			ADJ
ajst-31230	52	12			PUNCT
ajst-31230	52	13			PROPN
ajst-31230	52	14			NOUN
ajst-31230	52	15	nxgpooladaptiveaunm	nxgpooladaptiveaunm	PROPN
ajst-31230	52	16	kk	kk	PROPN
ajst-31230	52	17			PRON
ajst-31230	52	18	(	(	PUNCT
ajst-31230	52	19	4	4	NUM
ajst-31230	52	20	)	)	PUNCT
ajst-31230	52	21	the	the	DET
ajst-31230	52	22	sincnet	sincnet	NOUN
ajst-31230	52	23	spectrogram	spectrogram	NOUN
ajst-31230	52	24	optimizes	optimize	VERB
ajst-31230	52	25	band	band	NOUN
ajst-31230	52	26	segmentation	segmentation	NOUN
ajst-31230	52	27	through	through	ADP
ajst-31230	52	28	end	end	NOUN
ajst-31230	52	29	-	-	PUNCT
ajst-31230	52	30	to	to	ADP
ajst-31230	52	31	-	-	PUNCT
ajst-31230	52	32	end	end	NOUN
ajst-31230	52	33	learning	learning	NOUN
ajst-31230	52	34	,	,	PUNCT
ajst-31230	52	35	autonomously	autonomously	ADV
ajst-31230	52	36	captures	capture	VERB
ajst-31230	52	37	subtle	subtle	ADJ
ajst-31230	52	38	frequency	frequency	NOUN
ajst-31230	52	39	-	-	PUNCT
ajst-31230	52	40	domain	domain	NOUN
ajst-31230	52	41	patterns	pattern	NOUN
ajst-31230	52	42	of	of	ADP
ajst-31230	52	43	devices	device	NOUN
ajst-31230	52	44	,	,	PUNCT
ajst-31230	52	45	and	and	CCONJ
ajst-31230	52	46	preserves	preserve	VERB
ajst-31230	52	47	phase	phase	NOUN
ajst-31230	52	48	information	information	NOUN
ajst-31230	52	49	in	in	ADP
ajst-31230	52	50	time	time	NOUN
ajst-31230	52	51	-	-	PUNCT
ajst-31230	52	52	domain	domain	NOUN
ajst-31230	52	53	convolution	convolution	NOUN
ajst-31230	52	54	to	to	PART
ajst-31230	52	55	improve	improve	VERB
ajst-31230	52	56	sensitivity	sensitivity	NOUN
ajst-31230	52	57	to	to	ADP
ajst-31230	52	58	shock	shock	NOUN
ajst-31230	52	59	-	-	PUNCT
ajst-31230	52	60	type	type	NOUN
ajst-31230	52	61	anomalies	anomaly	NOUN
ajst-31230	52	62	.	.	PUNCT
ajst-31230	53	1	however	however	ADV
ajst-31230	53	2	,	,	PUNCT
ajst-31230	53	3	its	its	PRON
ajst-31230	53	4	band	band	NOUN
ajst-31230	53	5	resolution	resolution	NOUN
ajst-31230	53	6	is	be	AUX
ajst-31230	53	7	limited	limit	VERB
ajst-31230	53	8	by	by	ADP
ajst-31230	53	9	the	the	DET
ajst-31230	53	10	number	number	NOUN
ajst-31230	53	11	of	of	ADP
ajst-31230	53	12	filters	filter	NOUN
ajst-31230	53	13	,	,	PUNCT
ajst-31230	53	14	which	which	PRON
ajst-31230	53	15	makes	make	VERB
ajst-31230	53	16	it	it	PRON
ajst-31230	53	17	difficult	difficult	ADJ
ajst-31230	53	18	to	to	PART
ajst-31230	53	19	cover	cover	VERB
ajst-31230	53	20	broadband	broadband	NOUN
ajst-31230	53	21	noise	noise	NOUN
ajst-31230	53	22	interference	interference	NOUN
ajst-31230	53	23	.	.	PUNCT
ajst-31230	54	1	therefore	therefore	ADV
ajst-31230	54	2	,	,	PUNCT
ajst-31230	54	3	this	this	DET
ajst-31230	54	4	paper	paper	NOUN
ajst-31230	54	5	fuses	fuse	VERB
ajst-31230	54	6	sincnet	sincnet	NOUN
ajst-31230	54	7	and	and	CCONJ
ajst-31230	54	8	log	log	PROPN
ajst-31230	54	9	-	-	PUNCT
ajst-31230	54	10	mel	mel	PROPN
ajst-31230	54	11	spectra	spectra	PROPN
ajst-31230	54	12	:	:	PUNCT
ajst-31230	54	13	log	log	PROPN
ajst-31230	54	14	-	-	PUNCT
ajst-31230	54	15	mel	mel	PROPN
ajst-31230	54	16	provides	provide	VERB
ajst-31230	54	17	global	global	ADJ
ajst-31230	54	18	energy	energy	NOUN
ajst-31230	54	19	distribution	distribution	NOUN
ajst-31230	54	20	,	,	PUNCT
ajst-31230	54	21	and	and	CCONJ
ajst-31230	54	22	sincnet	sincnet	NOUN
ajst-31230	54	23	focuses	focus	VERB
ajst-31230	54	24	on	on	ADP
ajst-31230	54	25	local	local	ADJ
ajst-31230	54	26	high	high	ADJ
ajst-31230	54	27	-	-	PUNCT
ajst-31230	54	28	frequency	frequency	NOUN
ajst-31230	54	29	details	detail	NOUN
ajst-31230	54	30	,	,	PUNCT
ajst-31230	54	31	forming	form	VERB
ajst-31230	54	32	complementary	complementary	ADJ
ajst-31230	54	33	acoustic	acoustic	ADJ
ajst-31230	54	34	representations	representation	NOUN
ajst-31230	54	35	to	to	PART
ajst-31230	54	36	enhance	enhance	VERB
ajst-31230	54	37	the	the	DET
ajst-31230	54	38	discriminative	discriminative	NOUN
ajst-31230	54	39	power	power	NOUN
ajst-31230	54	40	.	.	PUNCT
ajst-31230	55	1	2.1.3	2.1.3	NUM
ajst-31230	55	2	.	.	PUNCT
ajst-31230	55	3	spectrogram	spectrogram	NOUN
ajst-31230	55	4	fusion	fusion	NOUN
ajst-31230	55	5	in	in	ADP
ajst-31230	55	6	the	the	DET
ajst-31230	55	7	study	study	NOUN
ajst-31230	55	8	of	of	ADP
ajst-31230	55	9	acoustic	acoustic	ADJ
ajst-31230	55	10	feature	feature	NOUN
ajst-31230	55	11	fusion	fusion	NOUN
ajst-31230	55	12	,	,	PUNCT
ajst-31230	55	13	the	the	DET
ajst-31230	55	14	multimodal	multimodal	ADJ
ajst-31230	55	15	spectrogram	spectrogram	NOUN
ajst-31230	55	16	integration	integration	NOUN
ajst-31230	55	17	strategy	strategy	NOUN
ajst-31230	55	18	can	can	AUX
ajst-31230	55	19	improve	improve	VERB
ajst-31230	55	20	the	the	DET
ajst-31230	55	21	accuracy	accuracy	NOUN
ajst-31230	55	22	of	of	ADP
ajst-31230	55	23	anomaly	anomaly	NOUN
ajst-31230	55	24	detection	detection	NOUN
ajst-31230	55	25	in	in	ADP
ajst-31230	55	26	complex	complex	ADJ
ajst-31230	55	27	scenes	scene	NOUN
ajst-31230	55	28	by	by	ADP
ajst-31230	55	29	integrating	integrate	VERB
ajst-31230	55	30	features	feature	NOUN
ajst-31230	55	31	from	from	ADP
ajst-31230	55	32	different	different	ADJ
ajst-31230	55	33	frequency	frequency	NOUN
ajst-31230	55	34	domains	domain	NOUN
ajst-31230	55	35	.	.	PUNCT
ajst-31230	56	1	in	in	ADP
ajst-31230	56	2	this	this	DET
ajst-31230	56	3	paper	paper	NOUN
ajst-31230	56	4	,	,	PUNCT
ajst-31230	56	5	log	log	NOUN
ajst-31230	56	6	-	-	PUNCT
ajst-31230	56	7	mel	mel	NOUN
ajst-31230	56	8	spectrograms	spectrograms	PROPN
ajst-31230	56	9	and	and	CCONJ
ajst-31230	56	10	sincnet	sincnet	PROPN
ajst-31230	56	11	spectrograms	spectrogram	NOUN
ajst-31230	56	12	are	be	AUX
ajst-31230	56	13	spliced	splice	VERB
ajst-31230	56	14	with	with	ADP
ajst-31230	56	15	cross	cross	ADJ
ajst-31230	56	16	-	-	ADJ
ajst-31230	56	17	domain	domain	ADJ
ajst-31230	56	18	features	feature	NOUN
ajst-31230	56	19	to	to	PART
ajst-31230	56	20	form	form	VERB
ajst-31230	56	21	a	a	DET
ajst-31230	56	22	fusion	fusion	NOUN
ajst-31230	56	23	feature	feature	NOUN
ajst-31230	56	24	matrix	matrix	NOUN
ajst-31230	56	25	with	with	ADP
ajst-31230	56	26	complementary	complementary	ADJ
ajst-31230	56	27	characteristics	characteristic	NOUN
ajst-31230	56	28	.	.	PUNCT
ajst-31230	57	1	as	as	ADP
ajst-31230	57	2	in	in	ADP
ajst-31230	57	3	equation	equation	NOUN
ajst-31230	57	4	(	(	PUNCT
ajst-31230	57	5	5	5	NUM
ajst-31230	57	6	):	):	PUNCT
ajst-31230	57	7			NOUN
ajst-31230	57	8			SYM
ajst-31230	57	9			NOUN
ajst-31230	57	10			PROPN
ajst-31230	57	11			ADJ
ajst-31230	57	12			NOUN
ajst-31230	57	13			PROPN
ajst-31230	57	14			PROPN
ajst-31230	57	15			ADJ
ajst-31230	57	16			ADP
ajst-31230	57	17			NUM
ajst-31230	57	18			NUM
ajst-31230	57	19			NUM
ajst-31230	57	20			NOUN
ajst-31230	58	1			NOUN
ajst-31230	58	2			ADP
ajst-31230	58	3			ADJ
ajst-31230	58	4			PROPN
ajst-31230	58	5			PROPN
ajst-31230	58	6			PROPN
ajst-31230	58	7	sincmelmel	sincmelmel	PROPN
ajst-31230	58	8	sinc	sinc	PROPN
ajst-31230	58	9	sincsinc	sincsinc	PROPN
ajst-31230	58	10	mel	mel	PROPN
ajst-31230	58	11	mel	mel	PROPN
ajst-31230	58	12	melmel	melmel	PROPN
ajst-31230	58	13	fusion	fusion	PROPN
ajst-31230	58	14	cc	cc	PROPN
ajst-31230	58	15	,	,	PUNCT
ajst-31230	58	16	cc	cc	PROPN
ajst-31230	58	17	,	,	PUNCT
ajst-31230	58	18	t	t	PROPN
ajst-31230	58	19	,	,	PUNCT
ajst-31230	58	20	sf	sf	PROPN
ajst-31230	58	21	c	c	NOUN
ajst-31230	58	22	,	,	PUNCT
ajst-31230	58	23	c	c	X
ajst-31230	58	24	,	,	PUNCT
ajst-31230	58	25	t	t	PROPN
ajst-31230	58	26	,	,	PUNCT
ajst-31230	58	27	mf	mf	PROPN
ajst-31230	58	28	t	t	PROPN
ajst-31230	58	29	,	,	PUNCT
ajst-31230	58	30	cf	cf	NOUN
ajst-31230	58	31	1	1	NUM
ajst-31230	58	32	1	1	NUM
ajst-31230	59	1			NOUN
ajst-31230	59	2			NOUN
ajst-31230	59	3			NOUN
ajst-31230	59	4			NOUN
ajst-31230	59	5	(	(	PUNCT
ajst-31230	59	6	5	5	NUM
ajst-31230	59	7	)	)	PUNCT
ajst-31230	59	8	where	where	SCONJ
ajst-31230	59	9	melmel	melmel	ADJ
ajst-31230	59	10	,	,	PUNCT
ajst-31230	59	11			PROPN
ajst-31230	59	12	and	and	CCONJ
ajst-31230	59	13	sincsinc	sincsinc	NOUN
ajst-31230	59	14	,	,	PUNCT
ajst-31230	59	15			PROPN
ajst-31230	59	16	represent	represent	VERB
ajst-31230	59	17	the	the	DET
ajst-31230	59	18	channel	channel	NOUN
ajst-31230	59	19	statistics	statistic	NOUN
ajst-31230	59	20	,	,	PUNCT
ajst-31230	59	21	melc	melc	VERB
ajst-31230	59	22	and	and	CCONJ
ajst-31230	59	23	sincc	sincc	NOUN
ajst-31230	59	24	denote	denote	VERB
ajst-31230	59	25	the	the	DET
ajst-31230	59	26	channel	channel	NOUN
ajst-31230	59	27	dimensions	dimension	NOUN
ajst-31230	59	28	of	of	ADP
ajst-31230	59	29	the	the	DET
ajst-31230	59	30	two	two	NUM
ajst-31230	59	31	types	type	NOUN
ajst-31230	59	32	of	of	ADP
ajst-31230	59	33	spectrograms	spectrogram	NOUN
ajst-31230	59	34	,	,	PUNCT
ajst-31230	59	35	respectively	respectively	ADV
ajst-31230	59	36	,	,	PUNCT
ajst-31230	59	37	and	and	CCONJ
ajst-31230	59	38	melf	melf	NOUN
ajst-31230	59	39	preserves	preserve	VERB
ajst-31230	59	40	the	the	DET
ajst-31230	59	41	global	global	ADJ
ajst-31230	59	42	band	band	NOUN
ajst-31230	59	43	energy	energy	NOUN
ajst-31230	59	44	distribution	distribution	NOUN
ajst-31230	59	45	while	while	SCONJ
ajst-31230	59	46	sincf	sincf	NOUN
ajst-31230	59	47	focuses	focus	VERB
ajst-31230	59	48	on	on	ADP
ajst-31230	59	49	the	the	DET
ajst-31230	59	50	localized	localized	ADJ
ajst-31230	59	51	band	band	NOUN
ajst-31230	59	52	transient	transient	ADJ
ajst-31230	59	53	response	response	NOUN
ajst-31230	59	54	.	.	PUNCT
ajst-31230	60	1	using	use	VERB
ajst-31230	60	2	this	this	DET
ajst-31230	60	3	fusion	fusion	NOUN
ajst-31230	60	4	method	method	NOUN
ajst-31230	60	5	preserves	preserve	VERB
ajst-31230	60	6	the	the	DET
ajst-31230	60	7	advantages	advantage	NOUN
ajst-31230	60	8	of	of	ADP
ajst-31230	60	9	log	log	NOUN
ajst-31230	60	10	-	-	PUNCT
ajst-31230	60	11	mel	mel	NOUN
ajst-31230	60	12	spectrograms	spectrograms	PROPN
ajst-31230	60	13	and	and	CCONJ
ajst-31230	60	14	sincnet	sincnet	PROPN
ajst-31230	60	15	spectrograms	spectrogram	NOUN
ajst-31230	60	16	,	,	PUNCT
ajst-31230	60	17	allowing	allow	VERB
ajst-31230	60	18	the	the	DET
ajst-31230	60	19	two	two	NUM
ajst-31230	60	20	spectrograms	spectrogram	NOUN
ajst-31230	60	21	to	to	PART
ajst-31230	60	22	complement	complement	VERB
ajst-31230	60	23	each	each	DET
ajst-31230	60	24	other	other	ADJ
ajst-31230	60	25	in	in	ADP
ajst-31230	60	26	the	the	DET
ajst-31230	60	27	frequency	frequency	NOUN
ajst-31230	60	28	domain	domain	NOUN
ajst-31230	60	29	coverage	coverage	NOUN
ajst-31230	61	1	[	[	X
ajst-31230	61	2	7	7	NUM
ajst-31230	61	3	]	]	PUNCT
ajst-31230	61	4	.	.	PUNCT
ajst-31230	62	1	2.2	2.2	NUM
ajst-31230	62	2	.	.	PUNCT
ajst-31230	62	3	anomaly	anomaly	PROPN
ajst-31230	62	4	detection	detection	NOUN
ajst-31230	62	5	network	network	NOUN
ajst-31230	62	6	optimization	optimization	NOUN
ajst-31230	62	7	based	base	VERB
ajst-31230	62	8	on	on	ADP
ajst-31230	62	9	mobilenetv3	mobilenetv3	PROPN
ajst-31230	62	10	2.2.1	2.2.1	NUM
ajst-31230	62	11	.	.	PUNCT
ajst-31230	63	1	introduction	introduction	NOUN
ajst-31230	63	2	of	of	ADP
ajst-31230	63	3	the	the	DET
ajst-31230	63	4	dfc	dfc	NOUN
ajst-31230	63	5	module	module	NOUN
ajst-31230	63	6	in	in	ADP
ajst-31230	63	7	order	order	NOUN
ajst-31230	63	8	to	to	PART
ajst-31230	63	9	enhance	enhance	VERB
ajst-31230	63	10	the	the	DET
ajst-31230	63	11	model	model	NOUN
ajst-31230	63	12	's	's	PART
ajst-31230	63	13	ability	ability	NOUN
ajst-31230	63	14	to	to	PART
ajst-31230	63	15	extract	extract	VERB
ajst-31230	63	16	frequency	frequency	NOUN
ajst-31230	63	17	domain	domain	NOUN
ajst-31230	63	18	features	feature	NOUN
ajst-31230	63	19	of	of	ADP
ajst-31230	63	20	sound	sound	ADJ
ajst-31230	63	21	signals	signal	NOUN
ajst-31230	63	22	,	,	PUNCT
ajst-31230	63	23	this	this	DET
ajst-31230	63	24	paper	paper	NOUN
ajst-31230	63	25	introduces	introduce	VERB
ajst-31230	63	26	the	the	DET
ajst-31230	63	27	dynamic	dynamic	ADJ
ajst-31230	63	28	frequency	frequency	NOUN
ajst-31230	63	29	convolution	convolution	NOUN
ajst-31230	63	30	(	(	PUNCT
ajst-31230	63	31	dfc	dfc	NOUN
ajst-31230	63	32	)	)	PUNCT
ajst-31230	63	33	module	module	NOUN
ajst-31230	63	34	into	into	ADP
ajst-31230	63	35	the	the	DET
ajst-31230	63	36	mobilenetv3	mobilenetv3	PROPN
ajst-31230	63	37	network	network	NOUN
ajst-31230	63	38	structure	structure	NOUN
ajst-31230	63	39	.	.	PUNCT
ajst-31230	64	1	this	this	DET
ajst-31230	64	2	module	module	NOUN
ajst-31230	64	3	performs	perform	VERB
ajst-31230	64	4	multi	multi	ADJ
ajst-31230	64	5	-	-	ADJ
ajst-31230	64	6	scale	scale	ADJ
ajst-31230	64	7	frequency	frequency	NOUN
ajst-31230	64	8	analysis	analysis	NOUN
ajst-31230	64	9	of	of	ADP
ajst-31230	64	10	the	the	DET
ajst-31230	64	11	input	input	NOUN
ajst-31230	64	12	signal	signal	NOUN
ajst-31230	64	13	by	by	ADP
ajst-31230	64	14	means	mean	NOUN
ajst-31230	64	15	of	of	ADP
ajst-31230	64	16	a	a	DET
ajst-31230	64	17	learnable	learnable	ADJ
ajst-31230	64	18	frequency	frequency	NOUN
ajst-31230	64	19	domain	domain	NOUN
ajst-31230	64	20	filter	filter	NOUN
ajst-31230	64	21	bank	bank	NOUN
ajst-31230	64	22	,	,	PUNCT
ajst-31230	64	23	which	which	PRON
ajst-31230	64	24	,	,	PUNCT
ajst-31230	64	25	combined	combine	VERB
ajst-31230	64	26	with	with	ADP
ajst-31230	64	27	lightweight	lightweight	ADJ
ajst-31230	64	28	parameter	parameter	NOUN
ajst-31230	64	29	design	design	NOUN
ajst-31230	64	30	,	,	PUNCT
ajst-31230	64	31	enhances	enhance	VERB
ajst-31230	64	32	the	the	DET
ajst-31230	64	33	network	network	NOUN
ajst-31230	64	34	's	's	PART
ajst-31230	64	35	ability	ability	NOUN
ajst-31230	64	36	to	to	PART
ajst-31230	64	37	capture	capture	VERB
ajst-31230	64	38	high	high	ADJ
ajst-31230	64	39	-	-	PUNCT
ajst-31230	64	40	frequency	frequency	NOUN
ajst-31230	64	41	details	detail	NOUN
ajst-31230	64	42	without	without	ADP
ajst-31230	64	43	significantly	significantly	ADV
ajst-31230	64	44	increasing	increase	VERB
ajst-31230	64	45	the	the	DET
ajst-31230	64	46	computational	computational	ADJ
ajst-31230	64	47	volume	volume	NOUN
ajst-31230	64	48	[	[	X
ajst-31230	64	49	8].the	8].the	DET
ajst-31230	64	50	dfc	dfc	PROPN
ajst-31230	64	51	module	module	NOUN
ajst-31230	64	52	adopts	adopt	VERB
ajst-31230	64	53	a	a	DET
ajst-31230	64	54	dynamic	dynamic	ADJ
ajst-31230	64	55	weight	weight	NOUN
ajst-31230	64	56	allocation	allocation	NOUN
ajst-31230	64	57	mechanism	mechanism	NOUN
ajst-31230	64	58	,	,	PUNCT
ajst-31230	64	59	which	which	PRON
ajst-31230	64	60	adaptively	adaptively	ADV
ajst-31230	64	61	adjusts	adjust	VERB
ajst-31230	64	62	the	the	DET
ajst-31230	64	63	filter	filter	NOUN
ajst-31230	64	64	parameters	parameter	NOUN
ajst-31230	64	65	according	accord	VERB
ajst-31230	64	66	to	to	ADP
ajst-31230	64	67	the	the	DET
ajst-31230	64	68	127	127	NUM
ajst-31230	64	69	characteristics	characteristic	NOUN
ajst-31230	64	70	of	of	ADP
ajst-31230	64	71	the	the	DET
ajst-31230	64	72	input	input	NOUN
ajst-31230	64	73	spectrum	spectrum	NOUN
ajst-31230	64	74	,	,	PUNCT
ajst-31230	64	75	effectively	effectively	ADV
ajst-31230	64	76	extracting	extract	VERB
ajst-31230	64	77	the	the	DET
ajst-31230	64	78	non	non	ADJ
ajst-31230	64	79	-	-	ADJ
ajst-31230	64	80	smooth	smooth	ADJ
ajst-31230	64	81	high	high	ADJ
ajst-31230	64	82	-	-	PUNCT
ajst-31230	64	83	frequency	frequency	NOUN
ajst-31230	64	84	transient	transient	NOUN
ajst-31230	64	85	components	component	NOUN
ajst-31230	64	86	of	of	ADP
ajst-31230	64	87	the	the	DET
ajst-31230	64	88	anomalous	anomalous	ADJ
ajst-31230	64	89	sound	sound	NOUN
ajst-31230	64	90	.	.	PUNCT
ajst-31230	65	1	the	the	DET
ajst-31230	65	2	dfc	dfc	PROPN
ajst-31230	65	3	module	module	NOUN
ajst-31230	65	4	is	be	AUX
ajst-31230	65	5	connected	connect	VERB
ajst-31230	65	6	in	in	ADP
ajst-31230	65	7	parallel	parallel	NOUN
ajst-31230	65	8	with	with	ADP
ajst-31230	65	9	the	the	DET
ajst-31230	65	10	depth	depth	NOUN
ajst-31230	65	11	-	-	PUNCT
ajst-31230	65	12	separable	separable	NOUN
ajst-31230	65	13	convolutional	convolutional	ADJ
ajst-31230	65	14	layer	layer	NOUN
ajst-31230	65	15	of	of	ADP
ajst-31230	65	16	mobilenetv3	mobilenetv3	PROPN
ajst-31230	65	17	to	to	PART
ajst-31230	65	18	form	form	VERB
ajst-31230	65	19	a	a	DET
ajst-31230	65	20	complementary	complementary	ADJ
ajst-31230	65	21	feature	feature	NOUN
ajst-31230	65	22	fusion	fusion	NOUN
ajst-31230	65	23	structure	structure	NOUN
ajst-31230	65	24	,	,	PUNCT
ajst-31230	65	25	which	which	PRON
ajst-31230	65	26	takes	take	VERB
ajst-31230	65	27	into	into	ADP
ajst-31230	65	28	account	account	NOUN
ajst-31230	65	29	the	the	DET
ajst-31230	65	30	efficiency	efficiency	NOUN
ajst-31230	65	31	of	of	ADP
ajst-31230	65	32	the	the	DET
ajst-31230	65	33	model	model	NOUN
ajst-31230	65	34	operation	operation	NOUN
ajst-31230	65	35	and	and	CCONJ
ajst-31230	65	36	the	the	DET
ajst-31230	65	37	ability	ability	NOUN
ajst-31230	65	38	to	to	PART
ajst-31230	65	39	fine	fine	ADJ
ajst-31230	65	40	-	-	PUNCT
ajst-31230	65	41	tune	tune	NOUN
ajst-31230	65	42	the	the	DET
ajst-31230	65	43	expression	expression	NOUN
ajst-31230	65	44	of	of	ADP
ajst-31230	65	45	acoustic	acoustic	ADJ
ajst-31230	65	46	features.the	features.the	DET
ajst-31230	65	47	structure	structure	NOUN
ajst-31230	65	48	diagram	diagram	NOUN
ajst-31230	65	49	of	of	ADP
ajst-31230	65	50	the	the	DET
ajst-31230	65	51	dfc	dfc	PROPN
ajst-31230	65	52	module	module	NOUN
ajst-31230	65	53	is	be	AUX
ajst-31230	65	54	shown	show	VERB
ajst-31230	65	55	in	in	ADP
ajst-31230	65	56	figure	figure	NOUN
ajst-31230	65	57	.	.	PUNCT
ajst-31230	66	1	4	4	X
ajst-31230	66	2	.	.	X
ajst-31230	66	3	figure	figure	NOUN
ajst-31230	66	4	4	4	NUM
ajst-31230	66	5	.	.	PUNCT
ajst-31230	66	6	dfc	dfc	PROPN
ajst-31230	66	7	module	module	NOUN
ajst-31230	66	8	diagram	diagram	NOUN
ajst-31230	66	9	2.2.2	2.2.2	NUM
ajst-31230	66	10	.	.	PUNCT
ajst-31230	67	1	integration	integration	NOUN
ajst-31230	67	2	of	of	ADP
ajst-31230	67	3	the	the	DET
ajst-31230	67	4	softpool	softpool	NOUN
ajst-31230	67	5	in	in	ADP
ajst-31230	67	6	order	order	NOUN
ajst-31230	67	7	to	to	PART
ajst-31230	67	8	improve	improve	VERB
ajst-31230	67	9	the	the	DET
ajst-31230	67	10	model	model	NOUN
ajst-31230	67	11	's	's	PART
ajst-31230	67	12	ability	ability	NOUN
ajst-31230	67	13	to	to	PART
ajst-31230	67	14	extract	extract	VERB
ajst-31230	67	15	acoustic	acoustic	ADJ
ajst-31230	67	16	features	feature	NOUN
ajst-31230	67	17	in	in	ADP
ajst-31230	67	18	a	a	DET
ajst-31230	67	19	fine	fine	ADV
ajst-31230	67	20	-	-	PUNCT
ajst-31230	67	21	grained	grain	VERB
ajst-31230	67	22	way	way	NOUN
ajst-31230	67	23	,	,	PUNCT
ajst-31230	67	24	this	this	DET
ajst-31230	67	25	study	study	NOUN
ajst-31230	67	26	introduces	introduce	NOUN
ajst-31230	67	27	softpool	softpool	VERB
ajst-31230	67	28	to	to	PART
ajst-31230	67	29	replace	replace	VERB
ajst-31230	67	30	the	the	DET
ajst-31230	67	31	traditional	traditional	ADJ
ajst-31230	67	32	pooling	pooling	NOUN
ajst-31230	67	33	layer	layer	NOUN
ajst-31230	67	34	in	in	ADP
ajst-31230	67	35	mobilenetv3	mobilenetv3	PROPN
ajst-31230	67	36	.	.	PUNCT
ajst-31230	68	1	this	this	DET
ajst-31230	68	2	pooling	pooling	NOUN
ajst-31230	68	3	method	method	NOUN
ajst-31230	68	4	adopts	adopt	VERB
ajst-31230	68	5	an	an	DET
ajst-31230	68	6	exponentially	exponentially	ADV
ajst-31230	68	7	weighted	weight	VERB
ajst-31230	68	8	average	average	ADJ
ajst-31230	68	9	strategy	strategy	NOUN
ajst-31230	68	10	,	,	PUNCT
ajst-31230	68	11	which	which	PRON
ajst-31230	68	12	reduces	reduce	VERB
ajst-31230	68	13	the	the	DET
ajst-31230	68	14	spatial	spatial	ADJ
ajst-31230	68	15	resolution	resolution	NOUN
ajst-31230	68	16	through	through	ADP
ajst-31230	68	17	weighted	weighted	ADJ
ajst-31230	68	18	aggregation	aggregation	NOUN
ajst-31230	68	19	on	on	ADP
ajst-31230	68	20	the	the	DET
ajst-31230	68	21	basis	basis	NOUN
ajst-31230	68	22	of	of	ADP
ajst-31230	68	23	retaining	retain	VERB
ajst-31230	68	24	the	the	DET
ajst-31230	68	25	consistency	consistency	NOUN
ajst-31230	68	26	of	of	ADP
ajst-31230	68	27	the	the	DET
ajst-31230	68	28	input	input	NOUN
ajst-31230	68	29	and	and	CCONJ
ajst-31230	68	30	output	output	NOUN
ajst-31230	68	31	dimensions	dimension	NOUN
ajst-31230	68	32	,	,	PUNCT
ajst-31230	68	33	and	and	CCONJ
ajst-31230	68	34	reduces	reduce	VERB
ajst-31230	68	35	the	the	DET
ajst-31230	68	36	loss	loss	NOUN
ajst-31230	68	37	of	of	ADP
ajst-31230	68	38	high	high	ADJ
ajst-31230	68	39	-	-	PUNCT
ajst-31230	68	40	frequency	frequency	NOUN
ajst-31230	68	41	details	detail	NOUN
ajst-31230	68	42	compared	compare	VERB
ajst-31230	68	43	with	with	ADP
ajst-31230	68	44	maximum	maximum	ADJ
ajst-31230	68	45	pooling	pooling	NOUN
ajst-31230	68	46	[	[	X
ajst-31230	68	47	9	9	NUM
ajst-31230	68	48	]	]	PUNCT
ajst-31230	68	49	.	.	PUNCT
ajst-31230	69	1	aiming	aim	VERB
ajst-31230	69	2	at	at	ADP
ajst-31230	69	3	the	the	DET
ajst-31230	69	4	significant	significant	ADJ
ajst-31230	69	5	characteristics	characteristic	NOUN
ajst-31230	69	6	of	of	ADP
ajst-31230	69	7	high	high	ADJ
ajst-31230	69	8	-	-	PUNCT
ajst-31230	69	9	frequency	frequency	NOUN
ajst-31230	69	10	transient	transient	NOUN
ajst-31230	69	11	features	feature	NOUN
ajst-31230	69	12	in	in	ADP
ajst-31230	69	13	the	the	DET
ajst-31230	69	14	wind	wind	NOUN
ajst-31230	69	15	turbine	turbine	NOUN
ajst-31230	69	16	abnormal	abnormal	ADJ
ajst-31230	69	17	sound	sound	NOUN
ajst-31230	69	18	detection	detection	NOUN
ajst-31230	69	19	task	task	NOUN
ajst-31230	69	20	,	,	PUNCT
ajst-31230	69	21	softpool	softpool	NOUN
ajst-31230	69	22	can	can	AUX
ajst-31230	69	23	effectively	effectively	ADV
ajst-31230	69	24	alleviate	alleviate	VERB
ajst-31230	69	25	the	the	DET
ajst-31230	69	26	information	information	NOUN
ajst-31230	69	27	degradation	degradation	NOUN
ajst-31230	69	28	problem	problem	NOUN
ajst-31230	69	29	of	of	ADP
ajst-31230	69	30	traditional	traditional	ADJ
ajst-31230	69	31	pooling	pooling	NOUN
ajst-31230	69	32	and	and	CCONJ
ajst-31230	69	33	enhance	enhance	VERB
ajst-31230	69	34	the	the	DET
ajst-31230	69	35	robustness	robustness	NOUN
ajst-31230	69	36	.	.	PUNCT
ajst-31230	70	1	figure	figure	NOUN
ajst-31230	70	2	5	5	NUM
ajst-31230	70	3	shows	show	VERB
ajst-31230	70	4	the	the	DET
ajst-31230	70	5	schematic	schematic	ADJ
ajst-31230	70	6	diagram	diagram	NOUN
ajst-31230	70	7	of	of	ADP
ajst-31230	70	8	the	the	DET
ajst-31230	70	9	softpool	softpool	NOUN
ajst-31230	70	10	weighted	weight	VERB
ajst-31230	70	11	pooling	pool	VERB
ajst-31230	70	12	process	process	NOUN
ajst-31230	70	13	.	.	PUNCT
ajst-31230	71	1	its	its	PRON
ajst-31230	71	2	computational	computational	ADJ
ajst-31230	71	3	process	process	NOUN
ajst-31230	71	4	can	can	AUX
ajst-31230	71	5	be	be	AUX
ajst-31230	71	6	described	describe	VERB
ajst-31230	71	7	as	as	ADP
ajst-31230	71	8	equation	equation	NOUN
ajst-31230	71	9	(	(	PUNCT
ajst-31230	71	10	6	6	NUM
ajst-31230	71	11	):	):	PUNCT
ajst-31230	71	12			X
ajst-31230	71	13			PROPN
ajst-31230	71	14			PROPN
ajst-31230	71	15	rj	rj	PROPN
ajst-31230	72	1	a	a	PRON
ajst-31230	72	2	a	a	PRON
ajst-31230	73	1	i	i	PRON
ajst-31230	73	2	j	j	NOUN
ajst-31230	74	1	i	i	NOUN
ajst-31230	74	2	e	e	VERB
ajst-31230	74	3	e	e	X
ajst-31230	74	4	(	(	PUNCT
ajst-31230	74	5	6	6	NUM
ajst-31230	74	6	)	)	PUNCT
ajst-31230	74	7	where	where	SCONJ
ajst-31230	74	8	ia	ia	PROPN
ajst-31230	74	9	is	be	AUX
ajst-31230	74	10	the	the	DET
ajst-31230	74	11	activation	activation	NOUN
ajst-31230	74	12	value	value	NOUN
ajst-31230	74	13	of	of	ADP
ajst-31230	74	14	the	the	DET
ajst-31230	74	15	i	i	PROPN
ajst-31230	74	16	rd	rd	NOUN
ajst-31230	74	17	feature	feature	NOUN
ajst-31230	74	18	point	point	NOUN
ajst-31230	74	19	in	in	ADP
ajst-31230	74	20	the	the	DET
ajst-31230	74	21	feature	feature	NOUN
ajst-31230	74	22	region	region	NOUN
ajst-31230	74	23	r	r	NOUN
ajst-31230	74	24	and	and	CCONJ
ajst-31230	74	25	i	i	NOUN
ajst-31230	74	26	is	be	AUX
ajst-31230	74	27	the	the	DET
ajst-31230	74	28	normalized	normalize	VERB
ajst-31230	74	29	weight	weight	NOUN
ajst-31230	74	30	.	.	PUNCT
ajst-31230	75	1	the	the	DET
ajst-31230	75	2	method	method	NOUN
ajst-31230	75	3	strengthens	strengthen	VERB
ajst-31230	75	4	the	the	DET
ajst-31230	75	5	key	key	ADJ
ajst-31230	75	6	feature	feature	NOUN
ajst-31230	75	7	response	response	NOUN
ajst-31230	75	8	while	while	SCONJ
ajst-31230	75	9	suppressing	suppress	VERB
ajst-31230	75	10	noise	noise	NOUN
ajst-31230	75	11	,	,	PUNCT
ajst-31230	75	12	and	and	CCONJ
ajst-31230	75	13	is	be	AUX
ajst-31230	75	14	especially	especially	ADV
ajst-31230	75	15	suitable	suitable	ADJ
ajst-31230	75	16	for	for	ADP
ajst-31230	75	17	timefrequency	timefrequency	ADJ
ajst-31230	75	18	structure	structure	NOUN
ajst-31230	75	19	extraction	extraction	NOUN
ajst-31230	75	20	of	of	ADP
ajst-31230	75	21	non	non	ADJ
ajst-31230	75	22	-	-	ADJ
ajst-31230	75	23	stationary	stationary	ADJ
ajst-31230	75	24	mechanical	mechanical	ADJ
ajst-31230	75	25	acoustic	acoustic	ADJ
ajst-31230	75	26	signals	signal	NOUN
ajst-31230	75	27	.	.	PUNCT
ajst-31230	76	1	figure	figure	NOUN
ajst-31230	76	2	5	5	NUM
ajst-31230	76	3	.	.	NOUN
ajst-31230	76	4	softpool	softpool	NOUN
ajst-31230	76	5	calculation	calculation	NOUN
ajst-31230	76	6	process	process	NOUN
ajst-31230	76	7	128	128	NUM
ajst-31230	76	8	2.2.3	2.2.3	NUM
ajst-31230	76	9	.	.	PUNCT
ajst-31230	77	1	network	network	NOUN
ajst-31230	77	2	architecture	architecture	NOUN
ajst-31230	77	3	in	in	ADP
ajst-31230	77	4	this	this	DET
ajst-31230	77	5	paper	paper	NOUN
ajst-31230	77	6	,	,	PUNCT
ajst-31230	77	7	we	we	PRON
ajst-31230	77	8	integrate	integrate	VERB
ajst-31230	77	9	the	the	DET
ajst-31230	77	10	dynamic	dynamic	ADJ
ajst-31230	77	11	frequency	frequency	NOUN
ajst-31230	77	12	convolution	convolution	NOUN
ajst-31230	77	13	module	module	NOUN
ajst-31230	77	14	and	and	CCONJ
ajst-31230	77	15	optimize	optimize	VERB
ajst-31230	77	16	the	the	DET
ajst-31230	77	17	pooling	pool	VERB
ajst-31230	77	18	layer	layer	NOUN
ajst-31230	77	19	design	design	NOUN
ajst-31230	77	20	on	on	ADP
ajst-31230	77	21	the	the	DET
ajst-31230	77	22	basis	basis	NOUN
ajst-31230	77	23	of	of	ADP
ajst-31230	77	24	mobilenetv3	mobilenetv3	PROPN
ajst-31230	77	25	network	network	NOUN
ajst-31230	77	26	to	to	PART
ajst-31230	77	27	construct	construct	VERB
ajst-31230	77	28	a	a	DET
ajst-31230	77	29	lightweight	lightweight	ADJ
ajst-31230	77	30	acoustic	acoustic	ADJ
ajst-31230	77	31	feature	feature	NOUN
ajst-31230	77	32	extraction	extraction	NOUN
ajst-31230	77	33	network	network	NOUN
ajst-31230	77	34	,	,	PUNCT
ajst-31230	77	35	and	and	CCONJ
ajst-31230	77	36	the	the	DET
ajst-31230	77	37	overall	overall	ADJ
ajst-31230	77	38	architecture	architecture	NOUN
ajst-31230	77	39	is	be	AUX
ajst-31230	77	40	shown	show	VERB
ajst-31230	77	41	in	in	ADP
ajst-31230	77	42	figure	figure	NOUN
ajst-31230	77	43	6	6	NUM
ajst-31230	77	44	.	.	PUNCT
ajst-31230	77	45	figure	figure	VERB
ajst-31230	77	46	6	6	NUM
ajst-31230	77	47	.	.	PUNCT
ajst-31230	78	1	ds	ds	ADJ
ajst-31230	78	2	-	-	PUNCT
ajst-31230	78	3	mobilenetv3	mobilenetv3	NOUN
ajst-31230	78	4	network	network	NOUN
ajst-31230	78	5	architecture	architecture	VERB
ajst-31230	78	6	the	the	DET
ajst-31230	78	7	input	input	NOUN
ajst-31230	78	8	of	of	ADP
ajst-31230	78	9	the	the	DET
ajst-31230	78	10	network	network	NOUN
ajst-31230	78	11	is	be	AUX
ajst-31230	78	12	the	the	DET
ajst-31230	78	13	pre	pre	ADJ
ajst-31230	78	14	-	-	ADJ
ajst-31230	78	15	processed	process	VERB
ajst-31230	78	16	audio	audio	NOUN
ajst-31230	78	17	spectrogram	spectrogram	NOUN
ajst-31230	78	18	,	,	PUNCT
ajst-31230	78	19	and	and	CCONJ
ajst-31230	78	20	after	after	SCONJ
ajst-31230	78	21	the	the	DET
ajst-31230	78	22	shallow	shallow	ADJ
ajst-31230	78	23	features	feature	NOUN
ajst-31230	78	24	are	be	AUX
ajst-31230	78	25	extracted	extract	VERB
ajst-31230	78	26	by	by	ADP
ajst-31230	78	27	the	the	DET
ajst-31230	78	28	initial	initial	ADJ
ajst-31230	78	29	convolutional	convolutional	ADJ
ajst-31230	78	30	layer	layer	NOUN
ajst-31230	78	31	,	,	PUNCT
ajst-31230	78	32	the	the	DET
ajst-31230	78	33	multi	multi	ADJ
ajst-31230	78	34	-	-	ADJ
ajst-31230	78	35	level	level	ADJ
ajst-31230	78	36	feature	feature	NOUN
ajst-31230	78	37	abstraction	abstraction	NOUN
ajst-31230	78	38	is	be	AUX
ajst-31230	78	39	realized	realize	VERB
ajst-31230	78	40	by	by	ADP
ajst-31230	78	41	the	the	DET
ajst-31230	78	42	improved	improve	VERB
ajst-31230	78	43	bottleneck	bottleneck	NOUN
ajst-31230	78	44	modules	module	NOUN
ajst-31230	78	45	at	at	ADP
ajst-31230	78	46	multiple	multiple	ADJ
ajst-31230	78	47	levels	level	NOUN
ajst-31230	78	48	.	.	PUNCT
ajst-31230	79	1	each	each	DET
ajst-31230	79	2	bottleneck	bottleneck	NOUN
ajst-31230	79	3	module	module	NOUN
ajst-31230	79	4	adopts	adopt	VERB
ajst-31230	79	5	a	a	DET
ajst-31230	79	6	two	two	NUM
ajst-31230	79	7	-	-	PUNCT
ajst-31230	79	8	branch	branch	NOUN
ajst-31230	79	9	parallel	parallel	ADJ
ajst-31230	79	10	structure	structure	NOUN
ajst-31230	79	11	:	:	PUNCT
ajst-31230	79	12	the	the	DET
ajst-31230	79	13	main	main	ADJ
ajst-31230	79	14	branch	branch	NOUN
ajst-31230	79	15	retains	retain	VERB
ajst-31230	79	16	mobilenetv3	mobilenetv3	PROPN
ajst-31230	79	17	's	's	PART
ajst-31230	79	18	original	original	ADJ
ajst-31230	79	19	depth	depth	NOUN
ajst-31230	79	20	-	-	PUNCT
ajst-31230	79	21	separable	separable	NOUN
ajst-31230	79	22	convolution	convolution	NOUN
ajst-31230	79	23	and	and	CCONJ
ajst-31230	79	24	se	se	ADJ
ajst-31230	79	25	attention	attention	NOUN
ajst-31230	79	26	mechanism	mechanism	NOUN
ajst-31230	79	27	for	for	ADP
ajst-31230	79	28	spatial	spatial	ADJ
ajst-31230	79	29	feature	feature	NOUN
ajst-31230	79	30	extraction	extraction	NOUN
ajst-31230	79	31	and	and	CCONJ
ajst-31230	79	32	channel	channel	NOUN
ajst-31230	79	33	dimensionality	dimensionality	NOUN
ajst-31230	79	34	recalibration	recalibration	NOUN
ajst-31230	79	35	;	;	PUNCT
ajst-31230	79	36	the	the	DET
ajst-31230	79	37	newly	newly	ADV
ajst-31230	79	38	added	add	VERB
ajst-31230	79	39	dfc	dfc	NOUN
ajst-31230	79	40	module	module	NOUN
ajst-31230	79	41	performs	perform	VERB
ajst-31230	79	42	multiscale	multiscale	ADJ
ajst-31230	79	43	frequency	frequency	NOUN
ajst-31230	79	44	analysis	analysis	NOUN
ajst-31230	79	45	of	of	ADP
ajst-31230	79	46	the	the	DET
ajst-31230	79	47	input	input	NOUN
ajst-31230	79	48	signal	signal	NOUN
ajst-31230	79	49	through	through	ADP
ajst-31230	79	50	a	a	DET
ajst-31230	79	51	dynamic	dynamic	ADJ
ajst-31230	79	52	frequency	frequency	NOUN
ajst-31230	79	53	-	-	PUNCT
ajst-31230	79	54	domain	domain	NOUN
ajst-31230	79	55	filter	filter	NOUN
ajst-31230	79	56	bank	bank	NOUN
ajst-31230	79	57	,	,	PUNCT
ajst-31230	79	58	focusing	focus	VERB
ajst-31230	79	59	on	on	ADP
ajst-31230	79	60	capturing	capture	VERB
ajst-31230	79	61	the	the	DET
ajst-31230	79	62	high	high	ADJ
ajst-31230	79	63	-	-	PUNCT
ajst-31230	79	64	frequency	frequency	NOUN
ajst-31230	79	65	transient	transient	NOUN
ajst-31230	79	66	components	component	NOUN
ajst-31230	79	67	of	of	ADP
ajst-31230	79	68	the	the	DET
ajst-31230	79	69	anomalous	anomalous	ADJ
ajst-31230	79	70	sound	sound	NOUN
ajst-31230	79	71	.	.	PUNCT
ajst-31230	80	1	the	the	DET
ajst-31230	80	2	two	two	NUM
ajst-31230	80	3	-	-	PUNCT
ajst-31230	80	4	branch	branch	NOUN
ajst-31230	80	5	output	output	NOUN
ajst-31230	80	6	is	be	AUX
ajst-31230	80	7	feature	feature	NOUN
ajst-31230	80	8	spliced	splice	VERB
ajst-31230	80	9	and	and	CCONJ
ajst-31230	80	10	dimension	dimension	NOUN
ajst-31230	80	11	matching	matching	NOUN
ajst-31230	80	12	is	be	AUX
ajst-31230	80	13	realized	realize	VERB
ajst-31230	80	14	by	by	ADP
ajst-31230	80	15	1x1	1x1	NUM
ajst-31230	80	16	compression	compression	NOUN
ajst-31230	80	17	convolution	convolution	NOUN
ajst-31230	80	18	.	.	PUNCT
ajst-31230	81	1	at	at	ADP
ajst-31230	81	2	the	the	DET
ajst-31230	81	3	end	end	NOUN
ajst-31230	81	4	of	of	ADP
ajst-31230	81	5	the	the	DET
ajst-31230	81	6	network	network	NOUN
ajst-31230	81	7	,	,	PUNCT
ajst-31230	81	8	softpool	softpool	NOUN
ajst-31230	81	9	is	be	AUX
ajst-31230	81	10	used	use	VERB
ajst-31230	81	11	to	to	PART
ajst-31230	81	12	replace	replace	VERB
ajst-31230	81	13	the	the	DET
ajst-31230	81	14	conventional	conventional	ADJ
ajst-31230	81	15	global	global	ADJ
ajst-31230	81	16	average	average	ADJ
ajst-31230	81	17	pooling	pool	VERB
ajst-31230	81	18	layer	layer	NOUN
ajst-31230	81	19	to	to	PART
ajst-31230	81	20	avoid	avoid	VERB
ajst-31230	81	21	the	the	DET
ajst-31230	81	22	feature	feature	NOUN
ajst-31230	81	23	smoothing	smoothing	NOUN
ajst-31230	81	24	problem	problem	NOUN
ajst-31230	81	25	caused	cause	VERB
ajst-31230	81	26	by	by	ADP
ajst-31230	81	27	conventional	conventional	ADJ
ajst-31230	81	28	pooling	pool	VERB
ajst-31230	81	29	operations	operation	NOUN
ajst-31230	81	30	.	.	PUNCT
ajst-31230	82	1	this	this	DET
ajst-31230	82	2	design	design	NOUN
ajst-31230	82	3	significantly	significantly	ADV
ajst-31230	82	4	improves	improve	VERB
ajst-31230	82	5	the	the	DET
ajst-31230	82	6	resolution	resolution	NOUN
ajst-31230	82	7	of	of	ADP
ajst-31230	82	8	high	high	ADJ
ajst-31230	82	9	-	-	PUNCT
ajst-31230	82	10	frequency	frequency	NOUN
ajst-31230	82	11	acoustic	acoustic	ADJ
ajst-31230	82	12	features	feature	NOUN
ajst-31230	82	13	while	while	SCONJ
ajst-31230	82	14	maintaining	maintain	VERB
ajst-31230	82	15	the	the	DET
ajst-31230	82	16	efficient	efficient	ADJ
ajst-31230	82	17	computational	computational	ADJ
ajst-31230	82	18	characteristics	characteristic	NOUN
ajst-31230	82	19	of	of	ADP
ajst-31230	82	20	mobilenetv3	mobilenetv3	PROPN
ajst-31230	82	21	,	,	PUNCT
ajst-31230	82	22	which	which	PRON
ajst-31230	82	23	is	be	AUX
ajst-31230	82	24	suitable	suitable	ADJ
ajst-31230	82	25	for	for	ADP
ajst-31230	82	26	turbine	turbine	NOUN
ajst-31230	82	27	anomaly	anomaly	NOUN
ajst-31230	82	28	detection	detection	NOUN
ajst-31230	82	29	scenarios	scenario	NOUN
ajst-31230	82	30	under	under	ADP
ajst-31230	82	31	complex	complex	ADJ
ajst-31230	82	32	working	work	VERB
ajst-31230	82	33	conditions	condition	NOUN
ajst-31230	82	34	.	.	PUNCT
ajst-31230	83	1	3	3	X
ajst-31230	83	2	.	.	X
ajst-31230	83	3	experimental	experimental	ADJ
ajst-31230	83	4	data	datum	NOUN
ajst-31230	83	5	and	and	CCONJ
ajst-31230	83	6	analysis	analysis	NOUN
ajst-31230	83	7	3.1	3.1	NUM
ajst-31230	83	8	.	.	PUNCT
ajst-31230	84	1	data	datum	NOUN
ajst-31230	84	2	set	set	VERB
ajst-31230	84	3	the	the	DET
ajst-31230	84	4	experiment	experiment	NOUN
ajst-31230	84	5	uses	use	VERB
ajst-31230	84	6	the	the	DET
ajst-31230	84	7	wind	wind	NOUN
ajst-31230	84	8	turbine	turbine	NOUN
ajst-31230	84	9	acoustic	acoustic	ADJ
ajst-31230	84	10	data	datum	NOUN
ajst-31230	84	11	set	set	VERB
ajst-31230	84	12	[	[	X
ajst-31230	84	13	10	10	NUM
ajst-31230	84	14	]	]	PUNCT
ajst-31230	84	15	from	from	ADP
ajst-31230	84	16	the	the	DET
ajst-31230	84	17	danish	danish	PROPN
ajst-31230	84	18	university	university	PROPN
ajst-31230	84	19	of	of	ADP
ajst-31230	84	20	science	science	NOUN
ajst-31230	84	21	and	and	CCONJ
ajst-31230	84	22	technology	technology	NOUN
ajst-31230	84	23	,	,	PUNCT
ajst-31230	84	24	which	which	PRON
ajst-31230	84	25	contains	contain	VERB
ajst-31230	84	26	the	the	DET
ajst-31230	84	27	sound	sound	ADJ
ajst-31230	84	28	signals	signal	NOUN
ajst-31230	84	29	of	of	ADP
ajst-31230	84	30	the	the	DET
ajst-31230	84	31	three	three	NUM
ajst-31230	84	32	core	core	NOUN
ajst-31230	84	33	components	component	NOUN
ajst-31230	84	34	,	,	PUNCT
ajst-31230	84	35	namely	namely	ADV
ajst-31230	84	36	,	,	PUNCT
ajst-31230	84	37	gearbox	gearbox	NOUN
ajst-31230	84	38	,	,	PUNCT
ajst-31230	84	39	bearings	bearing	NOUN
ajst-31230	84	40	,	,	PUNCT
ajst-31230	84	41	and	and	CCONJ
ajst-31230	84	42	blades	blade	NOUN
ajst-31230	84	43	,	,	PUNCT
ajst-31230	84	44	under	under	ADP
ajst-31230	84	45	abnormal	abnormal	ADJ
ajst-31230	84	46	and	and	CCONJ
ajst-31230	84	47	normal	normal	ADJ
ajst-31230	84	48	conditions	condition	NOUN
ajst-31230	84	49	.	.	PUNCT
ajst-31230	85	1	the	the	DET
ajst-31230	85	2	total	total	ADJ
ajst-31230	85	3	number	number	NOUN
ajst-31230	85	4	of	of	ADP
ajst-31230	85	5	sound	sound	ADJ
ajst-31230	85	6	signal	signal	NOUN
ajst-31230	85	7	samples	sample	NOUN
ajst-31230	85	8	is	be	AUX
ajst-31230	85	9	8760	8760	NUM
ajst-31230	85	10	,	,	PUNCT
ajst-31230	85	11	of	of	ADP
ajst-31230	85	12	which	which	PRON
ajst-31230	85	13	the	the	DET
ajst-31230	85	14	number	number	NOUN
ajst-31230	85	15	of	of	ADP
ajst-31230	85	16	samples	sample	NOUN
ajst-31230	85	17	containing	contain	VERB
ajst-31230	85	18	only	only	ADV
ajst-31230	85	19	normal	normal	ADJ
ajst-31230	85	20	working	work	VERB
ajst-31230	85	21	condition	condition	NOUN
ajst-31230	85	22	sound	sound	NOUN
ajst-31230	85	23	data	datum	NOUN
ajst-31230	85	24	is	be	AUX
ajst-31230	85	25	6160	6160	NUM
ajst-31230	85	26	as	as	ADP
ajst-31230	85	27	the	the	DET
ajst-31230	85	28	training	training	NOUN
ajst-31230	85	29	set	set	NOUN
ajst-31230	85	30	.	.	PUNCT
ajst-31230	86	1	the	the	DET
ajst-31230	86	2	number	number	NOUN
ajst-31230	86	3	of	of	ADP
ajst-31230	86	4	samples	sample	NOUN
ajst-31230	86	5	containing	contain	VERB
ajst-31230	86	6	abnormal	abnormal	ADJ
ajst-31230	86	7	sound	sound	NOUN
ajst-31230	86	8	data	datum	NOUN
ajst-31230	86	9	is	be	AUX
ajst-31230	86	10	2600	2600	NUM
ajst-31230	86	11	,	,	PUNCT
ajst-31230	86	12	which	which	PRON
ajst-31230	86	13	is	be	AUX
ajst-31230	86	14	used	use	VERB
ajst-31230	86	15	as	as	ADP
ajst-31230	86	16	the	the	DET
ajst-31230	86	17	test	test	NOUN
ajst-31230	86	18	set	set	NOUN
ajst-31230	86	19	.	.	PUNCT
ajst-31230	87	1	the	the	DET
ajst-31230	87	2	duration	duration	NOUN
ajst-31230	87	3	of	of	ADP
ajst-31230	87	4	a	a	DET
ajst-31230	87	5	single	single	ADJ
ajst-31230	87	6	sample	sample	NOUN
ajst-31230	87	7	is	be	AUX
ajst-31230	87	8	5	5	NUM
ajst-31230	87	9	seconds	second	NOUN
ajst-31230	87	10	,	,	PUNCT
ajst-31230	87	11	the	the	DET
ajst-31230	87	12	sampling	sample	VERB
ajst-31230	87	13	rate	rate	NOUN
ajst-31230	87	14	is	be	AUX
ajst-31230	87	15	44.1	44.1	NUM
ajst-31230	87	16	khz	khz	NOUN
ajst-31230	87	17	,	,	PUNCT
ajst-31230	87	18	and	and	CCONJ
ajst-31230	87	19	the	the	DET
ajst-31230	87	20	background	background	NOUN
ajst-31230	87	21	wind	wind	NOUN
ajst-31230	87	22	noise	noise	NOUN
ajst-31230	87	23	environment	environment	NOUN
ajst-31230	87	24	is	be	AUX
ajst-31230	87	25	covered	cover	VERB
ajst-31230	87	26	by	by	ADP
ajst-31230	87	27	40	40	NUM
ajst-31230	87	28	-	-	SYM
ajst-31230	87	29	70	70	NUM
ajst-31230	87	30	db	db	NOUN
ajst-31230	87	31	,	,	PUNCT
ajst-31230	87	32	which	which	PRON
ajst-31230	87	33	highly	highly	ADV
ajst-31230	87	34	reproduces	reproduce	VERB
ajst-31230	87	35	the	the	DET
ajst-31230	87	36	complex	complex	ADJ
ajst-31230	87	37	working	working	NOUN
ajst-31230	87	38	conditions	condition	NOUN
ajst-31230	87	39	of	of	ADP
ajst-31230	87	40	wind	wind	NOUN
ajst-31230	87	41	farms	farm	NOUN
ajst-31230	87	42	.	.	PUNCT
ajst-31230	88	1	3.2	3.2	NUM
ajst-31230	88	2	.	.	PUNCT
ajst-31230	88	3	experimental	experimental	ADJ
ajst-31230	88	4	environment	environment	NOUN
ajst-31230	88	5	the	the	DET
ajst-31230	88	6	input	input	NOUN
ajst-31230	88	7	features	feature	NOUN
ajst-31230	88	8	are	be	AUX
ajst-31230	88	9	ms	ms	PROPN
ajst-31230	88	10	spectrograms	spectrogram	NOUN
ajst-31230	88	11	with	with	ADP
ajst-31230	88	12	a	a	DET
ajst-31230	88	13	dimension	dimension	NOUN
ajst-31230	88	14	of	of	ADP
ajst-31230	88	15	128×313×2	128×313×2	NUM
ajst-31230	88	16	,	,	PUNCT
ajst-31230	88	17	and	and	CCONJ
ajst-31230	88	18	the	the	DET
ajst-31230	88	19	joint	joint	ADJ
ajst-31230	88	20	characterization	characterization	NOUN
ajst-31230	88	21	of	of	ADP
ajst-31230	88	22	highfrequency	highfrequency	NOUN
ajst-31230	88	23	transient	transient	NOUN
ajst-31230	88	24	and	and	CCONJ
ajst-31230	88	25	low	low	ADJ
ajst-31230	88	26	-	-	PUNCT
ajst-31230	88	27	frequency	frequency	NOUN
ajst-31230	88	28	harmonic	harmonic	NOUN
ajst-31230	88	29	features	feature	NOUN
ajst-31230	88	30	is	be	AUX
ajst-31230	88	31	enhanced	enhance	VERB
ajst-31230	88	32	by	by	ADP
ajst-31230	88	33	frequency	frequency	NOUN
ajst-31230	88	34	domain	domain	NOUN
ajst-31230	88	35	complementarity	complementarity	NOUN
ajst-31230	88	36	.	.	PUNCT
ajst-31230	89	1	training	training	NOUN
ajst-31230	89	2	is	be	AUX
ajst-31230	89	3	performed	perform	VERB
ajst-31230	89	4	using	use	VERB
ajst-31230	89	5	the	the	DET
ajst-31230	89	6	adam	adam	PROPN
ajst-31230	89	7	optimizer	optimizer	NOUN
ajst-31230	89	8	with	with	ADP
ajst-31230	89	9	β1=0.9,β2=0.999	β1=0.9,β2=0.999	PROPN
ajst-31230	89	10	,	,	PUNCT
ajst-31230	89	11	an	an	DET
ajst-31230	89	12	initial	initial	ADJ
ajst-31230	89	13	learning	learning	NOUN
ajst-31230	89	14	rate	rate	NOUN
ajst-31230	89	15	of	of	ADP
ajst-31230	89	16	1e-5	1e-5	NUM
ajst-31230	89	17	,	,	PUNCT
ajst-31230	89	18	and	and	CCONJ
ajst-31230	89	19	a	a	DET
ajst-31230	89	20	batch	batch	NOUN
ajst-31230	89	21	size=64	size=64	NOUN
ajst-31230	89	22	for	for	ADP
ajst-31230	89	23	a	a	DET
ajst-31230	89	24	total	total	NOUN
ajst-31230	89	25	of	of	ADP
ajst-31230	89	26	200	200	NUM
ajst-31230	89	27	rounds	round	NOUN
ajst-31230	89	28	.	.	PUNCT
ajst-31230	90	1	the	the	DET
ajst-31230	90	2	data	data	NOUN
ajst-31230	90	3	enhancement	enhancement	NOUN
ajst-31230	90	4	includes	include	VERB
ajst-31230	90	5	time	time	NOUN
ajst-31230	90	6	domain	domain	NOUN
ajst-31230	90	7	stretching	stretching	NOUN
ajst-31230	90	8	,	,	PUNCT
ajst-31230	90	9	gaussian	gaussian	ADJ
ajst-31230	90	10	noise	noise	NOUN
ajst-31230	90	11	injection	injection	NOUN
ajst-31230	90	12	and	and	CCONJ
ajst-31230	90	13	frequency	frequency	NOUN
ajst-31230	90	14	domain	domain	NOUN
ajst-31230	90	15	masking	masking	NOUN
ajst-31230	90	16	to	to	PART
ajst-31230	90	17	improve	improve	VERB
ajst-31230	90	18	the	the	DET
ajst-31230	90	19	model	model	NOUN
ajst-31230	90	20	robustness	robustness	NOUN
ajst-31230	90	21	.	.	PUNCT
ajst-31230	91	1	the	the	DET
ajst-31230	91	2	development	development	NOUN
ajst-31230	91	3	platform	platform	NOUN
ajst-31230	91	4	used	use	VERB
ajst-31230	91	5	for	for	ADP
ajst-31230	91	6	the	the	DET
ajst-31230	91	7	experiments	experiment	NOUN
ajst-31230	91	8	is	be	AUX
ajst-31230	91	9	pycharm	pycharm	NOUN
ajst-31230	91	10	,	,	PUNCT
ajst-31230	91	11	conducted	conduct	VERB
ajst-31230	91	12	using	use	VERB
ajst-31230	91	13	pytorch	pytorch	NOUN
ajst-31230	91	14	1.13.0	1.13.0	NUM
ajst-31230	91	15	and	and	CCONJ
ajst-31230	91	16	python	python	NOUN
ajst-31230	91	17	3.7.13	3.7.13	NUM
ajst-31230	91	18	,	,	PUNCT
ajst-31230	91	19	with	with	ADP
ajst-31230	91	20	training	training	NOUN
ajst-31230	91	21	done	do	VERB
ajst-31230	91	22	on	on	ADP
ajst-31230	91	23	nvidia	nvidia	PROPN
ajst-31230	91	24	rtx	rtx	PROPN
ajst-31230	91	25	3090	3090	NUM
ajst-31230	91	26	gpus	gpu	NOUN
ajst-31230	91	27	,	,	PUNCT
ajst-31230	91	28	and	and	CCONJ
ajst-31230	91	29	edge	edge	NOUN
ajst-31230	91	30	deployment	deployment	NOUN
ajst-31230	91	31	testing	testing	NOUN
ajst-31230	91	32	based	base	VERB
ajst-31230	91	33	on	on	ADP
ajst-31230	91	34	a	a	DET
ajst-31230	91	35	jetson	jetson	PROPN
ajst-31230	91	36	nano	nano	NOUN
ajst-31230	91	37	with	with	ADP
ajst-31230	91	38	4	4	NUM
ajst-31230	91	39	gb	gb	NOUN
ajst-31230	91	40	of	of	ADP
ajst-31230	91	41	ram	ram	NOUN
ajst-31230	91	42	.	.	PUNCT
ajst-31230	92	1	3.3	3.3	NUM
ajst-31230	92	2	.	.	PUNCT
ajst-31230	93	1	evaluation	evaluation	NOUN
ajst-31230	93	2	indicators	indicator	NOUN
ajst-31230	93	3	enhanced	enhance	VERB
ajst-31230	93	4	accuracy	accuracy	NOUN
ajst-31230	93	5	gain	gain	NOUN
ajst-31230	93	6	(	(	PUNCT
ajst-31230	93	7	auc	auc	NOUN
ajst-31230	93	8	)	)	PUNCT
ajst-31230	93	9	and	and	CCONJ
ajst-31230	93	10	partial	partial	ADJ
ajst-31230	93	11	enhanced	enhanced	ADJ
ajst-31230	93	12	accuracy	accuracy	NOUN
ajst-31230	93	13	gain	gain	NOUN
ajst-31230	93	14	(	(	PUNCT
ajst-31230	93	15	pauc	pauc	NOUN
ajst-31230	93	16	)	)	PUNCT
ajst-31230	93	17	are	be	AUX
ajst-31230	93	18	used	use	VERB
ajst-31230	93	19	as	as	ADP
ajst-31230	93	20	the	the	DET
ajst-31230	93	21	core	core	NOUN
ajst-31230	93	22	classification	classification	NOUN
ajst-31230	93	23	metrics	metric	NOUN
ajst-31230	93	24	to	to	PART
ajst-31230	93	25	evaluate	evaluate	VERB
ajst-31230	93	26	the	the	DET
ajst-31230	93	27	model	model	NOUN
ajst-31230	93	28	performance	performance	NOUN
ajst-31230	93	29	.	.	PUNCT
ajst-31230	94	1	auc	auc	NOUN
ajst-31230	94	2	is	be	AUX
ajst-31230	94	3	defined	define	VERB
ajst-31230	94	4	as	as	ADP
ajst-31230	94	5	the	the	DET
ajst-31230	94	6	area	area	NOUN
ajst-31230	94	7	under	under	ADP
ajst-31230	94	8	the	the	DET
ajst-31230	94	9	roc	roc	PROPN
ajst-31230	94	10	curve	curve	NOUN
ajst-31230	94	11	,	,	PUNCT
ajst-31230	94	12	which	which	PRON
ajst-31230	94	13	evaluates	evaluate	VERB
ajst-31230	94	14	the	the	DET
ajst-31230	94	15	overall	overall	ADJ
ajst-31230	94	16	anomaly	anomaly	NOUN
ajst-31230	94	17	detection	detection	NOUN
ajst-31230	94	18	capability	capability	NOUN
ajst-31230	94	19	.	.	PUNCT
ajst-31230	95	1	pauc	pauc	NOUN
ajst-31230	95	2	is	be	AUX
ajst-31230	95	3	defined	define	VERB
ajst-31230	95	4	as	as	ADP
ajst-31230	95	5	the	the	DET
ajst-31230	95	6	auc	auc	NOUN
ajst-31230	95	7	value	value	NOUN
ajst-31230	95	8	of	of	ADP
ajst-31230	95	9	the	the	DET
ajst-31230	95	10	restricted	restrict	VERB
ajst-31230	95	11	high	high	ADJ
ajst-31230	95	12	-	-	PUNCT
ajst-31230	95	13	frequency	frequency	NOUN
ajst-31230	95	14	anomaly	anomaly	NOUN
ajst-31230	95	15	samples	sample	NOUN
ajst-31230	95	16	,	,	PUNCT
ajst-31230	95	17	which	which	PRON
ajst-31230	95	18	is	be	AUX
ajst-31230	95	19	calculated	calculate	VERB
ajst-31230	95	20	in	in	ADP
ajst-31230	95	21	the	the	DET
ajst-31230	95	22	interval	interval	NOUN
ajst-31230	95	23	[	[	X
ajst-31230	95	24	0	0	NUM
ajst-31230	95	25	,	,	PUNCT
ajst-31230	95	26	p	p	X
ajst-31230	95	27	]	]	PUNCT
ajst-31230	95	28	where	where	SCONJ
ajst-31230	95	29	the	the	DET
ajst-31230	95	30	falsepositive	falsepositive	ADJ
ajst-31230	95	31	rate	rate	NOUN
ajst-31230	95	32	(	(	PUNCT
ajst-31230	95	33	fpr	fpr	NOUN
ajst-31230	95	34	)	)	PUNCT
ajst-31230	95	35	is	be	AUX
ajst-31230	95	36	low	low	ADJ
ajst-31230	95	37	.	.	PUNCT
ajst-31230	96	1	auc	auc	NOUN
ajst-31230	96	2	reflects	reflect	VERB
ajst-31230	96	3	the	the	DET
ajst-31230	96	4	the	the	DET
ajst-31230	96	5	magnitude	magnitude	NOUN
ajst-31230	96	6	of	of	ADP
ajst-31230	96	7	the	the	DET
ajst-31230	96	8	model	model	NOUN
ajst-31230	96	9	's	's	PART
ajst-31230	96	10	classification	classification	NOUN
ajst-31230	96	11	accuracy	accuracy	NOUN
ajst-31230	96	12	improvement	improvement	NOUN
ajst-31230	96	13	on	on	ADP
ajst-31230	96	14	the	the	DET
ajst-31230	96	15	noiseenhanced	noiseenhanced	ADJ
ajst-31230	96	16	test	test	NOUN
ajst-31230	96	17	set	set	NOUN
ajst-31230	96	18	,	,	PUNCT
ajst-31230	96	19	and	and	CCONJ
ajst-31230	96	20	calculates	calculate	VERB
ajst-31230	96	21	the	the	DET
ajst-31230	96	22	accuracy	accuracy	NOUN
ajst-31230	96	23	difference	difference	NOUN
ajst-31230	96	24	between	between	ADP
ajst-31230	96	25	the	the	DET
ajst-31230	96	26	improved	improved	ADJ
ajst-31230	96	27	model	model	NOUN
ajst-31230	96	28	and	and	CCONJ
ajst-31230	96	29	the	the	DET
ajst-31230	96	30	baseline	baseline	PROPN
ajst-31230	96	31	model	model	NOUN
ajst-31230	96	32	.	.	PUNCT
ajst-31230	97	1	pauc	pauc	ADV
ajst-31230	97	2	further	far	ADV
ajst-31230	97	3	refines	refine	VERB
ajst-31230	97	4	the	the	DET
ajst-31230	97	5	assessment	assessment	NOUN
ajst-31230	97	6	of	of	ADP
ajst-31230	97	7	the	the	DET
ajst-31230	97	8	proportion	proportion	NOUN
ajst-31230	97	9	of	of	ADP
ajst-31230	97	10	gain	gain	NOUN
ajst-31230	97	11	in	in	ADP
ajst-31230	97	12	high	high	ADJ
ajst-31230	97	13	-	-	PUNCT
ajst-31230	97	14	frequency	frequency	NOUN
ajst-31230	97	15	anomalous	anomalous	ADJ
ajst-31230	97	16	samples	sample	NOUN
ajst-31230	97	17	,	,	PUNCT
ajst-31230	97	18	and	and	CCONJ
ajst-31230	97	19	measures	measure	VERB
ajst-31230	97	20	the	the	DET
ajst-31230	97	21	model	model	NOUN
ajst-31230	97	22	's	's	PART
ajst-31230	97	23	sensitivity	sensitivity	NOUN
ajst-31230	97	24	to	to	ADP
ajst-31230	97	25	critical	critical	ADJ
ajst-31230	97	26	fault	fault	NOUN
ajst-31230	97	27	features	feature	NOUN
ajst-31230	97	28	.	.	PUNCT
ajst-31230	98	1	the	the	DET
ajst-31230	98	2	experiments	experiment	NOUN
ajst-31230	98	3	also	also	ADV
ajst-31230	98	4	count	count	VERB
ajst-31230	98	5	the	the	DET
ajst-31230	98	6	number	number	NOUN
ajst-31230	98	7	of	of	ADP
ajst-31230	98	8	parameters	parameter	NOUN
ajst-31230	98	9	,	,	PUNCT
ajst-31230	98	10	inference	inference	NOUN
ajst-31230	98	11	elapsed	elapse	VERB
ajst-31230	98	12	time	time	NOUN
ajst-31230	98	13	,	,	PUNCT
ajst-31230	98	14	and	and	CCONJ
ajst-31230	98	15	edge	edge	NOUN
ajst-31230	98	16	inference	inference	NOUN
ajst-31230	98	17	,	,	PUNCT
ajst-31230	98	18	and	and	CCONJ
ajst-31230	98	19	assess	assess	VERB
ajst-31230	98	20	metrics	metric	NOUN
ajst-31230	98	21	such	such	ADJ
ajst-31230	98	22	as	as	ADP
ajst-31230	98	23	computational	computational	ADJ
ajst-31230	98	24	power	power	NOUN
ajst-31230	98	25	and	and	CCONJ
ajst-31230	98	26	reliability	reliability	NOUN
ajst-31230	98	27	to	to	PART
ajst-31230	98	28	ensure	ensure	VERB
ajst-31230	98	29	that	that	SCONJ
ajst-31230	98	30	the	the	DET
ajst-31230	98	31	improved	improved	ADJ
ajst-31230	98	32	solution	solution	NOUN
ajst-31230	98	33	meets	meet	VERB
ajst-31230	98	34	the	the	DET
ajst-31230	98	35	lightweight	lightweight	ADJ
ajst-31230	98	36	deployment	deployment	NOUN
ajst-31230	98	37	requirements	requirement	NOUN
ajst-31230	98	38	.	.	PUNCT
ajst-31230	99	1	129	129	NUM
ajst-31230	99	2	3.4	3.4	NUM
ajst-31230	99	3	.	.	PUNCT
ajst-31230	100	1	ablation	ablation	NOUN
ajst-31230	100	2	experiments	experiment	NOUN
ajst-31230	100	3	to	to	PART
ajst-31230	100	4	validate	validate	VERB
ajst-31230	100	5	the	the	DET
ajst-31230	100	6	contribution	contribution	NOUN
ajst-31230	100	7	of	of	ADP
ajst-31230	100	8	dfc	dfc	PROPN
ajst-31230	100	9	and	and	CCONJ
ajst-31230	100	10	softpool	softpool	NOUN
ajst-31230	100	11	,	,	PUNCT
ajst-31230	100	12	the	the	DET
ajst-31230	100	13	following	follow	VERB
ajst-31230	100	14	comparison	comparison	NOUN
ajst-31230	100	15	experiments	experiment	NOUN
ajst-31230	100	16	are	be	AUX
ajst-31230	100	17	designed	design	VERB
ajst-31230	100	18	:	:	PUNCT
ajst-31230	100	19	table	table	NOUN
ajst-31230	100	20	1	1	NUM
ajst-31230	100	21	.	.	PUNCT
ajst-31230	100	22	ablation	ablation	NOUN
ajst-31230	100	23	comparison	comparison	NOUN
ajst-31230	100	24	experiments	experiment	VERB
ajst-31230	100	25	model	model	NOUN
ajst-31230	100	26	configuration	configuration	NOUN
ajst-31230	100	27	params	param	NOUN
ajst-31230	100	28	(	(	PUNCT
ajst-31230	100	29	m	m	NOUN
ajst-31230	100	30	)	)	PUNCT
ajst-31230	100	31	flops	flop	NOUN
ajst-31230	100	32	(	(	PUNCT
ajst-31230	100	33	g	g	NOUN
ajst-31230	100	34	)	)	PUNCT
ajst-31230	100	35	auc(%	auc(%	NOUN
ajst-31230	100	36	)	)	PUNCT
ajst-31230	100	37	pauc(%	pauc(%	NOUN
ajst-31230	100	38	)	)	PUNCT
ajst-31230	100	39	mobilenetv2	mobilenetv2	NOUN
ajst-31230	100	40	3.50	3.50	NUM
ajst-31230	100	41	0.535	0.535	NUM
ajst-31230	100	42	83.61	83.61	NUM
ajst-31230	100	43	mobilenetv3	mobilenetv3	NOUN
ajst-31230	100	44	2.10	2.10	NUM
ajst-31230	100	45	0.423	0.423	NUM
ajst-31230	100	46	89.14	89.14	NUM
ajst-31230	100	47	mobilenetv3+dfc	mobilenetv3+dfc	NOUN
ajst-31230	100	48	2.28	2.28	NUM
ajst-31230	100	49	0.439	0.439	NUM
ajst-31230	100	50	92.37	92.37	NUM
ajst-31230	100	51	87.92	87.92	NUM
ajst-31230	100	52	mobilenetv3+softpool	mobilenetv3+softpool	NOUN
ajst-31230	100	53	2.15	2.15	NUM
ajst-31230	100	54	0.428	0.428	NUM
ajst-31230	100	55	91.62	91.62	NUM
ajst-31230	100	56	88.45	88.45	NUM
ajst-31230	100	57	ds	ds	PROPN
ajst-31230	100	58	-	-	PUNCT
ajst-31230	100	59	mobilenetv3	mobilenetv3	NOUN
ajst-31230	100	60	2.38	2.38	NUM
ajst-31230	100	61	0.420	0.420	NUM
ajst-31230	100	62	94.71	94.71	NUM
ajst-31230	100	63	92.26	92.26	NUM
ajst-31230	100	64	the	the	DET
ajst-31230	100	65	effects	effect	NOUN
ajst-31230	100	66	of	of	ADP
ajst-31230	100	67	the	the	DET
ajst-31230	100	68	dfc	dfc	NOUN
ajst-31230	100	69	and	and	CCONJ
ajst-31230	100	70	softpool	softpool	NOUN
ajst-31230	100	71	modules	module	NOUN
ajst-31230	100	72	are	be	AUX
ajst-31230	100	73	verified	verify	VERB
ajst-31230	100	74	by	by	ADP
ajst-31230	100	75	a	a	DET
ajst-31230	100	76	module	module	NOUN
ajst-31230	100	77	-	-	PUNCT
ajst-31230	100	78	by	by	ADP
ajst-31230	100	79	-	-	PUNCT
ajst-31230	100	80	module	module	NOUN
ajst-31230	100	81	comparison	comparison	NOUN
ajst-31230	100	82	on	on	ADP
ajst-31230	100	83	a	a	DET
ajst-31230	100	84	machine	machine	NOUN
ajst-31230	100	85	anomaly	anomaly	NOUN
ajst-31230	100	86	sound	sound	NOUN
ajst-31230	100	87	dataset	dataset	VERB
ajst-31230	100	88	from	from	ADP
ajst-31230	100	89	the	the	DET
ajst-31230	100	90	technical	technical	ADJ
ajst-31230	100	91	university	university	PROPN
ajst-31230	100	92	of	of	ADP
ajst-31230	100	93	denmark	denmark	PROPN
ajst-31230	100	94	.	.	PUNCT
ajst-31230	101	1	as	as	SCONJ
ajst-31230	101	2	shown	show	VERB
ajst-31230	101	3	in	in	ADP
ajst-31230	101	4	table	table	NOUN
ajst-31230	101	5	1	1	NUM
ajst-31230	101	6	,	,	PUNCT
ajst-31230	101	7	the	the	DET
ajst-31230	101	8	dfc	dfc	NOUN
ajst-31230	101	9	module	module	NOUN
ajst-31230	101	10	alone	alone	ADV
ajst-31230	101	11	improves	improve	VERB
ajst-31230	101	12	the	the	DET
ajst-31230	101	13	auc	auc	NOUN
ajst-31230	101	14	by	by	ADP
ajst-31230	101	15	3.23	3.23	NUM
ajst-31230	101	16	%	%	NOUN
ajst-31230	101	17	,	,	PUNCT
ajst-31230	101	18	softpool	softpool	NOUN
ajst-31230	101	19	replaces	replace	VERB
ajst-31230	101	20	the	the	DET
ajst-31230	101	21	original	original	ADJ
ajst-31230	101	22	pooling	pooling	NOUN
ajst-31230	101	23	operation	operation	NOUN
ajst-31230	101	24	to	to	PART
ajst-31230	101	25	improve	improve	VERB
ajst-31230	101	26	the	the	DET
ajst-31230	101	27	auc	auc	NOUN
ajst-31230	101	28	by	by	ADP
ajst-31230	101	29	2.48	2.48	NUM
ajst-31230	101	30	%	%	NOUN
ajst-31230	101	31	,	,	PUNCT
ajst-31230	101	32	and	and	CCONJ
ajst-31230	101	33	the	the	DET
ajst-31230	101	34	two	two	NUM
ajst-31230	101	35	modules	module	NOUN
ajst-31230	101	36	synergistically	synergistically	ADV
ajst-31230	101	37	produce	produce	VERB
ajst-31230	101	38	a	a	DET
ajst-31230	101	39	gain	gain	NOUN
ajst-31230	101	40	-	-	PUNCT
ajst-31230	101	41	stacking	stack	VERB
ajst-31230	101	42	effect	effect	NOUN
ajst-31230	101	43	of	of	ADP
ajst-31230	101	44	1.35	1.35	NUM
ajst-31230	101	45	%	%	NOUN
ajst-31230	101	46	,	,	PUNCT
ajst-31230	101	47	and	and	CCONJ
ajst-31230	101	48	the	the	DET
ajst-31230	101	49	number	number	NOUN
ajst-31230	101	50	of	of	ADP
ajst-31230	101	51	parameters	parameter	NOUN
ajst-31230	101	52	increases	increase	VERB
ajst-31230	101	53	by	by	ADP
ajst-31230	101	54	only	only	ADV
ajst-31230	101	55	4.8	4.8	NUM
ajst-31230	101	56	%	%	NOUN
ajst-31230	101	57	,	,	PUNCT
ajst-31230	101	58	which	which	PRON
ajst-31230	101	59	experimentally	experimentally	ADV
ajst-31230	101	60	proves	prove	VERB
ajst-31230	101	61	the	the	DET
ajst-31230	101	62	feasibility	feasibility	NOUN
ajst-31230	101	63	of	of	ADP
ajst-31230	101	64	the	the	DET
ajst-31230	101	65	method	method	NOUN
ajst-31230	101	66	of	of	ADP
ajst-31230	101	67	this	this	DET
ajst-31230	101	68	paper	paper	NOUN
ajst-31230	101	69	.	.	PUNCT
ajst-31230	102	1	3.5	3.5	NUM
ajst-31230	102	2	.	.	PUNCT
ajst-31230	103	1	comparative	comparative	ADJ
ajst-31230	103	2	tests	test	NOUN
ajst-31230	103	3	in	in	ADP
ajst-31230	103	4	order	order	NOUN
ajst-31230	103	5	to	to	PART
ajst-31230	103	6	verify	verify	VERB
ajst-31230	103	7	the	the	DET
ajst-31230	103	8	superiority	superiority	NOUN
ajst-31230	103	9	of	of	ADP
ajst-31230	103	10	the	the	DET
ajst-31230	103	11	proposed	propose	VERB
ajst-31230	103	12	method	method	NOUN
ajst-31230	103	13	,	,	PUNCT
ajst-31230	103	14	a	a	DET
ajst-31230	103	15	comparative	comparative	ADJ
ajst-31230	103	16	analysis	analysis	NOUN
ajst-31230	103	17	of	of	ADP
ajst-31230	103	18	the	the	DET
ajst-31230	103	19	machine	machine	NOUN
ajst-31230	103	20	anomaly	anomaly	NOUN
ajst-31230	103	21	detection	detection	NOUN
ajst-31230	103	22	performance	performance	NOUN
ajst-31230	103	23	is	be	AUX
ajst-31230	103	24	carried	carry	VERB
ajst-31230	103	25	out	out	ADP
ajst-31230	103	26	based	base	VERB
ajst-31230	103	27	on	on	ADP
ajst-31230	103	28	the	the	DET
ajst-31230	103	29	wind	wind	NOUN
ajst-31230	103	30	turbine	turbine	NOUN
ajst-31230	103	31	acoustic	acoustic	ADJ
ajst-31230	103	32	dataset	dataset	NOUN
ajst-31230	103	33	from	from	ADP
ajst-31230	103	34	the	the	DET
ajst-31230	103	35	danish	danish	ADJ
ajst-31230	103	36	university	university	PROPN
ajst-31230	103	37	of	of	ADP
ajst-31230	103	38	science	science	NOUN
ajst-31230	103	39	and	and	CCONJ
ajst-31230	103	40	technology	technology	NOUN
ajst-31230	103	41	,	,	PUNCT
ajst-31230	103	42	comparing	compare	VERB
ajst-31230	103	43	the	the	DET
ajst-31230	103	44	method	method	NOUN
ajst-31230	103	45	in	in	ADP
ajst-31230	103	46	this	this	DET
ajst-31230	103	47	paper	paper	NOUN
ajst-31230	103	48	with	with	ADP
ajst-31230	103	49	other	other	ADJ
ajst-31230	103	50	mainstream	mainstream	NOUN
ajst-31230	103	51	methods	method	NOUN
ajst-31230	103	52	.	.	PUNCT
ajst-31230	104	1	the	the	DET
ajst-31230	104	2	comparison	comparison	NOUN
ajst-31230	104	3	results	result	NOUN
ajst-31230	104	4	are	be	AUX
ajst-31230	104	5	shown	show	VERB
ajst-31230	104	6	in	in	ADP
ajst-31230	104	7	table	table	NOUN
ajst-31230	104	8	2	2	NUM
ajst-31230	104	9	.	.	PUNCT
ajst-31230	104	10	table	table	NOUN
ajst-31230	104	11	2	2	NUM
ajst-31230	104	12	.	.	PUNCT
ajst-31230	104	13	model	model	NOUN
ajst-31230	104	14	comparison	comparison	NOUN
ajst-31230	104	15	experiments	experiment	NOUN
ajst-31230	104	16	mould	mould	AUX
ajst-31230	104	17	auc	auc	VERB
ajst-31230	104	18	pauc	pauc	ADJ
ajst-31230	104	19	params	param	NOUN
ajst-31230	104	20	(	(	PUNCT
ajst-31230	104	21	m	m	NOUN
ajst-31230	104	22	)	)	PUNCT
ajst-31230	104	23	flops	flop	NOUN
ajst-31230	104	24	(	(	PUNCT
ajst-31230	104	25	g	g	NOUN
ajst-31230	104	26	)	)	PUNCT
ajst-31230	104	27	training	training	NOUN
ajst-31230	104	28	time	time	NOUN
ajst-31230	104	29	(	(	PUNCT
ajst-31230	104	30	min	min	NOUN
ajst-31230	104	31	)	)	PUNCT
ajst-31230	104	32	marginal	marginal	ADJ
ajst-31230	104	33	reasoning	reasoning	NOUN
ajst-31230	104	34	(	(	PUNCT
ajst-31230	104	35	ms	ms	PROPN
ajst-31230	104	36	)	)	PUNCT
ajst-31230	104	37	mel	mel	PROPN
ajst-31230	104	38	-	-	PROPN
ajst-31230	104	39	cnn	cnn	PROPN
ajst-31230	104	40	89.31	89.31	NUM
ajst-31230	104	41	83.52	83.52	NUM
ajst-31230	104	42	1.80	1.80	NUM
ajst-31230	104	43	0.150	0.150	NUM
ajst-31230	104	44	142	142	NUM
ajst-31230	104	45	382	382	NUM
ajst-31230	104	46	mobilenetv2	mobilenetv2	NOUN
ajst-31230	104	47	88.75	88.75	NUM
ajst-31230	104	48	81.23	81.23	NUM
ajst-31230	104	49	3.40	3.40	NUM
ajst-31230	104	50	0.290	0.290	NUM
ajst-31230	104	51	198	198	NUM
ajst-31230	104	52	415	415	NUM
ajst-31230	104	53	mobilenetv3	mobilenetv3	NOUN
ajst-31230	104	54	91.16	91.16	NUM
ajst-31230	104	55	86.12	86.12	NUM
ajst-31230	104	56	2.10	2.10	NUM
ajst-31230	104	57	0.190	0.190	NUM
ajst-31230	104	58	156	156	NUM
ajst-31230	104	59	388	388	NUM
ajst-31230	104	60	resnet-18	resnet-18	PROPN
ajst-31230	104	61	92.58	92.58	NUM
ajst-31230	104	62	87.94	87.94	NUM
ajst-31230	104	63	11.70	11.70	NUM
ajst-31230	104	64	2.600	2.600	NUM
ajst-31230	104	65	426	426	NUM
ajst-31230	104	66	972	972	NUM
ajst-31230	104	67	autoencoder	autoencoder	NOUN
ajst-31230	104	68	85.61	85.61	NUM
ajst-31230	104	69	76.88	76.88	NUM
ajst-31230	104	70	12.10	12.10	NUM
ajst-31230	104	71	6.420	6.420	NUM
ajst-31230	104	72	598	598	NUM
ajst-31230	104	73	isolation	isolation	NOUN
ajst-31230	104	74	forest	forest	NOUN
ajst-31230	104	75	78.40	78.40	NUM
ajst-31230	104	76	70.34	70.34	NUM
ajst-31230	104	77	ds	ds	PROPN
ajst-31230	104	78	-	-	PUNCT
ajst-31230	104	79	mobilenetv3	mobilenetv3	NOUN
ajst-31230	104	80	94.71	94.71	NUM
ajst-31230	104	81	92.26	92.26	NUM
ajst-31230	104	82	2.38	2.38	NUM
ajst-31230	104	83	0.210	0.210	NUM
ajst-31230	104	84	168	168	NUM
ajst-31230	104	85	382	382	NUM
ajst-31230	104	86	as	as	SCONJ
ajst-31230	104	87	shown	show	VERB
ajst-31230	104	88	in	in	ADP
ajst-31230	104	89	table	table	NOUN
ajst-31230	104	90	2	2	NUM
ajst-31230	104	91	,	,	PUNCT
ajst-31230	104	92	this	this	DET
ajst-31230	104	93	paper	paper	NOUN
ajst-31230	104	94	's	's	PART
ajst-31230	104	95	method	method	NOUN
ajst-31230	104	96	outperforms	outperform	VERB
ajst-31230	104	97	the	the	DET
ajst-31230	104	98	comparison	comparison	NOUN
ajst-31230	104	99	model	model	NOUN
ajst-31230	104	100	in	in	ADP
ajst-31230	104	101	both	both	DET
ajst-31230	104	102	core	core	ADJ
ajst-31230	104	103	indexes	index	NOUN
ajst-31230	104	104	of	of	ADP
ajst-31230	104	105	auc	auc	NOUN
ajst-31230	104	106	and	and	CCONJ
ajst-31230	104	107	pauc	pauc	NOUN
ajst-31230	104	108	,	,	PUNCT
ajst-31230	104	109	and	and	CCONJ
ajst-31230	104	110	the	the	DET
ajst-31230	104	111	number	number	NOUN
ajst-31230	104	112	of	of	ADP
ajst-31230	104	113	parameters	parameter	NOUN
ajst-31230	104	114	is	be	AUX
ajst-31230	104	115	62.3	62.3	NUM
ajst-31230	104	116	%	%	NOUN
ajst-31230	104	117	less	less	ADJ
ajst-31230	104	118	than	than	ADP
ajst-31230	104	119	that	that	PRON
ajst-31230	104	120	of	of	ADP
ajst-31230	104	121	resnet-18	resnet-18	PROPN
ajst-31230	104	122	,	,	PUNCT
ajst-31230	104	123	and	and	CCONJ
ajst-31230	104	124	the	the	DET
ajst-31230	104	125	computation	computation	NOUN
ajst-31230	104	126	amount	amount	NOUN
ajst-31230	104	127	is	be	AUX
ajst-31230	104	128	reduced	reduce	VERB
ajst-31230	104	129	by	by	ADP
ajst-31230	104	130	0.03	0.03	NUM
ajst-31230	104	131	g	g	NOUN
ajst-31230	104	132	,	,	PUNCT
ajst-31230	104	133	which	which	PRON
ajst-31230	104	134	verifies	verify	VERB
ajst-31230	104	135	the	the	DET
ajst-31230	104	136	superiority	superiority	NOUN
ajst-31230	104	137	of	of	ADP
ajst-31230	104	138	the	the	DET
ajst-31230	104	139	model	model	NOUN
ajst-31230	104	140	.	.	PUNCT
ajst-31230	105	1	the	the	DET
ajst-31230	105	2	enhancement	enhancement	NOUN
ajst-31230	105	3	of	of	ADP
ajst-31230	105	4	high	high	ADJ
ajst-31230	105	5	-	-	PUNCT
ajst-31230	105	6	frequency	frequency	NOUN
ajst-31230	105	7	transient	transient	NOUN
ajst-31230	105	8	features	feature	NOUN
ajst-31230	105	9	by	by	ADP
ajst-31230	105	10	the	the	DET
ajst-31230	105	11	dfc	dfc	PROPN
ajst-31230	105	12	module	module	NOUN
ajst-31230	105	13	and	and	CCONJ
ajst-31230	105	14	softpool	softpool	NOUN
ajst-31230	105	15	is	be	AUX
ajst-31230	105	16	demonstrated	demonstrate	VERB
ajst-31230	105	17	.	.	PUNCT
ajst-31230	106	1	4	4	X
ajst-31230	106	2	.	.	X
ajst-31230	106	3	conclusions	conclusion	NOUN
ajst-31230	106	4	in	in	ADP
ajst-31230	106	5	this	this	DET
ajst-31230	106	6	paper	paper	NOUN
ajst-31230	106	7	,	,	PUNCT
ajst-31230	106	8	we	we	PRON
ajst-31230	106	9	propose	propose	VERB
ajst-31230	106	10	a	a	DET
ajst-31230	106	11	lightweight	lightweight	ADJ
ajst-31230	106	12	network	network	NOUN
ajst-31230	106	13	for	for	ADP
ajst-31230	106	14	abnormal	abnormal	ADJ
ajst-31230	106	15	sound	sound	NOUN
ajst-31230	106	16	detection	detection	NOUN
ajst-31230	106	17	in	in	ADP
ajst-31230	106	18	wind	wind	NOUN
ajst-31230	106	19	turbines	turbine	NOUN
ajst-31230	106	20	by	by	ADP
ajst-31230	106	21	incorporating	incorporate	VERB
ajst-31230	106	22	the	the	DET
ajst-31230	106	23	dynamic	dynamic	ADJ
ajst-31230	106	24	frequency	frequency	NOUN
ajst-31230	106	25	convolution	convolution	NOUN
ajst-31230	106	26	module	module	NOUN
ajst-31230	106	27	and	and	CCONJ
ajst-31230	106	28	optimizing	optimize	VERB
ajst-31230	106	29	the	the	DET
ajst-31230	106	30	pooling	pooling	NOUN
ajst-31230	106	31	layer	layer	NOUN
ajst-31230	106	32	with	with	ADP
ajst-31230	106	33	softpool	softpool	NOUN
ajst-31230	106	34	in	in	ADP
ajst-31230	106	35	mobilenetv3	mobilenetv3	PROPN
ajst-31230	106	36	.	.	PUNCT
ajst-31230	107	1	the	the	DET
ajst-31230	107	2	dfc	dfc	PROPN
ajst-31230	107	3	module	module	NOUN
ajst-31230	107	4	innovatively	innovatively	ADV
ajst-31230	107	5	adopts	adopt	VERB
ajst-31230	107	6	the	the	DET
ajst-31230	107	7	frequency	frequency	NOUN
ajst-31230	107	8	band	band	NOUN
ajst-31230	107	9	adaptive	adaptive	ADJ
ajst-31230	107	10	mechanism	mechanism	NOUN
ajst-31230	107	11	,	,	PUNCT
ajst-31230	107	12	enhances	enhance	VERB
ajst-31230	107	13	the	the	DET
ajst-31230	107	14	ability	ability	NOUN
ajst-31230	107	15	of	of	ADP
ajst-31230	107	16	high	high	ADJ
ajst-31230	107	17	-	-	PUNCT
ajst-31230	107	18	frequency	frequency	NOUN
ajst-31230	107	19	transient	transient	NOUN
ajst-31230	107	20	feature	feature	NOUN
ajst-31230	107	21	extraction	extraction	NOUN
ajst-31230	107	22	with	with	ADP
ajst-31230	107	23	a	a	DET
ajst-31230	107	24	learnable	learnable	ADJ
ajst-31230	107	25	band	band	NOUN
ajst-31230	107	26	-	-	PUNCT
ajst-31230	107	27	pass	pass	NOUN
ajst-31230	107	28	filter	filter	NOUN
ajst-31230	107	29	,	,	PUNCT
ajst-31230	107	30	and	and	CCONJ
ajst-31230	107	31	softpool	softpool	NOUN
ajst-31230	107	32	significantly	significantly	ADV
ajst-31230	107	33	reduces	reduce	VERB
ajst-31230	107	34	the	the	DET
ajst-31230	107	35	loss	loss	NOUN
ajst-31230	107	36	of	of	ADP
ajst-31230	107	37	high	high	ADJ
ajst-31230	107	38	-	-	PUNCT
ajst-31230	107	39	frequency	frequency	NOUN
ajst-31230	107	40	details	detail	NOUN
ajst-31230	107	41	.	.	PUNCT
ajst-31230	108	1	the	the	DET
ajst-31230	108	2	experiments	experiment	NOUN
ajst-31230	108	3	are	be	AUX
ajst-31230	108	4	validated	validate	VERB
ajst-31230	108	5	based	base	VERB
ajst-31230	108	6	on	on	ADP
ajst-31230	108	7	the	the	DET
ajst-31230	108	8	acoustic	acoustic	ADJ
ajst-31230	108	9	dataset	dataset	NOUN
ajst-31230	108	10	of	of	ADP
ajst-31230	108	11	danish	danish	PROPN
ajst-31230	108	12	university	university	PROPN
ajst-31230	108	13	of	of	ADP
ajst-31230	108	14	science	science	NOUN
ajst-31230	108	15	and	and	CCONJ
ajst-31230	108	16	technology	technology	NOUN
ajst-31230	108	17	,	,	PUNCT
ajst-31230	108	18	and	and	CCONJ
ajst-31230	108	19	the	the	DET
ajst-31230	108	20	improved	improved	ADJ
ajst-31230	108	21	model	model	NOUN
ajst-31230	108	22	improves	improve	VERB
ajst-31230	108	23	5.57	5.57	NUM
ajst-31230	108	24	%	%	NOUN
ajst-31230	108	25	in	in	ADP
ajst-31230	108	26	average	average	ADJ
ajst-31230	108	27	auc	auc	NOUN
ajst-31230	108	28	over	over	ADP
ajst-31230	108	29	the	the	DET
ajst-31230	108	30	original	original	ADJ
ajst-31230	108	31	mobilenetv3	mobilenetv3	NOUN
ajst-31230	108	32	,	,	PUNCT
ajst-31230	108	33	with	with	ADP
ajst-31230	108	34	only	only	ADV
ajst-31230	108	35	4.8	4.8	NUM
ajst-31230	108	36	%	%	NOUN
ajst-31230	108	37	increase	increase	NOUN
ajst-31230	108	38	in	in	ADP
ajst-31230	108	39	the	the	DET
ajst-31230	108	40	number	number	NOUN
ajst-31230	108	41	of	of	ADP
ajst-31230	108	42	parameters	parameter	NOUN
ajst-31230	108	43	.	.	PUNCT
ajst-31230	109	1	the	the	DET
ajst-31230	109	2	ablation	ablation	NOUN
ajst-31230	109	3	experiments	experiment	NOUN
ajst-31230	109	4	show	show	VERB
ajst-31230	109	5	that	that	SCONJ
ajst-31230	109	6	the	the	DET
ajst-31230	109	7	incorporation	incorporation	NOUN
ajst-31230	109	8	of	of	ADP
ajst-31230	109	9	dfc	dfc	NOUN
ajst-31230	109	10	module	module	NOUN
ajst-31230	109	11	and	and	CCONJ
ajst-31230	109	12	softpool	softpool	NOUN
ajst-31230	109	13	contributes	contribute	VERB
ajst-31230	109	14	significantly	significantly	ADV
ajst-31230	109	15	to	to	PART
ajst-31230	109	16	anomaly	anomaly	NOUN
ajst-31230	109	17	detection	detection	NOUN
ajst-31230	109	18	,	,	PUNCT
ajst-31230	109	19	and	and	CCONJ
ajst-31230	109	20	the	the	DET
ajst-31230	109	21	feature	feature	NOUN
ajst-31230	109	22	fusion	fusion	NOUN
ajst-31230	109	23	splicing	splicing	NOUN
ajst-31230	109	24	strategy	strategy	NOUN
ajst-31230	109	25	balances	balance	NOUN
ajst-31230	109	26	efficiency	efficiency	NOUN
ajst-31230	109	27	and	and	CCONJ
ajst-31230	109	28	accuracy	accuracy	NOUN
ajst-31230	109	29	.	.	PUNCT
ajst-31230	110	1	it	it	PRON
ajst-31230	110	2	provides	provide	VERB
ajst-31230	110	3	an	an	DET
ajst-31230	110	4	efficient	efficient	ADJ
ajst-31230	110	5	and	and	CCONJ
ajst-31230	110	6	low	low	ADJ
ajst-31230	110	7	-	-	PUNCT
ajst-31230	110	8	cost	cost	NOUN
ajst-31230	110	9	solution	solution	NOUN
ajst-31230	110	10	for	for	ADP
ajst-31230	110	11	wind	wind	NOUN
ajst-31230	110	12	farm	farm	NOUN
ajst-31230	110	13	operation	operation	NOUN
ajst-31230	110	14	and	and	CCONJ
ajst-31230	110	15	maintenance	maintenance	NOUN
ajst-31230	110	16	.	.	PUNCT
ajst-31230	111	1	references	reference	NOUN
ajst-31230	111	2	[	[	X
ajst-31230	111	3	1	1	X
ajst-31230	111	4	]	]	X
ajst-31230	111	5	wang	wang	PROPN
ajst-31230	111	6	m	m	PROPN
ajst-31230	111	7	,	,	PUNCT
ajst-31230	111	8	mei	mei	PROPN
ajst-31230	111	9	q	q	X
ajst-31230	111	10	,	,	PUNCT
ajst-31230	111	11	song	song	NOUN
ajst-31230	111	12	x	x	X
ajst-31230	111	13	,	,	PUNCT
ajst-31230	111	14	et	et	NOUN
ajst-31230	111	15	al.a	al.a	NOUN
ajst-31230	111	16	machine	machine	NOUN
ajst-31230	111	17	anomalous	anomalous	ADJ
ajst-31230	111	18	sound	sound	NOUN
ajst-31230	111	19	detection	detection	NOUN
ajst-31230	111	20	method	method	NOUN
ajst-31230	111	21	using	use	VERB
ajst-31230	111	22	the	the	DET
ajst-31230	111	23	lms	lm	NOUN
ajst-31230	111	24	spectrogram	spectrogram	NOUN
ajst-31230	111	25	and	and	CCONJ
ajst-31230	111	26	esmobilenetv3	esmobilenetv3	NOUN
ajst-31230	111	27	network[j].applied	network[j].applie	VERB
ajst-31230	111	28	sciences,2023,13(23	sciences,2023,13(23	NOUN
ajst-31230	111	29	):	):	PUNCT
ajst-31230	111	30	[	[	X
ajst-31230	111	31	2	2	NUM
ajst-31230	111	32	]	]	X
ajst-31230	111	33	shipeng	shipeng	NOUN
ajst-31230	111	34	h	h	PROPN
ajst-31230	111	35	,	,	PUNCT
ajst-31230	111	36	yihang	yihang	PROPN
ajst-31230	111	37	c	c	PROPN
ajst-31230	111	38	,	,	PUNCT
ajst-31230	111	39	zhifang	zhifang	PROPN
ajst-31230	111	40	w	w	PROPN
ajst-31230	111	41	,	,	PUNCT
ajst-31230	111	42	et	et	NOUN
ajst-31230	111	43	al.deep	al.deep	PUNCT
ajst-31230	111	44	learning	learn	VERB
ajst-31230	111	45	bird	bird	NOUN
ajst-31230	111	46	song	song	NOUN
ajst-31230	111	47	recognition	recognition	NOUN
ajst-31230	111	48	based	base	VERB
ajst-31230	111	49	on	on	ADP
ajst-31230	111	50	mff	mff	NOUN
ajst-31230	111	51	-	-	PUNCT
ajst-31230	111	52	scsenet	scsenet	NOUN
ajst-31230	112	1	[	[	X
ajst-31230	112	2	j	j	X
ajst-31230	112	3	]	]	X
ajst-31230	112	4	.	.	PUNCT
ajst-31230	113	1	ecological	ecological	ADJ
ajst-31230	113	2	indicators	indicator	NOUN
ajst-31230	113	3	,	,	PUNCT
ajst-31230	113	4	2023,154	2023,154	NUM
ajst-31230	113	5	[	[	X
ajst-31230	113	6	3	3	X
ajst-31230	113	7	]	]	X
ajst-31230	113	8	yixing	yixe	VERB
ajst-31230	113	9	f	f	PROPN
ajst-31230	113	10	,	,	PUNCT
ajst-31230	113	11	chunjiang	chunjiang	PROPN
ajst-31230	113	12	y	y	PROPN
ajst-31230	113	13	,	,	PUNCT
ajst-31230	113	14	yan	yan	PROPN
ajst-31230	113	15	z	z	PROPN
ajst-31230	113	16	,	,	PUNCT
ajst-31230	113	17	et	et	PROPN
ajst-31230	113	18	al.classification	al.classification	NOUN
ajst-31230	113	19	of	of	ADP
ajst-31230	113	20	birdsong	birdsong	ADJ
ajst-31230	113	21	spectrograms	spectrogram	NOUN
ajst-31230	113	22	based	base	VERB
ajst-31230	113	23	on	on	ADP
ajst-31230	113	24	dr	dr	PROPN
ajst-31230	113	25	-	-	PUNCT
ajst-31230	113	26	acgan	acgan	ADJ
ajst-31230	113	27	and	and	CCONJ
ajst-31230	113	28	dynamic	dynamic	ADJ
ajst-31230	113	29	convolution	convolution	NOUN
ajst-31230	113	30	[	[	X
ajst-31230	113	31	j	j	X
ajst-31230	113	32	]	]	X
ajst-31230	113	33	.	.	PUNCT
ajst-31230	114	1	ecological	ecological	ADJ
ajst-31230	114	2	informatics,2023,77	informatics,2023,77	NOUN
ajst-31230	115	1	[	[	X
ajst-31230	115	2	4	4	NUM
ajst-31230	115	3	]	]	X
ajst-31230	115	4	liu	liu	PROPN
ajst-31230	115	5	h	h	PROPN
ajst-31230	115	6	,	,	PUNCT
ajst-31230	115	7	wang	wang	PROPN
ajst-31230	115	8	h	h	PROPN
ajst-31230	115	9	.real	.real	ADJ
ajst-31230	115	10	-	-	PUNCT
ajst-31230	115	11	time	time	NOUN
ajst-31230	115	12	anomaly	anomaly	NOUN
ajst-31230	115	13	detection	detection	NOUN
ajst-31230	115	14	of	of	ADP
ajst-31230	115	15	network	network	NOUN
ajst-31230	115	16	traffic	traffic	NOUN
ajst-31230	115	17	based	base	VERB
ajst-31230	115	18	on	on	ADP
ajst-31230	115	19	cnn[j].symmetry,2023,15(6	cnn[j].symmetry,2023,15(6	NOUN
ajst-31230	115	20	):	):	PUNCT
ajst-31230	115	21	[	[	X
ajst-31230	115	22	5	5	X
ajst-31230	115	23	]	]	X
ajst-31230	115	24	yida	yida	PROPN
ajst-31230	115	25	w	w	PROPN
ajst-31230	115	26	,	,	PUNCT
ajst-31230	115	27	joseph	joseph	PROPN
ajst-31230	115	28	d	d	PROPN
ajst-31230	115	29	t	t	PROPN
ajst-31230	115	30	,	,	PUNCT
ajst-31230	115	31	nassir	nassir	NOUN
ajst-31230	115	32	n	n	PROPN
ajst-31230	115	33	,	,	PUNCT
ajst-31230	115	34	et	et	NOUN
ajst-31230	115	35	al.softpool++	al.softpool++	PROPN
ajst-31230	115	36	:	:	PUNCT
ajst-31230	115	37	an	an	DET
ajst-31230	115	38	encoder	encoder	NOUN
ajst-31230	115	39	–	–	PUNCT
ajst-31230	115	40	decoder	decoder	NOUN
ajst-31230	115	41	network	network	NOUN
ajst-31230	115	42	for	for	ADP
ajst-31230	115	43	point	point	NOUN
ajst-31230	115	44	cloud	cloud	ADJ
ajst-31230	115	45	completion[j].international	completion[j].international	ADJ
ajst-31230	115	46	journal	journal	NOUN
ajst-31230	115	47	of	of	ADP
ajst-31230	115	48	computer	computer	NOUN
ajst-31230	115	49	vision,2022,130(5):1145	vision,2022,130(5):1145	PROPN
ajst-31230	115	50	-	-	PUNCT
ajst-31230	115	51	1164	1164	NUM
ajst-31230	115	52	.	.	PUNCT
ajst-31230	116	1	[	[	X
ajst-31230	116	2	6	6	NUM
ajst-31230	116	3	]	]	X
ajst-31230	116	4	chunyuan	chunyuan	PROPN
ajst-31230	116	5	w	w	PROPN
ajst-31230	116	6	,	,	PUNCT
ajst-31230	116	7	yang	yang	PROPN
ajst-31230	116	8	w	w	PROPN
ajst-31230	116	9	,	,	PUNCT
ajst-31230	116	10	yihan	yihan	INTJ
ajst-31230	116	11	w	w	PROPN
ajst-31230	116	12	,	,	PUNCT
ajst-31230	116	13	et	et	NOUN
ajst-31230	116	14	al.scene	al.scene	NOUN
ajst-31230	116	15	recognition	recognition	NOUN
ajst-31230	116	16	using	use	VERB
ajst-31230	116	17	deep	deep	ADJ
ajst-31230	116	18	softpool	softpool	NOUN
ajst-31230	116	19	capsule	capsule	NOUN
ajst-31230	116	20	network	network	NOUN
ajst-31230	116	21	based	base	VERB
ajst-31230	116	22	on	on	ADP
ajst-31230	116	23	residual	residual	ADJ
ajst-31230	116	24	diverse	diverse	ADJ
ajst-31230	116	25	branch	branch	NOUN
ajst-31230	116	26	block[j].sensors,2021,21(16):5575	block[j].sensors,2021,21(16):5575	NOUN
ajst-31230	116	27	-	-	PUNCT
ajst-31230	116	28	5575	5575	NUM
ajst-31230	116	29	.	.	PUNCT
ajst-31230	117	1	[	[	X
ajst-31230	117	2	7	7	X
ajst-31230	117	3	]	]	X
ajst-31230	117	4	renström	renström	ADJ
ajst-31230	117	5	n	n	PROPN
ajst-31230	117	6	,	,	PUNCT
ajst-31230	117	7	bangalore	bangalore	PROPN
ajst-31230	117	8	p	p	NOUN
ajst-31230	117	9	,	,	PUNCT
ajst-31230	117	10	highcock	highcock	NOUN
ajst-31230	117	11	e	e	NOUN
ajst-31230	117	12	.system	.system	ADV
ajst-31230	117	13	-	-	PUNCT
ajst-31230	117	14	wide	wide	ADJ
ajst-31230	117	15	anomaly	anomaly	NOUN
ajst-31230	117	16	detection	detection	NOUN
ajst-31230	117	17	in	in	ADP
ajst-31230	117	18	wind	wind	NOUN
ajst-31230	117	19	turbines	turbine	NOUN
ajst-31230	117	20	using	use	VERB
ajst-31230	117	21	deep	deep	ADJ
ajst-31230	117	22	autoencoders	autoencoder	NOUN
ajst-31230	117	23	[	[	X
ajst-31230	117	24	j	j	X
ajst-31230	117	25	]	]	X
ajst-31230	117	26	.	.	PUNCT
ajst-31230	118	1	renewable	renewable	ADJ
ajst-31230	118	2	energy	energy	NOUN
ajst-31230	118	3	,	,	PUNCT
ajst-31230	118	4	2020,157(prepublish):647	2020,157(prepublish):647	NOUN
ajst-31230	118	5	-	-	PUNCT
ajst-31230	118	6	659	659	NUM
ajst-31230	118	7	.	.	PUNCT
ajst-31230	119	1	[	[	X
ajst-31230	119	2	8	8	NUM
ajst-31230	119	3	]	]	X
ajst-31230	119	4	feng	feng	PROPN
ajst-31230	119	5	z	z	PROPN
ajst-31230	119	6	,	,	PUNCT
ajst-31230	119	7	zhu	zhu	PROPN
ajst-31230	119	8	w	w	PROPN
ajst-31230	119	9	,	,	PUNCT
ajst-31230	119	10	zhang	zhang	PROPN
ajst-31230	119	11	d	d	PROPN
ajst-31230	119	12	.time	.time	ADJ
ajst-31230	119	13	-	-	ADJ
ajst-31230	119	14	frequency	frequency	NOUN
ajst-31230	119	15	demodulation	demodulation	NOUN
ajst-31230	119	16	analysis	analysis	NOUN
ajst-31230	119	17	via	via	ADP
ajst-31230	119	18	vold	vold	ADJ
ajst-31230	119	19	-	-	PUNCT
ajst-31230	119	20	kalman	kalman	NOUN
ajst-31230	119	21	filter	filter	NOUN
ajst-31230	119	22	for	for	ADP
ajst-31230	119	23	wind	wind	NOUN
ajst-31230	119	24	turbine	turbine	NOUN
ajst-31230	119	25	planetary	planetary	ADJ
ajst-31230	119	26	gearbox	gearbox	NOUN
ajst-31230	119	27	fault	fault	NOUN
ajst-31230	119	28	diagnosis	diagnosis	NOUN
ajst-31230	119	29	under	under	ADP
ajst-31230	119	30	nonstationary	nonstationary	ADJ
ajst-31230	119	31	speeds	speed	NOUN
ajst-31230	119	32	[	[	PUNCT
ajst-31230	119	33	j].mechanical	j].mechanical	ADJ
ajst-31230	119	34	systems	system	NOUN
ajst-31230	119	35	and	and	CCONJ
ajst-31230	119	36	signal	signal	NOUN
ajst-31230	119	37	processing	processing	NOUN
ajst-31230	119	38	,	,	PUNCT
ajst-31230	119	39	2019	2019	NUM
ajst-31230	119	40	,	,	PUNCT
ajst-31230	119	41	12893109	12893109	NUM
ajst-31230	119	42	.	.	PUNCT
ajst-31230	120	1	130	130	NUM
ajst-31230	121	1	[	[	SYM
ajst-31230	121	2	9	9	NUM
ajst-31230	121	3	]	]	X
ajst-31230	121	4	meng	meng	PROPN
ajst-31230	121	5	h	h	PROPN
ajst-31230	121	6	,	,	PUNCT
ajst-31230	121	7	yan	yan	PROPN
ajst-31230	121	8	t	t	PROPN
ajst-31230	121	9	,	,	PUNCT
ajst-31230	121	10	yuan	yuan	PROPN
ajst-31230	121	11	f	f	PROPN
ajst-31230	121	12	,	,	PUNCT
ajst-31230	121	13	et	et	PROPN
ajst-31230	121	14	al.speech	al.speech	PUNCT
ajst-31230	121	15	emotion	emotion	NOUN
ajst-31230	121	16	recognition	recognition	NOUN
ajst-31230	121	17	from	from	ADP
ajst-31230	121	18	3d	3d	NUM
ajst-31230	121	19	log	log	PROPN
ajst-31230	121	20	-	-	PUNCT
ajst-31230	121	21	mel	mel	PROPN
ajst-31230	121	22	spectrograms	spectrogram	NOUN
ajst-31230	121	23	with	with	ADP
ajst-31230	121	24	deep	deep	ADJ
ajst-31230	121	25	learning	learn	VERB
ajst-31230	121	26	network.[j].ieee	network.[j].ieee	NOUN
ajst-31230	121	27	access,2019,7125868	access,2019,7125868	NOUN
ajst-31230	121	28	-	-	PUNCT
ajst-31230	121	29	125881	125881	NUM
ajst-31230	121	30	.	.	PUNCT
ajst-31230	122	1	[	[	X
ajst-31230	122	2	10	10	NUM
ajst-31230	122	3	]	]	X
ajst-31230	122	4	emre	emre	PROPN
ajst-31230	122	5	b	b	PROPN
ajst-31230	122	6	,	,	PUNCT
ajst-31230	122	7	jun	jun	PROPN
ajst-31230	122	8	w	w	PROPN
ajst-31230	122	9	z	z	PROPN
ajst-31230	122	10	,	,	PUNCT
ajst-31230	122	11	zhong	zhong	PROPN
ajst-31230	122	12	w	w	PROPN
ajst-31230	122	13	s	s	PROPN
ajst-31230	122	14	,	,	PUNCT
ajst-31230	122	15	et	et	NOUN
ajst-31230	122	16	al.consistent	al.consistent	NOUN
ajst-31230	122	17	modelling	modelling	NOUN
ajst-31230	122	18	of	of	ADP
ajst-31230	122	19	wind	wind	NOUN
ajst-31230	122	20	turbine	turbine	NOUN
ajst-31230	122	21	noise	noise	NOUN
ajst-31230	122	22	propagation	propagation	NOUN
ajst-31230	122	23	from	from	ADP
ajst-31230	122	24	source	source	NOUN
ajst-31230	122	25	to	to	ADP
ajst-31230	122	26	receiver.[j].the	receiver.[j].the	DET
ajst-31230	122	27	journal	journal	NOUN
ajst-31230	122	28	of	of	ADP
ajst-31230	122	29	the	the	DET
ajst-31230	122	30	acoustical	acoustical	ADJ
ajst-31230	122	31	society	society	NOUN
ajst-31230	122	32	of	of	ADP
ajst-31230	122	33	america	america	PROPN
ajst-31230	122	34	,	,	PUNCT
ajst-31230	122	35	2017	2017	NUM
ajst-31230	122	36	,	,	PUNCT
ajst-31230	122	37	142(5	142(5	NUM
ajst-31230	122	38	):	):	PUNCT
ajst-31230	122	39	3297	3297	NUM
ajst-31230	122	40	.	.	PUNCT