id	sid	tid	token	lemma	pos
fcis-29907	1	1	frontiers	frontier	NOUN
fcis-29907	1	2	in	in	ADP
fcis-29907	1	3	computing	computing	NOUN
fcis-29907	1	4	and	and	CCONJ
fcis-29907	1	5	intelligent	intelligent	ADJ
fcis-29907	1	6	systems	system	NOUN
fcis-29907	1	7	issn	issn	VERB
fcis-29907	1	8	:	:	PUNCT
fcis-29907	1	9	2832	2832	NUM
fcis-29907	1	10	-	-	SYM
fcis-29907	1	11	6024	6024	NUM
fcis-29907	1	12	|	|	NOUN
fcis-29907	1	13	vol	vol	NOUN
fcis-29907	1	14	.	.	PROPN
fcis-29907	2	1	11	11	NUM
fcis-29907	2	2	,	,	PUNCT
fcis-29907	2	3	no	no	INTJ
fcis-29907	2	4	.	.	NOUN
fcis-29907	2	5	2	2	NUM
fcis-29907	2	6	,	,	PUNCT
fcis-29907	2	7	2025	2025	NUM
fcis-29907	2	8	106	106	NUM
fcis-29907	2	9	self‐supervised	self‐supervised	ADJ
fcis-29907	2	10	learning	learning	NOUN
fcis-29907	2	11	for	for	ADP
fcis-29907	2	12	speech‐based	speech‐based	ADJ
fcis-29907	2	13	detection	detection	NOUN
fcis-29907	2	14	of	of	ADP
fcis-29907	2	15	depressive	depressive	ADJ
fcis-29907	2	16	states	state	NOUN
fcis-29907	2	17	xinlin	xinlin	PROPN
fcis-29907	3	1	li	li	PROPN
fcis-29907	3	2	1	1	NUM
fcis-29907	3	3	,	,	PUNCT
fcis-29907	3	4	2	2	NUM
fcis-29907	3	5	,	,	PUNCT
fcis-29907	3	6	changhe	changhe	ADJ
fcis-29907	3	7	fan	fan	NOUN
fcis-29907	3	8	1	1	NUM
fcis-29907	3	9	,	,	PUNCT
fcis-29907	3	10	*	*	PUNCT
fcis-29907	3	11	and	and	CCONJ
fcis-29907	3	12	chengyue	chengyue	PROPN
fcis-29907	3	13	su	su	PROPN
fcis-29907	3	14	2	2	NUM
fcis-29907	3	15	1	1	NUM
fcis-29907	3	16	department	department	NOUN
fcis-29907	3	17	of	of	ADP
fcis-29907	3	18	psychiatry	psychiatry	NOUN
fcis-29907	3	19	,	,	PUNCT
fcis-29907	3	20	the	the	DET
fcis-29907	3	21	affiliated	affiliated	ADJ
fcis-29907	3	22	guangdong	guangdong	NOUN
fcis-29907	3	23	,	,	PUNCT
fcis-29907	3	24	second	second	ADJ
fcis-29907	3	25	provincial	provincial	ADJ
fcis-29907	3	26	general	general	ADJ
fcis-29907	3	27	hospital	hospital	NOUN
fcis-29907	3	28	of	of	ADP
fcis-29907	3	29	jinan	jinan	PROPN
fcis-29907	3	30	university	university	PROPN
fcis-29907	3	31	,	,	PUNCT
fcis-29907	3	32	guangzhou	guangzhou	PROPN
fcis-29907	3	33	guangdong	guangdong	PROPN
fcis-29907	3	34	,	,	PUNCT
fcis-29907	3	35	510317	510317	NUM
fcis-29907	3	36	,	,	PUNCT
fcis-29907	3	37	china	china	PROPN
fcis-29907	3	38	2	2	NUM
fcis-29907	3	39	school	school	NOUN
fcis-29907	3	40	of	of	ADP
fcis-29907	3	41	physics	physics	NOUN
fcis-29907	3	42	and	and	CCONJ
fcis-29907	3	43	optoelectronic	optoelectronic	ADJ
fcis-29907	3	44	engineering	engineering	NOUN
fcis-29907	3	45	,	,	PUNCT
fcis-29907	3	46	guangdong	guangdong	PROPN
fcis-29907	3	47	university	university	PROPN
fcis-29907	3	48	of	of	ADP
fcis-29907	3	49	technology	technology	PROPN
fcis-29907	3	50	,	,	PUNCT
fcis-29907	3	51	guangzhou	guangzhou	PROPN
fcis-29907	3	52	guangdong	guangdong	PROPN
fcis-29907	3	53	,	,	PUNCT
fcis-29907	3	54	510006	510006	NUM
fcis-29907	3	55	,	,	PUNCT
fcis-29907	3	56	china	china	PROPN
fcis-29907	3	57	*	*	PUNCT
fcis-29907	3	58	corresponding	correspond	VERB
fcis-29907	3	59	author	author	NOUN
fcis-29907	3	60	:	:	PUNCT
fcis-29907	3	61	changhe	changhe	PROPN
fcis-29907	3	62	fan	fan	PROPN
fcis-29907	3	63	abstract	abstract	PROPN
fcis-29907	3	64	:	:	PUNCT
fcis-29907	3	65	this	this	DET
fcis-29907	3	66	study	study	NOUN
fcis-29907	3	67	aims	aim	VERB
fcis-29907	3	68	to	to	PART
fcis-29907	3	69	enhance	enhance	VERB
fcis-29907	3	70	the	the	DET
fcis-29907	3	71	accuracy	accuracy	NOUN
fcis-29907	3	72	of	of	ADP
fcis-29907	3	73	depression	depression	NOUN
fcis-29907	3	74	detection	detection	NOUN
fcis-29907	3	75	by	by	ADP
fcis-29907	3	76	leveraging	leverage	VERB
fcis-29907	3	77	representation	representation	NOUN
fcis-29907	3	78	learning	learn	VERB
fcis-29907	3	79	from	from	ADP
fcis-29907	3	80	audio	audio	ADJ
fcis-29907	3	81	data	datum	NOUN
fcis-29907	3	82	.	.	PUNCT
fcis-29907	4	1	the	the	DET
fcis-29907	4	2	data	datum	NOUN
fcis-29907	4	3	of	of	ADP
fcis-29907	4	4	depression	depression	NOUN
fcis-29907	4	5	speech	speech	NOUN
fcis-29907	4	6	sets	set	NOUN
fcis-29907	4	7	are	be	AUX
fcis-29907	4	8	sparse	sparse	ADJ
fcis-29907	4	9	and	and	CCONJ
fcis-29907	4	10	costly	costly	ADJ
fcis-29907	4	11	to	to	PART
fcis-29907	4	12	annotate	annotate	VERB
fcis-29907	4	13	.	.	PUNCT
fcis-29907	5	1	therefore	therefore	ADV
fcis-29907	5	2	,	,	PUNCT
fcis-29907	5	3	a	a	DET
fcis-29907	5	4	self	self	NOUN
fcis-29907	5	5	-	-	PUNCT
fcis-29907	5	6	supervised	supervise	VERB
fcis-29907	5	7	pre	pre	ADJ
fcis-29907	5	8	-	-	ADJ
fcis-29907	5	9	training	training	ADJ
fcis-29907	5	10	approach	approach	NOUN
fcis-29907	5	11	is	be	AUX
fcis-29907	5	12	employed	employ	VERB
fcis-29907	5	13	to	to	PART
fcis-29907	5	14	improve	improve	VERB
fcis-29907	5	15	the	the	DET
fcis-29907	5	16	performance	performance	NOUN
fcis-29907	5	17	,	,	PUNCT
fcis-29907	5	18	generalization	generalization	NOUN
fcis-29907	5	19	capability	capability	NOUN
fcis-29907	5	20	,	,	PUNCT
fcis-29907	5	21	and	and	CCONJ
fcis-29907	5	22	training	training	NOUN
fcis-29907	5	23	efficiency	efficiency	NOUN
fcis-29907	5	24	of	of	ADP
fcis-29907	5	25	downstream	downstream	ADJ
fcis-29907	5	26	tasks	task	NOUN
fcis-29907	5	27	.	.	PUNCT
fcis-29907	6	1	when	when	SCONJ
fcis-29907	6	2	processing	process	VERB
fcis-29907	6	3	unlabeled	unlabeled	ADJ
fcis-29907	6	4	data	datum	NOUN
fcis-29907	6	5	,	,	PUNCT
fcis-29907	6	6	the	the	DET
fcis-29907	6	7	pre	pre	ADJ
fcis-29907	6	8	-	-	ADJ
fcis-29907	6	9	trained	train	VERB
fcis-29907	6	10	audio	audio	ADJ
fcis-29907	6	11	representations	representation	NOUN
fcis-29907	6	12	based	base	VERB
fcis-29907	6	13	on	on	ADP
fcis-29907	6	14	self	self	NOUN
fcis-29907	6	15	-	-	PUNCT
fcis-29907	6	16	supervised	supervise	VERB
fcis-29907	6	17	learning	learning	NOUN
fcis-29907	6	18	may	may	AUX
fcis-29907	6	19	be	be	AUX
fcis-29907	6	20	interfered	interfere	VERB
fcis-29907	6	21	with	with	ADP
fcis-29907	6	22	by	by	ADP
fcis-29907	6	23	noisy	noisy	ADJ
fcis-29907	6	24	data	datum	NOUN
fcis-29907	6	25	if	if	SCONJ
fcis-29907	6	26	there	there	PRON
fcis-29907	6	27	is	be	VERB
fcis-29907	6	28	a	a	DET
fcis-29907	6	29	significant	significant	ADJ
fcis-29907	6	30	amount	amount	NOUN
fcis-29907	6	31	of	of	ADP
fcis-29907	6	32	noise	noise	NOUN
fcis-29907	6	33	or	or	CCONJ
fcis-29907	6	34	errors	error	NOUN
fcis-29907	6	35	present	present	ADJ
fcis-29907	6	36	.	.	PUNCT
fcis-29907	7	1	consequently	consequently	ADV
fcis-29907	7	2	,	,	PUNCT
fcis-29907	7	3	it	it	PRON
fcis-29907	7	4	is	be	AUX
fcis-29907	7	5	necessary	necessary	ADJ
fcis-29907	7	6	to	to	PART
fcis-29907	7	7	effectively	effectively	ADV
fcis-29907	7	8	analyze	analyze	VERB
fcis-29907	7	9	long	long	ADJ
fcis-29907	7	10	-	-	PUNCT
fcis-29907	7	11	distance	distance	NOUN
fcis-29907	7	12	sequence	sequence	NOUN
fcis-29907	7	13	data	datum	NOUN
fcis-29907	7	14	to	to	PART
fcis-29907	7	15	enhance	enhance	VERB
fcis-29907	7	16	anti	anti	ADJ
fcis-29907	7	17	-	-	ADJ
fcis-29907	7	18	interference	interference	ADJ
fcis-29907	7	19	capabilities	capability	NOUN
fcis-29907	7	20	.	.	PUNCT
fcis-29907	8	1	however	however	ADV
fcis-29907	8	2	,	,	PUNCT
fcis-29907	8	3	traditional	traditional	ADJ
fcis-29907	8	4	lstm	lstm	NOUN
fcis-29907	8	5	models	model	NOUN
fcis-29907	8	6	have	have	VERB
fcis-29907	8	7	limitations	limitation	NOUN
fcis-29907	8	8	in	in	ADP
fcis-29907	8	9	context	context	NOUN
fcis-29907	8	10	extraction	extraction	NOUN
fcis-29907	8	11	and	and	CCONJ
fcis-29907	8	12	robustness	robustness	NOUN
fcis-29907	8	13	to	to	ADP
fcis-29907	8	14	input	input	NOUN
fcis-29907	8	15	outliers	outlier	NOUN
fcis-29907	8	16	.	.	PUNCT
fcis-29907	9	1	thus	thus	ADV
fcis-29907	9	2	,	,	PUNCT
fcis-29907	9	3	an	an	DET
fcis-29907	9	4	improved	improved	ADJ
fcis-29907	9	5	method	method	NOUN
fcis-29907	9	6	named	name	VERB
fcis-29907	9	7	cnn	cnn	PROPN
fcis-29907	9	8	-	-	PUNCT
fcis-29907	9	9	bilstm	bilstm	NOUN
fcis-29907	9	10	is	be	AUX
fcis-29907	9	11	proposed	propose	VERB
fcis-29907	9	12	in	in	ADP
fcis-29907	9	13	this	this	DET
fcis-29907	9	14	paper	paper	NOUN
fcis-29907	9	15	.	.	PUNCT
fcis-29907	10	1	the	the	DET
fcis-29907	10	2	network	network	NOUN
fcis-29907	10	3	initializes	initialize	VERB
fcis-29907	10	4	the	the	DET
fcis-29907	10	5	lstm	lstm	NOUN
fcis-29907	10	6	's	's	PART
fcis-29907	10	7	embedding	embed	VERB
fcis-29907	10	8	layer	layer	NOUN
fcis-29907	10	9	with	with	ADP
fcis-29907	10	10	pre	pre	ADJ
fcis-29907	10	11	-	-	ADJ
fcis-29907	10	12	trained	train	VERB
fcis-29907	10	13	word	word	NOUN
fcis-29907	10	14	vectors	vector	NOUN
fcis-29907	10	15	and	and	CCONJ
fcis-29907	10	16	extracts	extract	NOUN
fcis-29907	10	17	spatial	spatial	ADJ
fcis-29907	10	18	and	and	CCONJ
fcis-29907	10	19	temporal	temporal	ADJ
fcis-29907	10	20	features	feature	NOUN
fcis-29907	10	21	separately	separately	ADV
fcis-29907	10	22	to	to	PART
fcis-29907	10	23	ensure	ensure	VERB
fcis-29907	10	24	a	a	DET
fcis-29907	10	25	full	full	ADJ
fcis-29907	10	26	and	and	CCONJ
fcis-29907	10	27	complete	complete	ADJ
fcis-29907	10	28	expression	expression	NOUN
fcis-29907	10	29	of	of	ADP
fcis-29907	10	30	useful	useful	ADJ
fcis-29907	10	31	input	input	NOUN
fcis-29907	10	32	information	information	NOUN
fcis-29907	10	33	.	.	PUNCT
fcis-29907	11	1	different	different	ADJ
fcis-29907	11	2	weights	weight	NOUN
fcis-29907	11	3	are	be	AUX
fcis-29907	11	4	assigned	assign	VERB
fcis-29907	11	5	based	base	VERB
fcis-29907	11	6	on	on	ADP
fcis-29907	11	7	the	the	DET
fcis-29907	11	8	importance	importance	NOUN
fcis-29907	11	9	of	of	ADP
fcis-29907	11	10	the	the	DET
fcis-29907	11	11	features	feature	NOUN
fcis-29907	11	12	to	to	PART
fcis-29907	11	13	obtain	obtain	VERB
fcis-29907	11	14	fused	fused	ADJ
fcis-29907	11	15	features	feature	NOUN
fcis-29907	11	16	.	.	PUNCT
fcis-29907	12	1	additionally	additionally	ADV
fcis-29907	12	2	,	,	PUNCT
fcis-29907	12	3	a	a	DET
fcis-29907	12	4	random	random	ADJ
fcis-29907	12	5	forest	forest	NOUN
fcis-29907	12	6	is	be	AUX
fcis-29907	12	7	used	use	VERB
fcis-29907	12	8	for	for	ADP
fcis-29907	12	9	classification	classification	NOUN
fcis-29907	12	10	to	to	PART
fcis-29907	12	11	mitigate	mitigate	VERB
fcis-29907	12	12	the	the	DET
fcis-29907	12	13	risk	risk	NOUN
fcis-29907	12	14	of	of	ADP
fcis-29907	12	15	overfitting	overfitting	NOUN
fcis-29907	12	16	and	and	CCONJ
fcis-29907	12	17	to	to	PART
fcis-29907	12	18	demonstrate	demonstrate	VERB
fcis-29907	12	19	good	good	ADJ
fcis-29907	12	20	performance	performance	NOUN
fcis-29907	12	21	when	when	SCONJ
fcis-29907	12	22	processing	process	VERB
fcis-29907	12	23	high	high	ADJ
fcis-29907	12	24	-	-	PUNCT
fcis-29907	12	25	dimensional	dimensional	ADJ
fcis-29907	12	26	data	datum	NOUN
fcis-29907	12	27	.	.	PUNCT
fcis-29907	13	1	experimental	experimental	ADJ
fcis-29907	13	2	results	result	NOUN
fcis-29907	13	3	show	show	VERB
fcis-29907	13	4	that	that	SCONJ
fcis-29907	13	5	the	the	DET
fcis-29907	13	6	proposed	propose	VERB
fcis-29907	13	7	model	model	NOUN
fcis-29907	13	8	exhibits	exhibit	VERB
fcis-29907	13	9	good	good	ADJ
fcis-29907	13	10	classification	classification	NOUN
fcis-29907	13	11	performance	performance	NOUN
fcis-29907	13	12	on	on	ADP
fcis-29907	13	13	the	the	DET
fcis-29907	13	14	depression	depression	NOUN
fcis-29907	13	15	dataset	dataset	NOUN
fcis-29907	13	16	,	,	PUNCT
fcis-29907	13	17	outperforming	outperform	VERB
fcis-29907	13	18	traditional	traditional	ADJ
fcis-29907	13	19	methods	method	NOUN
fcis-29907	13	20	and	and	CCONJ
fcis-29907	13	21	state	state	NOUN
fcis-29907	13	22	-	-	PUNCT
fcis-29907	13	23	of	of	ADP
fcis-29907	13	24	-	-	PUNCT
fcis-29907	13	25	the	the	DET
fcis-29907	13	26	-	-	PUNCT
fcis-29907	13	27	art	art	NOUN
fcis-29907	13	28	investigations	investigation	NOUN
fcis-29907	13	29	.	.	PUNCT
fcis-29907	14	1	keywords	keyword	NOUN
fcis-29907	14	2	:	:	PUNCT
fcis-29907	14	3	self	self	NOUN
fcis-29907	14	4	-	-	PUNCT
fcis-29907	14	5	supervised	supervise	VERB
fcis-29907	14	6	pre	pre	ADJ
fcis-29907	14	7	-	-	NOUN
fcis-29907	14	8	training	training	NOUN
fcis-29907	14	9	;	;	PUNCT
fcis-29907	14	10	cnn	cnn	PROPN
fcis-29907	14	11	-	-	PUNCT
fcis-29907	14	12	bilstm	bilstm	NOUN
fcis-29907	14	13	;	;	PUNCT
fcis-29907	14	14	depression	depression	NOUN
fcis-29907	14	15	identification	identification	NOUN
fcis-29907	14	16	;	;	PUNCT
fcis-29907	14	17	speech	speech	NOUN
fcis-29907	14	18	detection	detection	NOUN
fcis-29907	14	19	.	.	PUNCT
fcis-29907	15	1	1	1	X
fcis-29907	15	2	.	.	X
fcis-29907	15	3	introduction	introduction	NOUN
fcis-29907	15	4	due	due	ADP
fcis-29907	15	5	to	to	ADP
fcis-29907	15	6	the	the	DET
fcis-29907	15	7	lack	lack	NOUN
fcis-29907	15	8	of	of	ADP
fcis-29907	15	9	effective	effective	ADJ
fcis-29907	15	10	measurable	measurable	ADJ
fcis-29907	15	11	symptoms	symptom	NOUN
fcis-29907	15	12	(	(	PUNCT
fcis-29907	15	13	physiological	physiological	ADJ
fcis-29907	15	14	or	or	CCONJ
fcis-29907	15	15	psychological	psychological	ADJ
fcis-29907	15	16	)	)	PUNCT
fcis-29907	15	17	,	,	PUNCT
fcis-29907	15	18	the	the	DET
fcis-29907	15	19	current	current	ADJ
fcis-29907	15	20	assessment	assessment	NOUN
fcis-29907	15	21	of	of	ADP
fcis-29907	15	22	depressive	depressive	ADJ
fcis-29907	15	23	states	state	NOUN
fcis-29907	15	24	is	be	AUX
fcis-29907	15	25	primarily	primarily	ADV
fcis-29907	15	26	diagnosed	diagnose	VERB
fcis-29907	15	27	by	by	ADP
fcis-29907	15	28	clinical	clinical	ADJ
fcis-29907	15	29	physicians	physician	NOUN
fcis-29907	15	30	through	through	ADP
fcis-29907	15	31	scoring	scoring	NOUN
fcis-29907	15	32	.	.	PUNCT
fcis-29907	16	1	with	with	ADP
fcis-29907	16	2	the	the	DET
fcis-29907	16	3	advancement	advancement	NOUN
fcis-29907	16	4	of	of	ADP
fcis-29907	16	5	technology	technology	NOUN
fcis-29907	16	6	,	,	PUNCT
fcis-29907	16	7	ade	ade	PROPN
fcis-29907	16	8	(	(	PUNCT
fcis-29907	16	9	automatic	automatic	ADJ
fcis-29907	16	10	depression	depression	NOUN
fcis-29907	16	11	diagnosis	diagnosis	NOUN
fcis-29907	16	12	system	system	NOUN
fcis-29907	16	13	)	)	PUNCT
fcis-29907	16	14	has	have	AUX
fcis-29907	16	15	been	be	AUX
fcis-29907	16	16	introduced	introduce	VERB
fcis-29907	16	17	to	to	PART
fcis-29907	16	18	assist	assist	VERB
fcis-29907	16	19	in	in	ADP
fcis-29907	16	20	diagnosis	diagnosis	NOUN
fcis-29907	16	21	.	.	PUNCT
fcis-29907	17	1	depression	depression	NOUN
fcis-29907	17	2	speech	speech	NOUN
fcis-29907	17	3	detection	detection	NOUN
fcis-29907	17	4	based	base	VERB
fcis-29907	17	5	on	on	ADP
fcis-29907	17	6	self	self	NOUN
fcis-29907	17	7	-	-	PUNCT
fcis-29907	17	8	supervised	supervise	VERB
fcis-29907	17	9	pre	pre	ADJ
fcis-29907	17	10	-	-	NOUN
fcis-29907	17	11	training	training	NOUN
fcis-29907	17	12	is	be	AUX
fcis-29907	17	13	a	a	DET
fcis-29907	17	14	method	method	NOUN
fcis-29907	17	15	that	that	PRON
fcis-29907	17	16	utilizes	utilize	VERB
fcis-29907	17	17	deep	deep	ADJ
fcis-29907	17	18	learning	learning	NOUN
fcis-29907	17	19	technology	technology	NOUN
fcis-29907	17	20	to	to	PART
fcis-29907	17	21	extract	extract	VERB
fcis-29907	17	22	features	feature	NOUN
fcis-29907	17	23	from	from	ADP
fcis-29907	17	24	patients	patient	NOUN
fcis-29907	17	25	'	'	PART
fcis-29907	17	26	speech	speech	NOUN
fcis-29907	17	27	to	to	PART
fcis-29907	17	28	identify	identify	VERB
fcis-29907	17	29	and	and	CCONJ
fcis-29907	17	30	diagnose	diagnose	VERB
fcis-29907	17	31	depression	depression	NOUN
fcis-29907	17	32	.	.	PUNCT
fcis-29907	18	1	the	the	DET
fcis-29907	18	2	core	core	NOUN
fcis-29907	18	3	of	of	ADP
fcis-29907	18	4	this	this	DET
fcis-29907	18	5	method	method	NOUN
fcis-29907	18	6	lies	lie	VERB
fcis-29907	18	7	in	in	ADP
fcis-29907	18	8	pre	pre	ADJ
fcis-29907	18	9	-	-	NOUN
fcis-29907	18	10	training	training	NOUN
fcis-29907	18	11	with	with	ADP
fcis-29907	18	12	a	a	DET
fcis-29907	18	13	large	large	ADJ
fcis-29907	18	14	amount	amount	NOUN
fcis-29907	18	15	of	of	ADP
fcis-29907	18	16	unlabeled	unlabeled	ADJ
fcis-29907	18	17	data	datum	NOUN
fcis-29907	18	18	and	and	CCONJ
fcis-29907	18	19	then	then	ADV
fcis-29907	18	20	fine	fine	ADV
fcis-29907	18	21	-	-	PUNCT
fcis-29907	18	22	tuning	tuning	NOUN
fcis-29907	18	23	on	on	ADP
fcis-29907	18	24	specific	specific	ADJ
fcis-29907	18	25	downstream	downstream	ADJ
fcis-29907	18	26	tasks	task	NOUN
fcis-29907	18	27	to	to	PART
fcis-29907	18	28	achieve	achieve	VERB
fcis-29907	18	29	efficient	efficient	ADJ
fcis-29907	18	30	and	and	CCONJ
fcis-29907	18	31	accurate	accurate	ADJ
fcis-29907	18	32	depression	depression	NOUN
fcis-29907	18	33	detection	detection	NOUN
fcis-29907	18	34	.	.	PUNCT
fcis-29907	19	1	real	real	ADJ
fcis-29907	19	2	-	-	PUNCT
fcis-29907	19	3	time	time	NOUN
fcis-29907	19	4	assessment	assessment	NOUN
fcis-29907	19	5	of	of	ADP
fcis-29907	19	6	the	the	DET
fcis-29907	19	7	severity	severity	NOUN
fcis-29907	19	8	of	of	ADP
fcis-29907	19	9	depressive	depressive	ADJ
fcis-29907	19	10	symptoms	symptom	NOUN
fcis-29907	19	11	is	be	AUX
fcis-29907	19	12	of	of	ADP
fcis-29907	19	13	great	great	ADJ
fcis-29907	19	14	significance	significance	NOUN
fcis-29907	19	15	for	for	ADP
fcis-29907	19	16	the	the	DET
fcis-29907	19	17	diagnosis	diagnosis	NOUN
fcis-29907	19	18	and	and	CCONJ
fcis-29907	19	19	treatment	treatment	NOUN
fcis-29907	19	20	of	of	ADP
fcis-29907	19	21	patients	patient	NOUN
fcis-29907	19	22	with	with	ADP
fcis-29907	19	23	depression	depression	NOUN
fcis-29907	19	24	.	.	PUNCT
fcis-29907	20	1	in	in	ADP
fcis-29907	20	2	clinical	clinical	ADJ
fcis-29907	20	3	practice	practice	NOUN
fcis-29907	20	4	,	,	PUNCT
fcis-29907	20	5	assessment	assessment	NOUN
fcis-29907	20	6	methods	method	NOUN
fcis-29907	20	7	mainly	mainly	ADV
fcis-29907	20	8	rely	rely	VERB
fcis-29907	20	9	on	on	ADP
fcis-29907	20	10	psychological	psychological	ADJ
fcis-29907	20	11	scales	scale	NOUN
fcis-29907	20	12	and	and	CCONJ
fcis-29907	20	13	doctor	doctor	NOUN
fcis-29907	20	14	-	-	PUNCT
fcis-29907	20	15	patient	patient	NOUN
fcis-29907	20	16	interviews	interview	NOUN
fcis-29907	20	17	,	,	PUNCT
fcis-29907	20	18	which	which	PRON
fcis-29907	20	19	are	be	AUX
fcis-29907	20	20	time	time	NOUN
fcis-29907	20	21	-	-	PUNCT
fcis-29907	20	22	consuming	consume	VERB
fcis-29907	20	23	and	and	CCONJ
fcis-29907	20	24	labor	labor	NOUN
fcis-29907	20	25	-	-	PUNCT
fcis-29907	20	26	intensive	intensive	ADJ
fcis-29907	20	27	.	.	PUNCT
fcis-29907	21	1	at	at	ADP
fcis-29907	21	2	the	the	DET
fcis-29907	21	3	same	same	ADJ
fcis-29907	21	4	time	time	NOUN
fcis-29907	21	5	,	,	PUNCT
fcis-29907	21	6	the	the	DET
fcis-29907	21	7	accuracy	accuracy	NOUN
fcis-29907	21	8	of	of	ADP
fcis-29907	21	9	the	the	DET
fcis-29907	21	10	results	result	NOUN
fcis-29907	21	11	largely	largely	ADV
fcis-29907	21	12	depends	depend	VERB
fcis-29907	21	13	on	on	ADP
fcis-29907	21	14	the	the	DET
fcis-29907	21	15	subjective	subjective	ADJ
fcis-29907	21	16	judgment	judgment	NOUN
fcis-29907	21	17	of	of	ADP
fcis-29907	21	18	clinical	clinical	ADJ
fcis-29907	21	19	physicians	physician	NOUN
fcis-29907	21	20	.	.	PUNCT
fcis-29907	22	1	with	with	ADP
fcis-29907	22	2	the	the	DET
fcis-29907	22	3	development	development	NOUN
fcis-29907	22	4	of	of	ADP
fcis-29907	22	5	artificial	artificial	ADJ
fcis-29907	22	6	intelligence	intelligence	NOUN
fcis-29907	22	7	technology	technology	NOUN
fcis-29907	22	8	,	,	PUNCT
fcis-29907	22	9	an	an	DET
fcis-29907	22	10	increasing	increase	VERB
fcis-29907	22	11	number	number	NOUN
fcis-29907	22	12	of	of	ADP
fcis-29907	22	13	machine	machine	NOUN
fcis-29907	22	14	learning	learning	NOUN
fcis-29907	22	15	methods	method	NOUN
fcis-29907	22	16	diagnose	diagnose	VERB
fcis-29907	22	17	depression	depression	NOUN
fcis-29907	22	18	through	through	ADP
fcis-29907	22	19	feature	feature	NOUN
fcis-29907	22	20	recognition	recognition	NOUN
fcis-29907	22	21	.	.	PUNCT
fcis-29907	23	1	to	to	PART
fcis-29907	23	2	address	address	VERB
fcis-29907	23	3	the	the	DET
fcis-29907	23	4	issues	issue	NOUN
fcis-29907	23	5	with	with	ADP
fcis-29907	23	6	traditional	traditional	ADJ
fcis-29907	23	7	depression	depression	NOUN
fcis-29907	23	8	detection	detection	NOUN
fcis-29907	23	9	methods	method	NOUN
fcis-29907	23	10	,	,	PUNCT
fcis-29907	23	11	this	this	DET
fcis-29907	23	12	paper	paper	NOUN
fcis-29907	23	13	starts	start	VERB
fcis-29907	23	14	from	from	ADP
fcis-29907	23	15	audio	audio	NOUN
fcis-29907	23	16	and	and	CCONJ
fcis-29907	23	17	selects	select	VERB
fcis-29907	23	18	the	the	DET
fcis-29907	23	19	optimal	optimal	ADJ
fcis-29907	23	20	path	path	NOUN
fcis-29907	23	21	through	through	ADP
fcis-29907	23	22	the	the	DET
fcis-29907	23	23	comparison	comparison	NOUN
fcis-29907	23	24	of	of	ADP
fcis-29907	23	25	multiple	multiple	ADJ
fcis-29907	23	26	deep	deep	ADJ
fcis-29907	23	27	learning	learning	NOUN
fcis-29907	23	28	models	model	NOUN
fcis-29907	23	29	for	for	ADP
fcis-29907	23	30	depression	depression	NOUN
fcis-29907	23	31	auxiliary	auxiliary	ADJ
fcis-29907	23	32	diagnosis	diagnosis	NOUN
fcis-29907	23	33	effects	effect	NOUN
fcis-29907	23	34	.	.	PUNCT
fcis-29907	24	1	2	2	X
fcis-29907	24	2	.	.	X
fcis-29907	24	3	daic	daic	PROPN
fcis-29907	24	4	-	-	PUNCT
fcis-29907	24	5	woz	woz	PROPN
fcis-29907	24	6	dataset	dataset	VERB
fcis-29907	24	7	various	various	ADJ
fcis-29907	24	8	deep	deep	ADJ
fcis-29907	24	9	learning	learning	NOUN
fcis-29907	24	10	models	model	NOUN
fcis-29907	24	11	are	be	AUX
fcis-29907	24	12	trained	train	VERB
fcis-29907	24	13	using	use	VERB
fcis-29907	24	14	the	the	DET
fcis-29907	24	15	speech	speech	NOUN
fcis-29907	24	16	data	datum	NOUN
fcis-29907	24	17	from	from	ADP
fcis-29907	24	18	the	the	DET
fcis-29907	24	19	daic	daic	PROPN
fcis-29907	24	20	-	-	PUNCT
fcis-29907	24	21	woz	woz	PROPN
fcis-29907	24	22	dataset	dataset	NOUN
fcis-29907	24	23	,	,	PUNCT
fcis-29907	24	24	where	where	SCONJ
fcis-29907	24	25	the	the	DET
fcis-29907	24	26	voice	voice	NOUN
fcis-29907	24	27	signals	signal	NOUN
fcis-29907	24	28	are	be	AUX
fcis-29907	24	29	decomposed	decompose	VERB
fcis-29907	24	30	into	into	ADP
fcis-29907	24	31	individual	individual	ADJ
fcis-29907	24	32	frequencies	frequency	NOUN
fcis-29907	24	33	and	and	CCONJ
fcis-29907	24	34	frequency	frequency	NOUN
fcis-29907	24	35	amplitudes	amplitude	NOUN
fcis-29907	24	36	through	through	ADP
fcis-29907	24	37	fourier	fourier	ADJ
fcis-29907	24	38	transformation	transformation	NOUN
fcis-29907	24	39	,	,	PUNCT
fcis-29907	24	40	converting	convert	VERB
fcis-29907	24	41	the	the	DET
fcis-29907	24	42	signals	signal	NOUN
fcis-29907	24	43	from	from	ADP
fcis-29907	24	44	the	the	DET
fcis-29907	24	45	time	time	NOUN
fcis-29907	24	46	domain	domain	NOUN
fcis-29907	24	47	to	to	ADP
fcis-29907	24	48	the	the	DET
fcis-29907	24	49	frequency	frequency	NOUN
fcis-29907	24	50	domain	domain	NOUN
fcis-29907	24	51	.	.	PUNCT
fcis-29907	25	1	the	the	DET
fcis-29907	25	2	daic	daic	PROPN
fcis-29907	25	3	-	-	PUNCT
fcis-29907	25	4	woz	woz	PROPN
fcis-29907	25	5	dataset	dataset	NOUN
fcis-29907	25	6	(	(	PUNCT
fcis-29907	25	7	distress	distress	NOUN
fcis-29907	25	8	analysis	analysis	NOUN
fcis-29907	25	9	interview	interview	NOUN
fcis-29907	25	10	corpus	corpus	NOUN
fcis-29907	25	11	/	/	SYM
fcis-29907	25	12	wizard	wizard	NOUN
fcis-29907	25	13	-	-	PUNCT
fcis-29907	25	14	of	of	ADP
fcis-29907	25	15	-	-	PUNCT
fcis-29907	25	16	oz	oz	NOUN
fcis-29907	25	17	set	set	NOUN
fcis-29907	25	18	)	)	PUNCT
fcis-29907	25	19	is	be	AUX
fcis-29907	25	20	a	a	DET
fcis-29907	25	21	corpus	corpus	NOUN
fcis-29907	25	22	specifically	specifically	ADV
fcis-29907	25	23	designed	design	VERB
fcis-29907	25	24	for	for	ADP
fcis-29907	25	25	depression	depression	NOUN
fcis-29907	25	26	detection	detection	NOUN
fcis-29907	25	27	,	,	PUNCT
fcis-29907	25	28	comprising	comprise	VERB
fcis-29907	25	29	voice	voice	NOUN
fcis-29907	25	30	and	and	CCONJ
fcis-29907	25	31	text	text	NOUN
fcis-29907	25	32	samples	sample	NOUN
fcis-29907	25	33	from	from	ADP
fcis-29907	25	34	189	189	NUM
fcis-29907	25	35	interviewees	interviewee	NOUN
fcis-29907	25	36	,	,	PUNCT
fcis-29907	25	37	with	with	ADP
fcis-29907	25	38	each	each	DET
fcis-29907	25	39	participant	participant	NOUN
fcis-29907	25	40	provided	provide	VERB
fcis-29907	25	41	two	two	NUM
fcis-29907	25	42	labels	label	NOUN
fcis-29907	25	43	:	:	PUNCT
fcis-29907	25	44	a	a	DET
fcis-29907	25	45	binary	binary	ADJ
fcis-29907	25	46	diagnosis	diagnosis	NOUN
fcis-29907	25	47	of	of	ADP
fcis-29907	25	48	depression	depression	NOUN
fcis-29907	25	49	/	/	SYM
fcis-29907	25	50	health	health	NOUN
fcis-29907	25	51	and	and	CCONJ
fcis-29907	25	52	the	the	DET
fcis-29907	25	53	patient	patient	NOUN
fcis-29907	25	54	's	's	PART
fcis-29907	25	55	eight	eight	NUM
fcis-29907	25	56	-	-	PUNCT
fcis-29907	25	57	item	item	NOUN
fcis-29907	25	58	patient	patient	ADJ
fcis-29907	25	59	health	health	NOUN
fcis-29907	25	60	questionnaire	questionnaire	NOUN
fcis-29907	25	61	(	(	PUNCT
fcis-29907	25	62	phq-8	phq-8	NOUN
fcis-29907	25	63	)	)	PUNCT
fcis-29907	25	64	score	score	NOUN
fcis-29907	25	65	.	.	PUNCT
fcis-29907	26	1	this	this	DET
fcis-29907	26	2	dataset	dataset	NOUN
fcis-29907	26	3	is	be	AUX
fcis-29907	26	4	part	part	NOUN
fcis-29907	26	5	of	of	ADP
fcis-29907	26	6	the	the	DET
fcis-29907	26	7	larger	large	ADJ
fcis-29907	26	8	disease	disease	NOUN
fcis-29907	26	9	analysis	analysis	NOUN
fcis-29907	26	10	interview	interview	NOUN
fcis-29907	26	11	corpus	corpus	NOUN
fcis-29907	26	12	(	(	PUNCT
fcis-29907	26	13	daic	daic	PROPN
fcis-29907	26	14	)	)	PUNCT
fcis-29907	26	15	,	,	PUNCT
fcis-29907	26	16	primarily	primarily	ADV
fcis-29907	26	17	used	use	VERB
fcis-29907	26	18	to	to	PART
fcis-29907	26	19	support	support	VERB
fcis-29907	26	20	the	the	DET
fcis-29907	26	21	diagnosis	diagnosis	NOUN
fcis-29907	26	22	of	of	ADP
fcis-29907	26	23	psychological	psychological	ADJ
fcis-29907	26	24	distress	distress	NOUN
fcis-29907	26	25	conditions	condition	NOUN
fcis-29907	26	26	such	such	ADJ
fcis-29907	26	27	as	as	ADP
fcis-29907	26	28	anxiety	anxiety	NOUN
fcis-29907	26	29	,	,	PUNCT
fcis-29907	26	30	depression	depression	NOUN
fcis-29907	26	31	,	,	PUNCT
fcis-29907	26	32	and	and	CCONJ
fcis-29907	26	33	post	post	ADJ
fcis-29907	26	34	-	-	ADJ
fcis-29907	26	35	traumatic	traumatic	ADJ
fcis-29907	26	36	stress	stress	NOUN
fcis-29907	26	37	disorder	disorder	NOUN
fcis-29907	26	38	(	(	PUNCT
fcis-29907	26	39	ptsd	ptsd	PROPN
fcis-29907	26	40	)	)	PUNCT
fcis-29907	26	41	.	.	PUNCT
fcis-29907	27	1	the	the	DET
fcis-29907	27	2	audio	audio	ADJ
fcis-29907	27	3	portion	portion	NOUN
fcis-29907	27	4	consists	consist	VERB
fcis-29907	27	5	of	of	ADP
fcis-29907	27	6	interviews	interview	NOUN
fcis-29907	27	7	conducted	conduct	VERB
fcis-29907	27	8	by	by	ADP
fcis-29907	27	9	an	an	DET
fcis-29907	27	10	animated	animate	VERB
fcis-29907	27	11	virtual	virtual	ADJ
fcis-29907	27	12	interviewer	interviewer	NOUN
fcis-29907	27	13	named	name	VERB
fcis-29907	27	14	ellie	ellie	PROPN
fcis-29907	27	15	,	,	PUNCT
fcis-29907	27	16	with	with	ADP
fcis-29907	27	17	a	a	DET
fcis-29907	27	18	recording	recording	NOUN
fcis-29907	27	19	frequency	frequency	NOUN
fcis-29907	27	20	of	of	ADP
fcis-29907	27	21	16khz	16khz	NOUN
fcis-29907	27	22	.	.	PUNCT
fcis-29907	28	1	due	due	ADP
fcis-29907	28	2	to	to	ADP
fcis-29907	28	3	the	the	DET
fcis-29907	28	4	presence	presence	NOUN
fcis-29907	28	5	of	of	ADP
fcis-29907	28	6	some	some	DET
fcis-29907	28	7	noise	noise	NOUN
fcis-29907	28	8	and	and	CCONJ
fcis-29907	28	9	abrupt	abrupt	ADJ
fcis-29907	28	10	pauses	pause	NOUN
fcis-29907	28	11	in	in	ADP
fcis-29907	28	12	the	the	DET
fcis-29907	28	13	original	original	ADJ
fcis-29907	28	14	audio	audio	NOUN
fcis-29907	28	15	,	,	PUNCT
fcis-29907	28	16	irrelevant	irrelevant	ADJ
fcis-29907	28	17	repetitive	repetitive	ADJ
fcis-29907	28	18	statements	statement	NOUN
fcis-29907	28	19	are	be	AUX
fcis-29907	28	20	removed	remove	VERB
fcis-29907	28	21	during	during	ADP
fcis-29907	28	22	preprocessing	preprocessing	NOUN
fcis-29907	28	23	,	,	PUNCT
fcis-29907	28	24	and	and	CCONJ
fcis-29907	28	25	features	feature	NOUN
fcis-29907	28	26	are	be	AUX
fcis-29907	28	27	re	re	VERB
fcis-29907	28	28	-	-	VERB
fcis-29907	28	29	extracted	extract	VERB
fcis-29907	28	30	.	.	PUNCT
fcis-29907	29	1	finally	finally	ADV
fcis-29907	29	2	,	,	PUNCT
fcis-29907	29	3	the	the	DET
fcis-29907	29	4	extracted	extract	VERB
fcis-29907	29	5	speech	speech	NOUN
fcis-29907	29	6	feature	feature	NOUN
fcis-29907	29	7	dataset	dataset	NOUN
fcis-29907	29	8	is	be	AUX
fcis-29907	29	9	divided	divide	VERB
fcis-29907	29	10	into	into	ADP
fcis-29907	29	11	a	a	DET
fcis-29907	29	12	training	training	NOUN
fcis-29907	29	13	set	set	NOUN
fcis-29907	29	14	of	of	ADP
fcis-29907	29	15	70	70	NUM
fcis-29907	29	16	%	%	NOUN
fcis-29907	29	17	,	,	PUNCT
fcis-29907	29	18	a	a	DET
fcis-29907	29	19	validation	validation	NOUN
fcis-29907	29	20	set	set	NOUN
fcis-29907	29	21	of	of	ADP
fcis-29907	29	22	15	15	NUM
fcis-29907	29	23	%	%	NOUN
fcis-29907	29	24	,	,	PUNCT
fcis-29907	29	25	and	and	CCONJ
fcis-29907	29	26	a	a	DET
fcis-29907	29	27	test	test	NOUN
fcis-29907	29	28	set	set	NOUN
fcis-29907	29	29	of	of	ADP
fcis-29907	29	30	15	15	NUM
fcis-29907	29	31	%	%	NOUN
fcis-29907	29	32	.	.	PUNCT
fcis-29907	30	1	3	3	X
fcis-29907	30	2	.	.	X
fcis-29907	30	3	self	self	NOUN
fcis-29907	30	4	-	-	PUNCT
fcis-29907	30	5	supervised	supervise	VERB
fcis-29907	30	6	pre	pre	ADJ
fcis-29907	30	7	-	-	ADJ
fcis-29907	30	8	training	training	ADJ
fcis-29907	30	9	models	model	NOUN
fcis-29907	30	10	a	a	DET
fcis-29907	30	11	primary	primary	ADJ
fcis-29907	30	12	bottleneck	bottleneck	NOUN
fcis-29907	30	13	in	in	ADP
fcis-29907	30	14	deep	deep	ADJ
fcis-29907	30	15	learning	learning	NOUN
fcis-29907	30	16	-	-	PUNCT
fcis-29907	30	17	based	base	VERB
fcis-29907	30	18	depression	depression	NOUN
fcis-29907	30	19	research	research	NOUN
fcis-29907	30	20	is	be	AUX
fcis-29907	30	21	the	the	DET
fcis-29907	30	22	limited	limited	ADJ
fcis-29907	30	23	availability	availability	NOUN
fcis-29907	30	24	and	and	CCONJ
fcis-29907	30	25	sparsity	sparsity	NOUN
fcis-29907	30	26	of	of	ADP
fcis-29907	30	27	data	datum	NOUN
fcis-29907	30	28	.	.	PUNCT
fcis-29907	31	1	in	in	ADP
fcis-29907	31	2	recent	recent	ADJ
fcis-29907	31	3	years	year	NOUN
fcis-29907	31	4	,	,	PUNCT
fcis-29907	31	5	self	self	NOUN
fcis-29907	31	6	-	-	PUNCT
fcis-29907	31	7	supervised	supervise	VERB
fcis-29907	31	8	learning	learning	NOUN
fcis-29907	31	9	has	have	AUX
fcis-29907	31	10	achieved	achieve	VERB
fcis-29907	31	11	success	success	NOUN
fcis-29907	31	12	in	in	ADP
fcis-29907	31	13	pre	pre	ADJ
fcis-29907	31	14	-	-	ADJ
fcis-29907	31	15	training	training	ADJ
fcis-29907	31	16	voice	voice	NOUN
fcis-29907	31	17	signals	signal	NOUN
fcis-29907	31	18	and	and	CCONJ
fcis-29907	31	19	has	have	AUX
fcis-29907	31	20	been	be	AUX
fcis-29907	31	21	widely	widely	ADV
fcis-29907	31	22	applied	apply	VERB
fcis-29907	31	23	to	to	ADP
fcis-29907	31	24	data	data	NOUN
fcis-29907	31	25	-	-	PUNCT
fcis-29907	31	26	sparse	sparse	ADJ
fcis-29907	31	27	related	related	ADJ
fcis-29907	31	28	tasks	task	NOUN
fcis-29907	31	29	.	.	PUNCT
fcis-29907	32	1	self	self	NOUN
fcis-29907	32	2	-	-	PUNCT
fcis-29907	32	3	supervised	supervise	VERB
fcis-29907	32	4	pre	pre	ADJ
fcis-29907	32	5	-	-	ADJ
fcis-29907	32	6	training	training	ADJ
fcis-29907	32	7	models	model	NOUN
fcis-29907	32	8	can	can	AUX
fcis-29907	32	9	directly	directly	ADV
fcis-29907	32	10	learn	learn	VERB
fcis-29907	32	11	meaningful	meaningful	ADJ
fcis-29907	32	12	speech	speech	NOUN
fcis-29907	32	13	representations	representation	NOUN
fcis-29907	32	14	from	from	ADP
fcis-29907	32	15	raw	raw	ADJ
fcis-29907	32	16	audio	audio	NOUN
fcis-29907	32	17	waveforms	waveform	NOUN
fcis-29907	32	18	,	,	PUNCT
fcis-29907	32	19	thereby	thereby	ADV
fcis-29907	32	20	reducing	reduce	VERB
fcis-29907	32	21	the	the	DET
fcis-29907	32	22	workload	workload	NOUN
fcis-29907	32	23	of	of	ADP
fcis-29907	32	24	manual	manual	ADJ
fcis-29907	32	25	data	datum	NOUN
fcis-29907	32	26	annotation	annotation	NOUN
fcis-29907	32	27	.	.	PUNCT
fcis-29907	33	1	this	this	PRON
fcis-29907	33	2	allows	allow	VERB
fcis-29907	33	3	it	it	PRON
fcis-29907	33	4	to	to	PART
fcis-29907	33	5	leverage	leverage	VERB
fcis-29907	33	6	a	a	DET
fcis-29907	33	7	large	large	ADJ
fcis-29907	33	8	amount	amount	NOUN
fcis-29907	33	9	of	of	ADP
fcis-29907	33	10	unmarked	unmarked	ADJ
fcis-29907	33	11	voice	voice	NOUN
fcis-29907	33	12	data	datum	NOUN
fcis-29907	33	13	for	for	ADP
fcis-29907	33	14	pre	pre	NOUN
fcis-29907	33	15	-	-	NOUN
fcis-29907	33	16	training	training	NOUN
fcis-29907	33	17	.	.	PUNCT
fcis-29907	34	1	in	in	ADP
fcis-29907	34	2	depression	depression	NOUN
fcis-29907	34	3	speech	speech	NOUN
fcis-29907	34	4	107	107	NUM
fcis-29907	34	5	detection	detection	NOUN
fcis-29907	34	6	,	,	PUNCT
fcis-29907	34	7	researchers	researcher	NOUN
fcis-29907	34	8	have	have	AUX
fcis-29907	34	9	found	find	VERB
fcis-29907	34	10	significant	significant	ADJ
fcis-29907	34	11	differences	difference	NOUN
fcis-29907	34	12	in	in	ADP
fcis-29907	34	13	voice	voice	NOUN
fcis-29907	34	14	features	feature	NOUN
fcis-29907	34	15	between	between	ADP
fcis-29907	34	16	depressed	depressed	ADJ
fcis-29907	34	17	patients	patient	NOUN
fcis-29907	34	18	and	and	CCONJ
fcis-29907	34	19	the	the	DET
fcis-29907	34	20	normal	normal	ADJ
fcis-29907	34	21	population	population	NOUN
fcis-29907	34	22	,	,	PUNCT
fcis-29907	34	23	such	such	ADJ
fcis-29907	34	24	as	as	ADP
fcis-29907	34	25	lower	low	ADJ
fcis-29907	34	26	pitch	pitch	NOUN
fcis-29907	34	27	and	and	CCONJ
fcis-29907	34	28	slower	slow	ADJ
fcis-29907	34	29	speech	speech	NOUN
fcis-29907	34	30	rate	rate	NOUN
fcis-29907	34	31	,	,	PUNCT
fcis-29907	34	32	which	which	PRON
fcis-29907	34	33	can	can	AUX
fcis-29907	34	34	be	be	AUX
fcis-29907	34	35	effectively	effectively	ADV
fcis-29907	34	36	extracted	extract	VERB
fcis-29907	34	37	and	and	CCONJ
fcis-29907	34	38	analyzed	analyze	VERB
fcis-29907	34	39	through	through	ADP
fcis-29907	34	40	selfsupervised	selfsupervise	VERB
fcis-29907	34	41	learning	learning	NOUN
fcis-29907	34	42	methods	method	NOUN
fcis-29907	34	43	.	.	PUNCT
fcis-29907	35	1	3.1	3.1	NUM
fcis-29907	35	2	.	.	PUNCT
fcis-29907	35	3	feature	feature	NOUN
fcis-29907	35	4	extractor	extractor	NOUN
fcis-29907	35	5	wav2vec2.0	wav2vec2.0	PROPN
fcis-29907	35	6	is	be	AUX
fcis-29907	35	7	one	one	NUM
fcis-29907	35	8	of	of	ADP
fcis-29907	35	9	the	the	DET
fcis-29907	35	10	most	most	ADV
fcis-29907	35	11	widely	widely	ADV
fcis-29907	35	12	used	use	VERB
fcis-29907	35	13	self	self	NOUN
fcis-29907	35	14	-	-	PUNCT
fcis-29907	35	15	supervised	supervise	VERB
fcis-29907	35	16	pre	pre	ADJ
fcis-29907	35	17	-	-	ADJ
fcis-29907	35	18	training	training	ADJ
fcis-29907	35	19	models	model	NOUN
fcis-29907	35	20	in	in	ADP
fcis-29907	35	21	the	the	DET
fcis-29907	35	22	field	field	NOUN
fcis-29907	35	23	of	of	ADP
fcis-29907	35	24	voice	voice	NOUN
fcis-29907	35	25	signal	signal	NOUN
fcis-29907	35	26	processing	processing	NOUN
fcis-29907	35	27	.	.	PUNCT
fcis-29907	36	1	it	it	PRON
fcis-29907	36	2	learns	learn	VERB
fcis-29907	36	3	effective	effective	ADJ
fcis-29907	36	4	encoding	encoding	NOUN
fcis-29907	36	5	of	of	ADP
fcis-29907	36	6	voice	voice	NOUN
fcis-29907	36	7	signals	signal	NOUN
fcis-29907	36	8	by	by	ADP
fcis-29907	36	9	predicting	predict	VERB
fcis-29907	36	10	the	the	DET
fcis-29907	36	11	representations	representation	NOUN
fcis-29907	36	12	of	of	ADP
fcis-29907	36	13	masked	masked	ADJ
fcis-29907	36	14	parts	part	NOUN
fcis-29907	36	15	in	in	ADP
fcis-29907	36	16	the	the	DET
fcis-29907	36	17	audio	audio	ADJ
fcis-29907	36	18	sequence	sequence	NOUN
fcis-29907	36	19	in	in	ADP
fcis-29907	36	20	an	an	DET
fcis-29907	36	21	unsupervised	unsupervised	ADJ
fcis-29907	36	22	setting	setting	NOUN
fcis-29907	36	23	and	and	CCONJ
fcis-29907	36	24	is	be	AUX
fcis-29907	36	25	widely	widely	ADV
fcis-29907	36	26	used	use	VERB
fcis-29907	36	27	in	in	ADP
fcis-29907	36	28	downstream	downstream	ADJ
fcis-29907	36	29	voice	voice	NOUN
fcis-29907	36	30	processing	processing	NOUN
fcis-29907	36	31	tasks	task	NOUN
fcis-29907	36	32	such	such	ADJ
fcis-29907	36	33	as	as	ADP
fcis-29907	36	34	speech	speech	NOUN
fcis-29907	36	35	recognition	recognition	NOUN
fcis-29907	36	36	,	,	PUNCT
fcis-29907	36	37	speaker	speaker	NOUN
fcis-29907	36	38	recognition	recognition	NOUN
fcis-29907	36	39	,	,	PUNCT
fcis-29907	36	40	or	or	CCONJ
fcis-29907	36	41	emotion	emotion	NOUN
fcis-29907	36	42	analysis	analysis	NOUN
fcis-29907	36	43	.	.	PUNCT
fcis-29907	37	1	vq	vq	NOUN
fcis-29907	37	2	-	-	PUNCT
fcis-29907	37	3	wav2vec	wav2vec	NOUN
fcis-29907	37	4	further	far	ADV
fcis-29907	37	5	improves	improve	VERB
fcis-29907	37	6	upon	upon	SCONJ
fcis-29907	37	7	wav2vec	wav2vec	NOUN
fcis-29907	37	8	by	by	ADP
fcis-29907	37	9	adding	add	VERB
fcis-29907	37	10	a	a	DET
fcis-29907	37	11	quantization	quantization	NOUN
fcis-29907	37	12	module	module	NOUN
fcis-29907	37	13	,	,	PUNCT
fcis-29907	37	14	including	include	VERB
fcis-29907	37	15	gumbel	gumbel	NOUN
fcis-29907	37	16	-	-	PUNCT
fcis-29907	37	17	softmax	softmax	NOUN
fcis-29907	37	18	and	and	CCONJ
fcis-29907	37	19	kmeans	kmean	NOUN
fcis-29907	37	20	clustering	cluster	VERB
fcis-29907	37	21	quantization	quantization	NOUN
fcis-29907	37	22	methods	method	NOUN
fcis-29907	37	23	.	.	PUNCT
fcis-29907	38	1	this	this	DET
fcis-29907	38	2	step	step	NOUN
fcis-29907	38	3	aims	aim	VERB
fcis-29907	38	4	to	to	PART
fcis-29907	38	5	discretize	discretize	VERB
fcis-29907	38	6	the	the	DET
fcis-29907	38	7	input	input	NOUN
fcis-29907	38	8	,	,	PUNCT
fcis-29907	38	9	facilitating	facilitate	VERB
fcis-29907	38	10	the	the	DET
fcis-29907	38	11	use	use	NOUN
fcis-29907	38	12	of	of	ADP
fcis-29907	38	13	the	the	DET
fcis-29907	38	14	transformer	transformer	NOUN
fcis-29907	38	15	's	's	PART
fcis-29907	38	16	mask	mask	NOUN
fcis-29907	38	17	loss	loss	NOUN
fcis-29907	38	18	.	.	PUNCT
fcis-29907	39	1	the	the	DET
fcis-29907	39	2	overall	overall	ADJ
fcis-29907	39	3	training	training	NOUN
fcis-29907	39	4	process	process	NOUN
fcis-29907	39	5	includes	include	VERB
fcis-29907	39	6	three	three	NUM
fcis-29907	39	7	steps	step	NOUN
fcis-29907	39	8	:	:	PUNCT
fcis-29907	39	9	1.train	1.train	NUM
fcis-29907	39	10	vq	vq	NOUN
fcis-29907	39	11	-	-	PUNCT
fcis-29907	39	12	wav2vec	wav2vec	NOUN
fcis-29907	39	13	.	.	PUNCT
fcis-29907	40	1	2.further	2.further	NUM
fcis-29907	40	2	pre	pre	ADJ
fcis-29907	40	3	-	-	ADJ
fcis-29907	40	4	train	train	ADJ
fcis-29907	40	5	bert	bert	NOUN
fcis-29907	40	6	based	base	VERB
fcis-29907	40	7	on	on	ADP
fcis-29907	40	8	the	the	DET
fcis-29907	40	9	discretized	discretized	ADJ
fcis-29907	40	10	output	output	NOUN
fcis-29907	40	11	of	of	ADP
fcis-29907	40	12	vq	vq	NOUN
fcis-29907	40	13	-	-	PUNCT
fcis-29907	40	14	wav2vec	wav2vec	NOUN
fcis-29907	40	15	.	.	PUNCT
fcis-29907	41	1	3.use	3.use	NUM
fcis-29907	41	2	the	the	DET
fcis-29907	41	3	bert	bert	ADJ
fcis-29907	41	4	pre	pre	ADJ
fcis-29907	41	5	-	-	ADJ
fcis-29907	41	6	training	training	ADJ
fcis-29907	41	7	model	model	NOUN
fcis-29907	41	8	as	as	ADP
fcis-29907	41	9	a	a	DET
fcis-29907	41	10	feature	feature	NOUN
fcis-29907	41	11	extractor	extractor	NOUN
fcis-29907	41	12	,	,	PUNCT
fcis-29907	41	13	and	and	CCONJ
fcis-29907	41	14	the	the	DET
fcis-29907	41	15	extracted	extract	VERB
fcis-29907	41	16	features	feature	NOUN
fcis-29907	41	17	as	as	ADP
fcis-29907	41	18	inputs	input	NOUN
fcis-29907	41	19	for	for	ADP
fcis-29907	41	20	am	am	NOUN
fcis-29907	41	21	.	.	PUNCT
fcis-29907	42	1	this	this	DET
fcis-29907	42	2	paper	paper	NOUN
fcis-29907	42	3	mainly	mainly	ADV
fcis-29907	42	4	fine	fine	ADJ
fcis-29907	42	5	-	-	PUNCT
fcis-29907	42	6	tunes	tune	NOUN
fcis-29907	42	7	the	the	DET
fcis-29907	42	8	vq	vq	NOUN
fcis-29907	42	9	-	-	PUNCT
fcis-29907	42	10	wav2vec	wav2vec	NOUN
fcis-29907	42	11	model	model	NOUN
fcis-29907	42	12	,	,	PUNCT
fcis-29907	42	13	which	which	PRON
fcis-29907	42	14	is	be	AUX
fcis-29907	42	15	used	use	VERB
fcis-29907	42	16	as	as	ADP
fcis-29907	42	17	a	a	DET
fcis-29907	42	18	feature	feature	NOUN
fcis-29907	42	19	extractor	extractor	NOUN
fcis-29907	42	20	for	for	ADP
fcis-29907	42	21	the	the	DET
fcis-29907	42	22	audio	audio	ADJ
fcis-29907	42	23	files	file	NOUN
fcis-29907	42	24	in	in	ADP
fcis-29907	42	25	the	the	DET
fcis-29907	42	26	daicwoz	daicwoz	PROPN
fcis-29907	42	27	dataset	dataset	NOUN
fcis-29907	42	28	.	.	PUNCT
fcis-29907	43	1	the	the	DET
fcis-29907	43	2	maximum	maximum	ADJ
fcis-29907	43	3	voice	voice	NOUN
fcis-29907	43	4	length	length	NOUN
fcis-29907	43	5	for	for	ADP
fcis-29907	43	6	vq	vq	NOUN
fcis-29907	43	7	-	-	PUNCT
fcis-29907	43	8	wav2vec	wav2vec	NOUN
fcis-29907	43	9	is	be	AUX
fcis-29907	43	10	10	10	NUM
fcis-29907	43	11	seconds	second	NOUN
fcis-29907	43	12	,	,	PUNCT
fcis-29907	43	13	and	and	CCONJ
fcis-29907	43	14	the	the	DET
fcis-29907	43	15	sampling	sample	VERB
fcis-29907	43	16	rate	rate	NOUN
fcis-29907	43	17	is	be	AUX
fcis-29907	43	18	fixed	fix	VERB
fcis-29907	43	19	at	at	ADP
fcis-29907	43	20	16khz	16khz	NOUN
fcis-29907	43	21	.	.	PUNCT
fcis-29907	44	1	therefore	therefore	ADV
fcis-29907	44	2	,	,	PUNCT
fcis-29907	44	3	the	the	DET
fcis-29907	44	4	original	original	ADJ
fcis-29907	44	5	audio	audio	NOUN
fcis-29907	44	6	is	be	AUX
fcis-29907	44	7	segmented	segment	VERB
fcis-29907	44	8	and	and	CCONJ
fcis-29907	44	9	preprocessed	preprocesse	VERB
fcis-29907	44	10	based	base	VERB
fcis-29907	44	11	on	on	ADP
fcis-29907	44	12	the	the	DET
fcis-29907	44	13	start_time	start_time	ADJ
fcis-29907	44	14	and	and	CCONJ
fcis-29907	44	15	stop_time	stop_time	NOUN
fcis-29907	44	16	in	in	ADP
fcis-29907	44	17	the	the	DET
fcis-29907	44	18	transcript.csv	transcript.csv	DET
fcis-29907	44	19	file	file	NOUN
fcis-29907	44	20	.	.	PUNCT
fcis-29907	45	1	start_time	start_time	NUM
fcis-29907	45	2	stop_time	stop_time	PROPN
fcis-29907	45	3	speaker	speaker	NOUN
fcis-29907	45	4	value	value	VERB
fcis-29907	45	5	411.950	411.950	NUM
fcis-29907	45	6	413.320	413.320	NUM
fcis-29907	45	7	ellie	ellie	NOUN
fcis-29907	45	8	how	how	SCONJ
fcis-29907	45	9	have	have	AUX
fcis-29907	45	10	you	you	PRON
fcis-29907	45	11	been	be	AUX
fcis-29907	45	12	feeling	feel	VERB
fcis-29907	45	13	lately	lately	ADV
fcis-29907	45	14	?	?	PUNCT
fcis-29907	46	1	414.090	414.090	NUM
fcis-29907	46	2	417.140	417.140	NUM
fcis-29907	46	3	participant	participant	NOUN
fcis-29907	46	4	lately	lately	ADV
fcis-29907	46	5	i	i	PRON
fcis-29907	46	6	've	have	AUX
fcis-29907	46	7	been	be	AUX
fcis-29907	46	8	feeling	feel	VERB
fcis-29907	46	9	depressed	depressed	ADJ
fcis-29907	46	10	.	.	PUNCT
fcis-29907	47	1	fig	fig	NOUN
fcis-29907	47	2	1	1	NUM
fcis-29907	47	3	.	.	PUNCT
fcis-29907	47	4	self	self	NOUN
fcis-29907	47	5	-	-	PUNCT
fcis-29907	47	6	supervised	supervise	VERB
fcis-29907	47	7	extraction	extraction	NOUN
fcis-29907	47	8	of	of	ADP
fcis-29907	47	9	speech	speech	NOUN
fcis-29907	47	10	information	information	NOUN
fcis-29907	47	11	3.2	3.2	NUM
fcis-29907	47	12	.	.	PUNCT
fcis-29907	48	1	feature	feature	NOUN
fcis-29907	48	2	representation	representation	NOUN
fcis-29907	48	3	utilizing	utilize	VERB
fcis-29907	48	4	the	the	DET
fcis-29907	48	5	vq	vq	NOUN
fcis-29907	48	6	-	-	PUNCT
fcis-29907	48	7	wav2vec	wav2vec	NOUN
fcis-29907	48	8	model	model	NOUN
fcis-29907	48	9	,	,	PUNCT
fcis-29907	48	10	a	a	DET
fcis-29907	48	11	self	self	NOUN
fcis-29907	48	12	-	-	PUNCT
fcis-29907	48	13	supervised	supervise	VERB
fcis-29907	48	14	approach	approach	NOUN
fcis-29907	48	15	is	be	AUX
fcis-29907	48	16	employed	employ	VERB
fcis-29907	48	17	to	to	AUX
fcis-29907	48	18	pre	pre	VERB
fcis-29907	48	19	-	-	VERB
fcis-29907	48	20	train	train	NOUN
fcis-29907	48	21	on	on	ADP
fcis-29907	48	22	a	a	DET
fcis-29907	48	23	large	large	ADJ
fcis-29907	48	24	number	number	NOUN
fcis-29907	48	25	of	of	ADP
fcis-29907	48	26	unlabeled	unlabeled	ADJ
fcis-29907	48	27	speech	speech	NOUN
fcis-29907	48	28	segments	segment	NOUN
fcis-29907	48	29	,	,	PUNCT
fcis-29907	48	30	followed	follow	VERB
fcis-29907	48	31	by	by	ADP
fcis-29907	48	32	fine	fine	ADV
fcis-29907	48	33	-	-	PUNCT
fcis-29907	48	34	tuning	tuning	NOUN
fcis-29907	48	35	for	for	ADP
fcis-29907	48	36	emotion	emotion	NOUN
fcis-29907	48	37	classification	classification	NOUN
fcis-29907	48	38	and	and	CCONJ
fcis-29907	48	39	english	english	ADJ
fcis-29907	48	40	speech	speech	NOUN
fcis-29907	48	41	recognition	recognition	NOUN
fcis-29907	48	42	tasks	task	NOUN
fcis-29907	48	43	.	.	PUNCT
fcis-29907	49	1	the	the	DET
fcis-29907	49	2	extracted	extract	VERB
fcis-29907	49	3	embeddings	embedding	NOUN
fcis-29907	49	4	are	be	AUX
fcis-29907	49	5	subjected	subject	VERB
fcis-29907	49	6	to	to	ADP
fcis-29907	49	7	average	average	ADJ
fcis-29907	49	8	pooling	pooling	NOUN
fcis-29907	49	9	and	and	CCONJ
fcis-29907	49	10	dimensionality	dimensionality	NOUN
fcis-29907	49	11	reduction	reduction	NOUN
fcis-29907	49	12	along	along	ADP
fcis-29907	49	13	the	the	DET
fcis-29907	49	14	temporal	temporal	ADJ
fcis-29907	49	15	dimension	dimension	NOUN
fcis-29907	49	16	,	,	PUNCT
fcis-29907	49	17	and	and	CCONJ
fcis-29907	49	18	the	the	DET
fcis-29907	49	19	mean	mean	ADJ
fcis-29907	49	20	and	and	CCONJ
fcis-29907	49	21	standard	standard	ADJ
fcis-29907	49	22	deviation	deviation	NOUN
fcis-29907	49	23	of	of	ADP
fcis-29907	49	24	the	the	DET
fcis-29907	49	25	embeddings	embedding	NOUN
fcis-29907	49	26	are	be	AUX
fcis-29907	49	27	calculated	calculate	VERB
fcis-29907	49	28	.	.	PUNCT
fcis-29907	50	1	this	this	PRON
fcis-29907	50	2	leverages	leverage	VERB
fcis-29907	50	3	the	the	DET
fcis-29907	50	4	multi	multi	ADJ
fcis-29907	50	5	-	-	ADJ
fcis-29907	50	6	layer	layer	ADJ
fcis-29907	50	7	feature	feature	NOUN
fcis-29907	50	8	representation	representation	NOUN
fcis-29907	50	9	capability	capability	NOUN
fcis-29907	50	10	of	of	ADP
fcis-29907	50	11	the	the	DET
fcis-29907	50	12	self	self	NOUN
fcis-29907	50	13	-	-	PUNCT
fcis-29907	50	14	supervised	supervise	VERB
fcis-29907	50	15	pre	pre	ADJ
fcis-29907	50	16	-	-	ADJ
fcis-29907	50	17	training	training	ADJ
fcis-29907	50	18	model	model	NOUN
fcis-29907	50	19	to	to	PART
fcis-29907	50	20	distinguish	distinguish	VERB
fcis-29907	50	21	the	the	DET
fcis-29907	50	22	characteristics	characteristic	NOUN
fcis-29907	50	23	of	of	ADP
fcis-29907	50	24	depressive	depressive	ADJ
fcis-29907	50	25	state	state	NOUN
fcis-29907	50	26	speech	speech	NOUN
fcis-29907	50	27	[	[	X
fcis-29907	50	28	4	4	NUM
fcis-29907	50	29	]	]	PUNCT
fcis-29907	50	30	.	.	PUNCT
fcis-29907	51	1	3.3	3.3	NUM
fcis-29907	51	2	.	.	PUNCT
fcis-29907	52	1	hyperparameter	hyperparameter	NOUN
fcis-29907	52	2	settings	setting	NOUN
fcis-29907	52	3	during	during	ADP
fcis-29907	52	4	the	the	DET
fcis-29907	52	5	self	self	NOUN
fcis-29907	52	6	-	-	PUNCT
fcis-29907	52	7	supervised	supervise	VERB
fcis-29907	52	8	pre	pre	ADJ
fcis-29907	52	9	-	-	ADJ
fcis-29907	52	10	training	training	ADJ
fcis-29907	52	11	process	process	NOUN
fcis-29907	52	12	,	,	PUNCT
fcis-29907	52	13	the	the	DET
fcis-29907	52	14	model	model	NOUN
fcis-29907	52	15	embedding	embed	VERB
fcis-29907	52	16	dimension	dimension	NOUN
fcis-29907	52	17	n	n	VERB
fcis-29907	52	18	is	be	AUX
fcis-29907	52	19	set	set	VERB
fcis-29907	52	20	to	to	ADP
fcis-29907	52	21	1024	1024	NUM
fcis-29907	52	22	,	,	PUNCT
fcis-29907	52	23	the	the	DET
fcis-29907	52	24	self	self	NOUN
fcis-29907	52	25	-	-	PUNCT
fcis-29907	52	26	attention	attention	NOUN
fcis-29907	52	27	layer	layer	NOUN
fcis-29907	52	28	mapping	mapping	NOUN
fcis-29907	52	29	dimension	dimension	NOUN
fcis-29907	52	30	m	m	VERB
fcis-29907	52	31	is	be	AUX
fcis-29907	52	32	set	set	VERB
fcis-29907	52	33	to	to	ADP
fcis-29907	52	34	1024	1024	NUM
fcis-29907	52	35	,	,	PUNCT
fcis-29907	52	36	the	the	DET
fcis-29907	52	37	cnn	cnn	PROPN
fcis-29907	52	38	-	-	PUNCT
fcis-29907	52	39	bilstm	bilstm	NOUN
fcis-29907	52	40	mapping	mapping	NOUN
fcis-29907	52	41	dimension	dimension	NOUN
fcis-29907	52	42	ne	ne	PROPN
fcis-29907	52	43	is	be	AUX
fcis-29907	52	44	256	256	NUM
fcis-29907	52	45	,	,	PUNCT
fcis-29907	52	46	and	and	CCONJ
fcis-29907	52	47	the	the	DET
fcis-29907	52	48	number	number	NOUN
fcis-29907	52	49	of	of	ADP
fcis-29907	52	50	nodes	node	NOUN
fcis-29907	52	51	in	in	ADP
fcis-29907	52	52	the	the	DET
fcis-29907	52	53	fully	fully	ADV
fcis-29907	52	54	connected	connect	VERB
fcis-29907	52	55	layer	layer	NOUN
fcis-29907	52	56	d	d	X
fcis-29907	52	57	is	be	AUX
fcis-29907	52	58	256	256	NUM
fcis-29907	52	59	.	.	PUNCT
fcis-29907	53	1	adam	adam	PROPN
fcis-29907	53	2	optimizer	optimizer	NOUN
fcis-29907	53	3	is	be	AUX
fcis-29907	53	4	used	use	VERB
fcis-29907	53	5	for	for	ADP
fcis-29907	53	6	training	training	NOUN
fcis-29907	53	7	,	,	PUNCT
fcis-29907	53	8	with	with	ADP
fcis-29907	53	9	a	a	DET
fcis-29907	53	10	batch	batch	NOUN
fcis-29907	53	11	size	size	NOUN
fcis-29907	53	12	of	of	ADP
fcis-29907	53	13	64	64	NUM
fcis-29907	53	14	and	and	CCONJ
fcis-29907	53	15	a	a	DET
fcis-29907	53	16	maximum	maximum	NOUN
fcis-29907	53	17	of	of	ADP
fcis-29907	53	18	100	100	NUM
fcis-29907	53	19	training	training	NOUN
fcis-29907	53	20	epochs	epoch	NOUN
fcis-29907	53	21	,	,	PUNCT
fcis-29907	53	22	and	and	CCONJ
fcis-29907	53	23	an	an	DET
fcis-29907	53	24	initial	initial	ADJ
fcis-29907	53	25	learning	learning	NOUN
fcis-29907	53	26	rate	rate	NOUN
fcis-29907	53	27	of	of	ADP
fcis-29907	53	28	0.004	0.004	NUM
fcis-29907	53	29	.	.	PUNCT
fcis-29907	54	1	4	4	NUM
fcis-29907	54	2	.	.	X
fcis-29907	54	3	cnn	cnn	PROPN
fcis-29907	54	4	-	-	PUNCT
fcis-29907	54	5	bilstm	bilstm	NOUN
fcis-29907	54	6	depression	depression	NOUN
fcis-29907	54	7	state	state	NOUN
fcis-29907	54	8	detection	detection	NOUN
fcis-29907	54	9	the	the	DET
fcis-29907	54	10	lstm	lstm	NOUN
fcis-29907	54	11	module	module	NOUN
fcis-29907	54	12	mitigates	mitigate	VERB
fcis-29907	54	13	the	the	DET
fcis-29907	54	14	issues	issue	NOUN
fcis-29907	54	15	of	of	ADP
fcis-29907	54	16	vanishing	vanish	VERB
fcis-29907	54	17	and	and	CCONJ
fcis-29907	54	18	exploding	explode	VERB
fcis-29907	54	19	gradients	gradient	NOUN
fcis-29907	54	20	through	through	ADP
fcis-29907	54	21	its	its	PRON
fcis-29907	54	22	gating	gate	VERB
fcis-29907	54	23	mechanism	mechanism	NOUN
fcis-29907	54	24	,	,	PUNCT
fcis-29907	54	25	while	while	SCONJ
fcis-29907	54	26	the	the	DET
fcis-29907	54	27	cnn	cnn	NOUN
fcis-29907	54	28	-	-	PUNCT
fcis-29907	54	29	bilstm	bilstm	NOUN
fcis-29907	54	30	further	far	ADV
fcis-29907	54	31	improves	improve	VERB
fcis-29907	54	32	the	the	DET
fcis-29907	54	33	propagation	propagation	NOUN
fcis-29907	54	34	of	of	ADP
fcis-29907	54	35	gradients	gradient	NOUN
fcis-29907	54	36	by	by	ADP
fcis-29907	54	37	facilitating	facilitate	VERB
fcis-29907	54	38	information	information	NOUN
fcis-29907	54	39	flow	flow	NOUN
fcis-29907	54	40	in	in	ADP
fcis-29907	54	41	both	both	CCONJ
fcis-29907	54	42	forward	forward	ADJ
fcis-29907	54	43	and	and	CCONJ
fcis-29907	54	44	backward	backward	ADJ
fcis-29907	54	45	directions	direction	NOUN
fcis-29907	54	46	.	.	PUNCT
fcis-29907	55	1	this	this	PRON
fcis-29907	55	2	enables	enable	VERB
fcis-29907	55	3	the	the	DET
fcis-29907	55	4	model	model	NOUN
fcis-29907	55	5	to	to	PART
fcis-29907	55	6	leverage	leverage	VERB
fcis-29907	55	7	information	information	NOUN
fcis-29907	55	8	from	from	ADP
fcis-29907	55	9	both	both	PRON
fcis-29907	55	10	past	past	NOUN
fcis-29907	55	11	and	and	CCONJ
fcis-29907	55	12	future	future	ADJ
fcis-29907	55	13	contexts	context	NOUN
fcis-29907	55	14	at	at	ADP
fcis-29907	55	15	the	the	DET
fcis-29907	55	16	current	current	ADJ
fcis-29907	55	17	time	time	NOUN
fcis-29907	55	18	step	step	NOUN
fcis-29907	55	19	,	,	PUNCT
fcis-29907	55	20	thereby	thereby	ADV
fcis-29907	55	21	better	well	ADV
fcis-29907	55	22	capturing	capture	VERB
fcis-29907	55	23	long	long	ADJ
fcis-29907	55	24	-	-	PUNCT
fcis-29907	55	25	range	range	NOUN
fcis-29907	55	26	dependencies	dependency	NOUN
fcis-29907	55	27	within	within	ADP
fcis-29907	55	28	sequences	sequence	NOUN
fcis-29907	55	29	.	.	PUNCT
fcis-29907	56	1	the	the	DET
fcis-29907	56	2	proposed	propose	VERB
fcis-29907	56	3	cnn	cnn	PROPN
fcis-29907	56	4	-	-	PUNCT
fcis-29907	56	5	bilstm	bilstm	NOUN
fcis-29907	56	6	model	model	NOUN
fcis-29907	56	7	,	,	PUNCT
fcis-29907	56	8	when	when	SCONJ
fcis-29907	56	9	confronted	confront	VERB
fcis-29907	56	10	with	with	ADP
fcis-29907	56	11	noisy	noisy	ADJ
fcis-29907	56	12	or	or	CCONJ
fcis-29907	56	13	incomplete	incomplete	ADJ
fcis-29907	56	14	data	datum	NOUN
fcis-29907	56	15	,	,	PUNCT
fcis-29907	56	16	utilizes	utilize	VERB
fcis-29907	56	17	its	its	PRON
fcis-29907	56	18	longrange	longrange	NOUN
fcis-29907	56	19	dependency	dependency	NOUN
fcis-29907	56	20	and	and	CCONJ
fcis-29907	56	21	context	context	NOUN
fcis-29907	56	22	-	-	PUNCT
fcis-29907	56	23	aware	aware	ADJ
fcis-29907	56	24	capabilities	capability	NOUN
fcis-29907	56	25	to	to	PART
fcis-29907	56	26	resist	resist	VERB
fcis-29907	56	27	interference	interference	NOUN
fcis-29907	56	28	and	and	CCONJ
fcis-29907	56	29	make	make	VERB
fcis-29907	56	30	more	more	ADV
fcis-29907	56	31	accurate	accurate	ADJ
fcis-29907	56	32	predictions	prediction	NOUN
fcis-29907	56	33	by	by	ADP
fcis-29907	56	34	harnessing	harness	VERB
fcis-29907	56	35	information	information	NOUN
fcis-29907	56	36	from	from	ADP
fcis-29907	56	37	the	the	DET
fcis-29907	56	38	entire	entire	ADJ
fcis-29907	56	39	sequence	sequence	NOUN
fcis-29907	56	40	.	.	PUNCT
fcis-29907	57	1	4.1	4.1	NUM
fcis-29907	57	2	.	.	X
fcis-29907	58	1	cnn	cnn	PROPN
fcis-29907	58	2	-	-	PUNCT
fcis-29907	58	3	bilstm	bilstm	NOUN
fcis-29907	58	4	model	model	NOUN
fcis-29907	58	5	lstm	lstm	PROPN
fcis-29907	58	6	lstm	lstm	PROPN
fcis-29907	58	7	lstm	lstm	PROPN
fcis-29907	58	8	lstm	lstm	PROPN
fcis-29907	58	9	lstm	lstm	PROPN
fcis-29907	58	10	lstm	lstm	PROPN
fcis-29907	58	11	lstm	lstm	PROPN
fcis-29907	58	12	lstmcnn	lstmcnn	PROPN
fcis-29907	58	13	cnn	cnn	PROPN
fcis-29907	58	14	cnn	cnn	PROPN
fcis-29907	58	15	cnn	cnn	PROPN
fcis-29907	58	16	fig	fig	PROPN
fcis-29907	58	17	2	2	NUM
fcis-29907	58	18	.	.	PUNCT
fcis-29907	59	1	cnn	cnn	PROPN
fcis-29907	59	2	-	-	PUNCT
fcis-29907	59	3	bilstm	bilstm	NOUN
fcis-29907	59	4	structure	structure	NOUN
fcis-29907	59	5	diagram	diagram	NOUN
fcis-29907	59	6	each	each	DET
fcis-29907	59	7	lstm	lstm	PROPN
fcis-29907	59	8	unit	unit	NOUN
fcis-29907	59	9	contains	contain	VERB
fcis-29907	59	10	four	four	NUM
fcis-29907	59	11	gates	gate	NOUN
fcis-29907	59	12	(	(	PUNCT
fcis-29907	59	13	the	the	DET
fcis-29907	59	14	forget	forget	PROPN
fcis-29907	59	15	gate	gate	PROPN
fcis-29907	59	16	f	f	PROPN
fcis-29907	59	17	,	,	PUNCT
fcis-29907	59	18	the	the	DET
fcis-29907	59	19	input	input	NOUN
fcis-29907	59	20	gate	gate	NOUN
fcis-29907	59	21	i	i	PRON
fcis-29907	59	22	,	,	PUNCT
fcis-29907	59	23	the	the	DET
fcis-29907	59	24	output	output	NOUN
fcis-29907	59	25	gate	gate	NOUN
fcis-29907	59	26	o	o	PROPN
fcis-29907	59	27	and	and	CCONJ
fcis-29907	59	28	the	the	DET
fcis-29907	59	29	candidate	candidate	NOUN
fcis-29907	59	30	state	state	PROPN
fcis-29907	59	31	gate	gate	PROPN
fcis-29907	59	32	c	c	PROPN
fcis-29907	59	33	):	):	PUNCT
fcis-29907	59	34	f	f	PROPN
fcis-29907	59	35	σ	σ	PROPN
fcis-29907	59	36	w	w	PROPN
fcis-29907	59	37	⋅	⋅	PROPN
fcis-29907	59	38	h	h	NOUN
fcis-29907	59	39	,	,	PUNCT
fcis-29907	59	40	x	x	PROPN
fcis-29907	59	41	b	b	X
fcis-29907	59	42	108	108	NUM
fcis-29907	60	1	i	i	NOUN
fcis-29907	60	2	σ	σ	PROPN
fcis-29907	60	3	w	w	PROPN
fcis-29907	60	4	⋅	⋅	PROPN
fcis-29907	60	5	h	h	NOUN
fcis-29907	60	6	,	,	PUNCT
fcis-29907	60	7	x	x	PROPN
fcis-29907	60	8	b	b	X
fcis-29907	60	9	o	o	X
fcis-29907	60	10	σ	σ	PROPN
fcis-29907	60	11	w	w	PROPN
fcis-29907	60	12	⋅	⋅	PROPN
fcis-29907	60	13	h	h	NOUN
fcis-29907	60	14	,	,	PUNCT
fcis-29907	61	1	x	x	PROPN
fcis-29907	61	2	b	b	X
fcis-29907	61	3	c	c	X
fcis-29907	61	4	tanh	tanh	PROPN
fcis-29907	61	5	w	w	PROPN
fcis-29907	61	6	⋅	⋅	PROPN
fcis-29907	61	7	h	h	NOUN
fcis-29907	61	8	,	,	PUNCT
fcis-29907	61	9	x	x	PROPN
fcis-29907	61	10	b	b	X
fcis-29907	61	11	the	the	DET
fcis-29907	61	12	lstm	lstm	PROPN
fcis-29907	61	13	unit	unit	NOUN
fcis-29907	61	14	generates	generate	VERB
fcis-29907	61	15	its	its	PRON
fcis-29907	61	16	state	state	NOUN
fcis-29907	61	17	based	base	VERB
fcis-29907	61	18	on	on	ADP
fcis-29907	61	19	the	the	DET
fcis-29907	61	20	f	f	PROPN
fcis-29907	61	21	and	and	CCONJ
fcis-29907	61	22	i	i	PRON
fcis-29907	61	23	of	of	ADP
fcis-29907	61	24	the	the	DET
fcis-29907	61	25	gates	gate	NOUN
fcis-29907	61	26	:	:	PUNCT
fcis-29907	61	27	c	c	PROPN
fcis-29907	61	28	f	f	PROPN
fcis-29907	61	29	⊙	⊙	PROPN
fcis-29907	61	30	c	c	PROPN
fcis-29907	62	1	i	i	PRON
fcis-29907	62	2	⊙	⊙	VERB
fcis-29907	62	3	c	c	PROPN
fcis-29907	63	1	the	the	DET
fcis-29907	63	2	hidden	hide	VERB
fcis-29907	63	3	output	output	NOUN
fcis-29907	63	4	in	in	ADP
fcis-29907	63	5	either	either	DET
fcis-29907	63	6	direction	direction	NOUN
fcis-29907	63	7	.	.	PUNCT
fcis-29907	64	1	h	h	NOUN
fcis-29907	65	1	o	o	PROPN
fcis-29907	65	2	⊙	⊙	PROPN
fcis-29907	65	3	tanh	tanh	PROPN
fcis-29907	65	4	c	c	PROPN
fcis-29907	65	5	in	in	ADP
fcis-29907	65	6	which	which	PRON
fcis-29907	65	7	,	,	PUNCT
fcis-29907	65	8	σ	σ	PROPN
fcis-29907	65	9	represents	represent	VERB
fcis-29907	65	10	the	the	DET
fcis-29907	65	11	activation	activation	NOUN
fcis-29907	65	12	function	function	NOUN
fcis-29907	65	13	,	,	PUNCT
fcis-29907	65	14	tanh	tanh	PROPN
fcis-29907	65	15	represents	represent	VERB
fcis-29907	65	16	the	the	DET
fcis-29907	65	17	hyperbolic	hyperbolic	ADJ
fcis-29907	65	18	tangent	tangent	NOUN
fcis-29907	65	19	activation	activation	NOUN
fcis-29907	65	20	function	function	NOUN
fcis-29907	65	21	,	,	PUNCT
fcis-29907	65	22	⊙	⊙	PROPN
fcis-29907	65	23	represents	represent	VERB
fcis-29907	65	24	the	the	DET
fcis-29907	65	25	element	element	ADJ
fcis-29907	65	26	-	-	PUNCT
fcis-29907	65	27	wise	wise	ADJ
fcis-29907	65	28	product	product	NOUN
fcis-29907	65	29	,	,	PUNCT
fcis-29907	65	30	w	w	PROPN
fcis-29907	65	31	,	,	PUNCT
fcis-29907	65	32	w	w	PROPN
fcis-29907	65	33	,	,	PUNCT
fcis-29907	65	34	w	w	PROPN
fcis-29907	65	35	and	and	CCONJ
fcis-29907	65	36	w	w	PROPN
fcis-29907	65	37	are	be	AUX
fcis-29907	65	38	the	the	DET
fcis-29907	65	39	corresponding	corresponding	ADJ
fcis-29907	65	40	weight	weight	NOUN
fcis-29907	65	41	matrices	matrix	NOUN
fcis-29907	65	42	,	,	PUNCT
fcis-29907	65	43	b	b	PROPN
fcis-29907	65	44	,	,	PUNCT
fcis-29907	65	45	b	b	PROPN
fcis-29907	65	46	,	,	PUNCT
fcis-29907	65	47	b	b	PROPN
fcis-29907	65	48	and	and	CCONJ
fcis-29907	65	49	b	b	NOUN
fcis-29907	65	50	are	be	AUX
fcis-29907	65	51	the	the	DET
fcis-29907	65	52	bias	bias	NOUN
fcis-29907	65	53	terms	term	NOUN
fcis-29907	65	54	,	,	PUNCT
fcis-29907	65	55	and	and	CCONJ
fcis-29907	65	56	h	h	NOUN
fcis-29907	65	57	,	,	PUNCT
fcis-29907	65	58	x	x	X
fcis-29907	65	59	is	be	AUX
fcis-29907	65	60	the	the	DET
fcis-29907	65	61	concatenation	concatenation	NOUN
fcis-29907	65	62	of	of	ADP
fcis-29907	65	63	the	the	DET
fcis-29907	65	64	previous	previous	ADJ
fcis-29907	65	65	time	time	NOUN
fcis-29907	65	66	step	step	NOUN
fcis-29907	65	67	's	's	PART
fcis-29907	65	68	hidden	hide	VERB
fcis-29907	65	69	state	state	NOUN
fcis-29907	65	70	and	and	CCONJ
fcis-29907	65	71	the	the	DET
fcis-29907	65	72	current	current	ADJ
fcis-29907	65	73	input	input	NOUN
fcis-29907	65	74	.	.	PUNCT
fcis-29907	66	1	the	the	DET
fcis-29907	66	2	cnn	cnn	PROPN
fcis-29907	66	3	-	-	PUNCT
fcis-29907	66	4	bilstm	bilstm	NOUN
fcis-29907	66	5	model	model	NOUN
fcis-29907	66	6	comprises	comprise	VERB
fcis-29907	66	7	two	two	NUM
fcis-29907	66	8	lstm	lstm	ADJ
fcis-29907	66	9	layers	layer	NOUN
fcis-29907	66	10	,	,	PUNCT
fcis-29907	66	11	one	one	NUM
fcis-29907	66	12	for	for	ADP
fcis-29907	66	13	forward	forward	ADJ
fcis-29907	66	14	propagation	propagation	NOUN
fcis-29907	66	15	to	to	PART
fcis-29907	66	16	obtain	obtain	VERB
fcis-29907	66	17	h	h	NOUN
fcis-29907	66	18	and	and	CCONJ
fcis-29907	66	19	one	one	NUM
fcis-29907	66	20	for	for	ADP
fcis-29907	66	21	backward	backward	ADJ
fcis-29907	66	22	propagation	propagation	NOUN
fcis-29907	66	23	to	to	PART
fcis-29907	66	24	obtain	obtain	VERB
fcis-29907	66	25	hbackward	hbackward	NOUN
fcis-29907	66	26	,	,	PUNCT
fcis-29907	66	27	with	with	ADP
fcis-29907	66	28	the	the	DET
fcis-29907	66	29	information	information	NOUN
fcis-29907	66	30	from	from	ADP
fcis-29907	66	31	both	both	PRON
fcis-29907	66	32	eventually	eventually	ADV
fcis-29907	66	33	being	be	AUX
fcis-29907	66	34	merged	merge	VERB
fcis-29907	66	35	by	by	ADP
fcis-29907	66	36	subsequent	subsequent	ADJ
fcis-29907	66	37	layers	layer	NOUN
fcis-29907	66	38	or	or	CCONJ
fcis-29907	66	39	the	the	DET
fcis-29907	66	40	output	output	NOUN
fcis-29907	66	41	layer	layer	NOUN
fcis-29907	66	42	of	of	ADP
fcis-29907	66	43	the	the	DET
fcis-29907	66	44	model	model	NOUN
fcis-29907	66	45	.	.	PUNCT
fcis-29907	67	1	ultimately	ultimately	ADV
fcis-29907	67	2	,	,	PUNCT
fcis-29907	67	3	the	the	DET
fcis-29907	67	4	forward	forward	ADJ
fcis-29907	67	5	and	and	CCONJ
fcis-29907	67	6	backward	backward	ADJ
fcis-29907	67	7	hidden	hide	VERB
fcis-29907	67	8	states	state	NOUN
fcis-29907	67	9	can	can	AUX
fcis-29907	67	10	be	be	AUX
fcis-29907	67	11	concatenated	concatenate	VERB
fcis-29907	67	12	to	to	PART
fcis-29907	67	13	enhance	enhance	VERB
fcis-29907	67	14	pattern	pattern	NOUN
fcis-29907	67	15	recognition	recognition	NOUN
fcis-29907	67	16	capabilities	capability	NOUN
fcis-29907	67	17	and	and	CCONJ
fcis-29907	67	18	capture	capture	VERB
fcis-29907	67	19	richer	rich	ADJ
fcis-29907	67	20	contextual	contextual	ADJ
fcis-29907	67	21	information	information	NOUN
fcis-29907	67	22	.	.	PUNCT
fcis-29907	68	1	the	the	DET
fcis-29907	68	2	output	output	NOUN
fcis-29907	68	3	of	of	ADP
fcis-29907	68	4	the	the	DET
fcis-29907	68	5	bilstm	bilstm	NOUN
fcis-29907	68	6	at	at	ADP
fcis-29907	68	7	time	time	NOUN
fcis-29907	68	8	step	step	NOUN
fcis-29907	68	9	t	t	PROPN
fcis-29907	68	10	is	be	AUX
fcis-29907	68	11	obtained	obtain	VERB
fcis-29907	68	12	as	as	SCONJ
fcis-29907	68	13	follows	follow	VERB
fcis-29907	68	14	:	:	PUNCT
fcis-29907	68	15	h	h	NOUN
fcis-29907	68	16	h	h	NOUN
fcis-29907	68	17	,	,	PUNCT
fcis-29907	68	18	hbackward	hbackward	NOUN
fcis-29907	68	19	4.2	4.2	NUM
fcis-29907	68	20	.	.	PUNCT
fcis-29907	69	1	experimental	experimental	ADJ
fcis-29907	69	2	setup	setup	NOUN
fcis-29907	69	3	for	for	ADP
fcis-29907	69	4	the	the	DET
fcis-29907	69	5	daic	daic	ADJ
fcis-29907	69	6	dataset	dataset	NOUN
fcis-29907	69	7	,	,	PUNCT
fcis-29907	69	8	we	we	PRON
fcis-29907	69	9	employ	employ	VERB
fcis-29907	69	10	a	a	DET
fcis-29907	69	11	multi	multi	ADJ
fcis-29907	69	12	-	-	ADJ
fcis-29907	69	13	task	task	ADJ
fcis-29907	69	14	learning	learn	VERB
fcis-29907	69	15	strategy	strategy	NOUN
fcis-29907	69	16	to	to	PART
fcis-29907	69	17	output	output	VERB
fcis-29907	69	18	binary	binary	ADJ
fcis-29907	69	19	classification	classification	NOUN
fcis-29907	69	20	and	and	CCONJ
fcis-29907	69	21	phq-8	phq-8	PUNCT
fcis-29907	69	22	scores	score	NOUN
fcis-29907	69	23	.	.	PUNCT
fcis-29907	70	1	data	datum	NOUN
fcis-29907	70	2	standardization	standardization	NOUN
fcis-29907	70	3	is	be	AUX
fcis-29907	70	4	applied	apply	VERB
fcis-29907	70	5	by	by	ADP
fcis-29907	70	6	calculating	calculate	VERB
fcis-29907	70	7	the	the	DET
fcis-29907	70	8	global	global	ADJ
fcis-29907	70	9	mean	mean	NOUN
fcis-29907	70	10	and	and	CCONJ
fcis-29907	70	11	variance	variance	NOUN
fcis-29907	70	12	on	on	ADP
fcis-29907	70	13	the	the	DET
fcis-29907	70	14	training	training	NOUN
fcis-29907	70	15	set	set	NOUN
fcis-29907	70	16	and	and	CCONJ
fcis-29907	70	17	then	then	ADV
fcis-29907	70	18	using	use	VERB
fcis-29907	70	19	the	the	DET
fcis-29907	70	20	mean	mean	NOUN
fcis-29907	70	21	and	and	CCONJ
fcis-29907	70	22	variance	variance	NOUN
fcis-29907	70	23	from	from	ADP
fcis-29907	70	24	the	the	DET
fcis-29907	70	25	development	development	NOUN
fcis-29907	70	26	set	set	NOUN
fcis-29907	70	27	[	[	X
fcis-29907	70	28	5	5	NUM
fcis-29907	70	29	]	]	PUNCT
fcis-29907	70	30	.	.	PUNCT
fcis-29907	71	1	a	a	DET
fcis-29907	71	2	dropout	dropout	NOUN
fcis-29907	71	3	of	of	ADP
fcis-29907	71	4	0.1	0.1	NUM
fcis-29907	71	5	is	be	AUX
fcis-29907	71	6	taken	take	VERB
fcis-29907	71	7	after	after	ADP
fcis-29907	71	8	each	each	DET
fcis-29907	71	9	lstm	lstm	ADJ
fcis-29907	71	10	layer	layer	NOUN
fcis-29907	71	11	to	to	PART
fcis-29907	71	12	prevent	prevent	VERB
fcis-29907	71	13	overfitting	overfitting	NOUN
fcis-29907	71	14	.	.	PUNCT
fcis-29907	72	1	results	result	NOUN
fcis-29907	72	2	are	be	AUX
fcis-29907	72	3	reported	report	VERB
fcis-29907	72	4	based	base	VERB
fcis-29907	72	5	on	on	ADP
fcis-29907	72	6	the	the	DET
fcis-29907	72	7	mean	mean	ADJ
fcis-29907	72	8	absolute	absolute	ADJ
fcis-29907	72	9	error	error	NOUN
fcis-29907	72	10	(	(	PUNCT
fcis-29907	72	11	mae	mae	PROPN
fcis-29907	72	12	)	)	PUNCT
fcis-29907	72	13	and	and	CCONJ
fcis-29907	72	14	root	root	NOUN
fcis-29907	72	15	mean	mean	ADJ
fcis-29907	72	16	square	square	ADJ
fcis-29907	72	17	error	error	NOUN
fcis-29907	72	18	(	(	PUNCT
fcis-29907	72	19	rmse	rmse	NOUN
fcis-29907	72	20	)	)	PUNCT
fcis-29907	72	21	for	for	ADP
fcis-29907	72	22	regression	regression	NOUN
fcis-29907	72	23	,	,	PUNCT
fcis-29907	72	24	and	and	CCONJ
fcis-29907	72	25	macro	macro	ADJ
fcis-29907	72	26	-	-	NOUN
fcis-29907	72	27	average	average	ADJ
fcis-29907	72	28	(	(	PUNCT
fcis-29907	72	29	classification	classification	NOUN
fcis-29907	72	30	)	)	PUNCT
fcis-29907	72	31	precision	precision	NOUN
fcis-29907	72	32	,	,	PUNCT
fcis-29907	72	33	recall	recall	NOUN
fcis-29907	72	34	,	,	PUNCT
fcis-29907	72	35	and	and	CCONJ
fcis-29907	72	36	their	their	PRON
fcis-29907	72	37	harmonic	harmonic	ADJ
fcis-29907	72	38	mean	mean	NOUN
fcis-29907	72	39	(	(	PUNCT
fcis-29907	72	40	f1	f1	NOUN
fcis-29907	72	41	)	)	PUNCT
fcis-29907	72	42	scores	score	NOUN
fcis-29907	72	43	.	.	PUNCT
fcis-29907	73	1	4.3	4.3	NUM
fcis-29907	73	2	.	.	PUNCT
fcis-29907	73	3	experimental	experimental	ADJ
fcis-29907	73	4	results	result	NOUN
fcis-29907	73	5	as	as	SCONJ
fcis-29907	73	6	can	can	AUX
fcis-29907	73	7	be	be	AUX
fcis-29907	73	8	seen	see	VERB
fcis-29907	73	9	from	from	ADP
fcis-29907	73	10	the	the	DET
fcis-29907	73	11	results	result	NOUN
fcis-29907	73	12	in	in	ADP
fcis-29907	73	13	table	table	NOUN
fcis-29907	73	14	1	1	NUM
fcis-29907	73	15	,	,	PUNCT
fcis-29907	73	16	the	the	DET
fcis-29907	73	17	cnnbilstm	cnnbilstm	PROPN
fcis-29907	73	18	model	model	PROPN
fcis-29907	73	19	shows	show	VERB
fcis-29907	73	20	an	an	DET
fcis-29907	73	21	overall	overall	ADJ
fcis-29907	73	22	improvement	improvement	NOUN
fcis-29907	73	23	in	in	ADP
fcis-29907	73	24	accuracy	accuracy	NOUN
fcis-29907	73	25	(	(	PUNCT
fcis-29907	73	26	acc	acc	PROPN
fcis-29907	73	27	)	)	PUNCT
fcis-29907	73	28	,	,	PUNCT
fcis-29907	73	29	precision	precision	NOUN
fcis-29907	73	30	(	(	PUNCT
fcis-29907	73	31	pre	pre	ADJ
fcis-29907	73	32	)	)	PUNCT
fcis-29907	73	33	,	,	PUNCT
fcis-29907	73	34	recall	recall	NOUN
fcis-29907	73	35	(	(	PUNCT
fcis-29907	73	36	rec	rec	NOUN
fcis-29907	73	37	)	)	PUNCT
fcis-29907	73	38	,	,	PUNCT
fcis-29907	73	39	and	and	CCONJ
fcis-29907	73	40	f1	f1	NOUN
fcis-29907	73	41	scores	score	NOUN
fcis-29907	73	42	compared	compare	VERB
fcis-29907	73	43	to	to	ADP
fcis-29907	73	44	other	other	ADJ
fcis-29907	73	45	models	model	NOUN
fcis-29907	73	46	.	.	PUNCT
fcis-29907	74	1	this	this	PRON
fcis-29907	74	2	demonstrates	demonstrate	VERB
fcis-29907	74	3	that	that	SCONJ
fcis-29907	74	4	the	the	DET
fcis-29907	74	5	cnn	cnn	PROPN
fcis-29907	74	6	-	-	PUNCT
fcis-29907	74	7	bilstm	bilstm	NOUN
fcis-29907	74	8	model	model	NOUN
fcis-29907	74	9	has	have	VERB
fcis-29907	74	10	superior	superior	ADJ
fcis-29907	74	11	performance	performance	NOUN
fcis-29907	74	12	in	in	ADP
fcis-29907	74	13	the	the	DET
fcis-29907	74	14	analysis	analysis	NOUN
fcis-29907	74	15	of	of	ADP
fcis-29907	74	16	depressive	depressive	ADJ
fcis-29907	74	17	state	state	NOUN
fcis-29907	74	18	speech	speech	NOUN
fcis-29907	74	19	for	for	ADP
fcis-29907	74	20	long	long	ADJ
fcis-29907	74	21	sequences	sequence	NOUN
fcis-29907	74	22	compared	compare	VERB
fcis-29907	74	23	to	to	ADP
fcis-29907	74	24	other	other	ADJ
fcis-29907	74	25	models	model	NOUN
fcis-29907	74	26	.	.	PUNCT
fcis-29907	75	1	table	table	NOUN
fcis-29907	75	2	1	1	NUM
fcis-29907	75	3	.	.	PUNCT
fcis-29907	75	4	comparison	comparison	NOUN
fcis-29907	75	5	of	of	ADP
fcis-29907	75	6	results	result	NOUN
fcis-29907	75	7	without	without	ADP
fcis-29907	75	8	self	self	NOUN
fcis-29907	75	9	-	-	PUNCT
fcis-29907	75	10	supervised	supervise	VERB
fcis-29907	75	11	pre	pre	ADJ
fcis-29907	75	12	-	-	ADJ
fcis-29907	75	13	training	training	ADJ
fcis-29907	75	14	method	method	NOUN
fcis-29907	75	15	acc	acc	PROPN
fcis-29907	75	16	pre	pre	PROPN
fcis-29907	75	17	rec	rec	PROPN
fcis-29907	75	18	f1	f1	PROPN
fcis-29907	75	19	rnn	rnn	VERB
fcis-29907	75	20	0.634	0.634	NUM
fcis-29907	75	21	0.595	0.595	NUM
fcis-29907	75	22	0.654	0.654	NUM
fcis-29907	75	23	0.623	0.623	NUM
fcis-29907	75	24	gru	gru	NOUN
fcis-29907	75	25	0.703	0.703	NUM
fcis-29907	75	26	0.639	0.639	NUM
fcis-29907	75	27	0.842	0.842	NUM
fcis-29907	75	28	0.727	0.727	NUM
fcis-29907	75	29	lstm	lstm	VERB
fcis-29907	75	30	0.771	0.771	NUM
fcis-29907	75	31	0.775	0.775	NUM
fcis-29907	75	32	0.797	0.797	NUM
fcis-29907	75	33	0.786	0.786	NUM
fcis-29907	75	34	cnn	cnn	PROPN
fcis-29907	75	35	-	-	PUNCT
fcis-29907	75	36	bilstm	bilstm	NOUN
fcis-29907	75	37	0.790	0.790	NUM
fcis-29907	75	38	0.807	0.807	NUM
fcis-29907	75	39	0.815	0.815	NUM
fcis-29907	75	40	0.810	0.810	NUM
fcis-29907	75	41	the	the	DET
fcis-29907	75	42	results	result	NOUN
fcis-29907	75	43	presented	present	VERB
fcis-29907	75	44	in	in	ADP
fcis-29907	75	45	table	table	NOUN
fcis-29907	75	46	2	2	NUM
fcis-29907	75	47	indicate	indicate	VERB
fcis-29907	75	48	that	that	SCONJ
fcis-29907	75	49	after	after	ADP
fcis-29907	75	50	employing	employ	VERB
fcis-29907	75	51	the	the	DET
fcis-29907	75	52	method	method	NOUN
fcis-29907	75	53	of	of	ADP
fcis-29907	75	54	self	self	NOUN
fcis-29907	75	55	-	-	PUNCT
fcis-29907	75	56	supervised	supervise	VERB
fcis-29907	75	57	pre	pre	ADJ
fcis-29907	75	58	-	-	NOUN
fcis-29907	75	59	training	training	NOUN
fcis-29907	75	60	,	,	PUNCT
fcis-29907	75	61	there	there	PRON
fcis-29907	75	62	is	be	VERB
fcis-29907	75	63	a	a	DET
fcis-29907	75	64	noticeable	noticeable	ADJ
fcis-29907	75	65	improvement	improvement	NOUN
fcis-29907	75	66	in	in	ADP
fcis-29907	75	67	accuracy	accuracy	NOUN
fcis-29907	75	68	,	,	PUNCT
fcis-29907	75	69	precision	precision	NOUN
fcis-29907	75	70	,	,	PUNCT
fcis-29907	75	71	recall	recall	NOUN
fcis-29907	75	72	,	,	PUNCT
fcis-29907	75	73	and	and	CCONJ
fcis-29907	75	74	f1	f1	NOUN
fcis-29907	75	75	scores	score	NOUN
fcis-29907	75	76	for	for	ADP
fcis-29907	75	77	each	each	DET
fcis-29907	75	78	model	model	NOUN
fcis-29907	75	79	overall	overall	ADV
fcis-29907	75	80	.	.	PUNCT
fcis-29907	76	1	moreover	moreover	ADV
fcis-29907	76	2	,	,	PUNCT
fcis-29907	76	3	the	the	DET
fcis-29907	76	4	cnnbilstm	cnnbilstm	PROPN
fcis-29907	76	5	model	model	NOUN
fcis-29907	76	6	continues	continue	VERB
fcis-29907	76	7	to	to	PART
fcis-29907	76	8	outperform	outperform	VERB
fcis-29907	76	9	other	other	ADJ
fcis-29907	76	10	models	model	NOUN
fcis-29907	76	11	in	in	ADP
fcis-29907	76	12	terms	term	NOUN
fcis-29907	76	13	of	of	ADP
fcis-29907	76	14	overall	overall	ADJ
fcis-29907	76	15	performance	performance	NOUN
fcis-29907	76	16	.	.	PUNCT
fcis-29907	77	1	table	table	NOUN
fcis-29907	77	2	2	2	NUM
fcis-29907	77	3	.	.	PUNCT
fcis-29907	77	4	comparison	comparison	NOUN
fcis-29907	77	5	of	of	ADP
fcis-29907	77	6	results	result	NOUN
fcis-29907	77	7	using	use	VERB
fcis-29907	77	8	self	self	NOUN
fcis-29907	77	9	-	-	PUNCT
fcis-29907	77	10	supervised	supervise	VERB
fcis-29907	77	11	pre	pre	ADJ
fcis-29907	77	12	-	-	ADJ
fcis-29907	77	13	training	training	ADJ
fcis-29907	77	14	method	method	NOUN
fcis-29907	77	15	acc	acc	PROPN
fcis-29907	77	16	pre	pre	PROPN
fcis-29907	77	17	rec	rec	PROPN
fcis-29907	77	18	f1	f1	PROPN
fcis-29907	77	19	self	self	NOUN
fcis-29907	77	20	-	-	PUNCT
fcis-29907	77	21	supervised	supervise	VERB
fcis-29907	77	22	+	+	NOUN
fcis-29907	77	23	rnn	rnn	VERB
fcis-29907	77	24	0.651	0.651	NUM
fcis-29907	77	25	0.633	0.633	NUM
fcis-29907	77	26	0.654	0.654	NUM
fcis-29907	77	27	0.743	0.743	NUM
fcis-29907	77	28	self	self	NOUN
fcis-29907	77	29	-	-	PUNCT
fcis-29907	77	30	supervised	supervise	VERB
fcis-29907	77	31	+	+	NOUN
fcis-29907	77	32	gru	gru	NOUN
fcis-29907	77	33	0.752	0.752	NUM
fcis-29907	77	34	0.706	0.706	NUM
fcis-29907	77	35	0.837	0.837	NUM
fcis-29907	77	36	0.767	0.767	NUM
fcis-29907	77	37	self	self	NOUN
fcis-29907	77	38	-	-	PUNCT
fcis-29907	77	39	supervised	supervise	VERB
fcis-29907	77	40	+	+	NOUN
fcis-29907	77	41	lstm	lstm	NOUN
fcis-29907	77	42	0.806	0.806	SYM
fcis-29907	77	43	0.772	0.772	NUM
fcis-29907	77	44	0.851	0.851	NUM
fcis-29907	77	45	0.829	0.829	NUM
fcis-29907	77	46	self	self	NOUN
fcis-29907	77	47	-	-	PUNCT
fcis-29907	77	48	supervised	supervise	VERB
fcis-29907	77	49	+	+	PROPN
fcis-29907	77	50	cnn	cnn	NOUN
fcis-29907	77	51	-	-	NOUN
fcis-29907	77	52	bilstm	bilstm	NOUN
fcis-29907	77	53	0.863	0.863	NUM
fcis-29907	77	54	0.851	0.851	NUM
fcis-29907	77	55	0.868	0.868	NUM
fcis-29907	77	56	0.860	0.860	NUM
fcis-29907	77	57	the	the	DET
fcis-29907	77	58	results	result	NOUN
fcis-29907	77	59	in	in	ADP
fcis-29907	77	60	table	table	NOUN
fcis-29907	77	61	3	3	NUM
fcis-29907	77	62	indicate	indicate	VERB
fcis-29907	77	63	an	an	DET
fcis-29907	77	64	overall	overall	ADJ
fcis-29907	77	65	trend	trend	NOUN
fcis-29907	77	66	:	:	PUNCT
fcis-29907	77	67	all	all	DET
fcis-29907	77	68	models	model	NOUN
fcis-29907	77	69	perform	perform	VERB
fcis-29907	77	70	slightly	slightly	ADV
fcis-29907	77	71	better	well	ADV
fcis-29907	77	72	on	on	ADP
fcis-29907	77	73	female	female	ADJ
fcis-29907	77	74	samples	sample	NOUN
fcis-29907	77	75	than	than	ADP
fcis-29907	77	76	on	on	ADP
fcis-29907	77	77	male	male	ADJ
fcis-29907	77	78	samples	sample	NOUN
fcis-29907	77	79	.	.	PUNCT
fcis-29907	78	1	as	as	SCONJ
fcis-29907	78	2	the	the	DET
fcis-29907	78	3	complexity	complexity	NOUN
fcis-29907	78	4	of	of	ADP
fcis-29907	78	5	the	the	DET
fcis-29907	78	6	models	model	NOUN
fcis-29907	78	7	increases	increase	VERB
fcis-29907	78	8	(	(	PUNCT
fcis-29907	78	9	from	from	ADP
fcis-29907	78	10	rnn	rnn	PROPN
fcis-29907	78	11	to	to	ADP
fcis-29907	78	12	cnn	cnn	PROPN
fcis-29907	78	13	-	-	PUNCT
fcis-29907	78	14	bilstm	bilstm	NOUN
fcis-29907	78	15	)	)	PUNCT
fcis-29907	78	16	,	,	PUNCT
fcis-29907	78	17	the	the	DET
fcis-29907	78	18	performance	performance	NOUN
fcis-29907	78	19	difference	difference	NOUN
fcis-29907	78	20	between	between	ADP
fcis-29907	78	21	genders	gender	NOUN
fcis-29907	78	22	appears	appear	VERB
fcis-29907	78	23	to	to	PART
fcis-29907	78	24	decrease	decrease	VERB
fcis-29907	78	25	.	.	PUNCT
fcis-29907	79	1	model	model	NOUN
fcis-29907	79	2	-	-	PUNCT
fcis-29907	79	3	specific	specific	ADJ
fcis-29907	79	4	analysis	analysis	NOUN
fcis-29907	79	5	:	:	PUNCT
fcis-29907	79	6	rnn	rnn	NOUN
fcis-29907	79	7	:	:	PUNCT
fcis-29907	79	8	performs	perform	VERB
fcis-29907	79	9	significantly	significantly	ADV
fcis-29907	79	10	better	well	ADV
fcis-29907	79	11	on	on	ADP
fcis-29907	79	12	female	female	ADJ
fcis-29907	79	13	samples	sample	NOUN
fcis-29907	79	14	than	than	ADP
fcis-29907	79	15	on	on	ADP
fcis-29907	79	16	male	male	ADJ
fcis-29907	79	17	samples	sample	NOUN
fcis-29907	79	18	,	,	PUNCT
fcis-29907	79	19	with	with	ADP
fcis-29907	79	20	the	the	DET
fcis-29907	79	21	largest	large	ADJ
fcis-29907	79	22	performance	performance	NOUN
fcis-29907	79	23	difference	difference	NOUN
fcis-29907	79	24	.	.	PUNCT
fcis-29907	80	1	gru	gru	PROPN
fcis-29907	80	2	:	:	PUNCT
fcis-29907	80	3	the	the	DET
fcis-29907	80	4	gender	gender	NOUN
fcis-29907	80	5	difference	difference	NOUN
fcis-29907	80	6	remains	remain	VERB
fcis-29907	80	7	noticeable	noticeable	ADJ
fcis-29907	80	8	but	but	CCONJ
fcis-29907	80	9	is	be	AUX
fcis-29907	80	10	reduced	reduce	VERB
fcis-29907	80	11	compared	compare	VERB
fcis-29907	80	12	to	to	ADP
fcis-29907	80	13	the	the	DET
fcis-29907	80	14	rnn.lstm	rnn.lstm	NOUN
fcis-29907	80	15	:	:	PUNCT
fcis-29907	80	16	the	the	DET
fcis-29907	80	17	performance	performance	NOUN
fcis-29907	80	18	difference	difference	NOUN
fcis-29907	80	19	between	between	ADP
fcis-29907	80	20	genders	gender	NOUN
fcis-29907	80	21	is	be	AUX
fcis-29907	80	22	further	far	ADV
fcis-29907	80	23	reduced	reduce	VERB
fcis-29907	80	24	.	.	PUNCT
fcis-29907	81	1	cnn	cnn	PROPN
fcis-29907	81	2	-	-	PUNCT
fcis-29907	81	3	bilstm	bilstm	NOUN
fcis-29907	81	4	:	:	PUNCT
fcis-29907	81	5	shows	show	VERB
fcis-29907	81	6	the	the	DET
fcis-29907	81	7	smallest	small	ADJ
fcis-29907	81	8	gender	gender	NOUN
fcis-29907	81	9	difference	difference	NOUN
fcis-29907	81	10	,	,	PUNCT
fcis-29907	81	11	indicating	indicate	VERB
fcis-29907	81	12	that	that	SCONJ
fcis-29907	81	13	this	this	DET
fcis-29907	81	14	model	model	NOUN
fcis-29907	81	15	is	be	AUX
fcis-29907	81	16	more	more	ADV
fcis-29907	81	17	stable	stable	ADJ
fcis-29907	81	18	in	in	ADP
fcis-29907	81	19	processing	processing	NOUN
fcis-29907	81	20	speech	speech	NOUN
fcis-29907	81	21	features	feature	NOUN
fcis-29907	81	22	of	of	ADP
fcis-29907	81	23	different	different	ADJ
fcis-29907	81	24	genders	gender	NOUN
fcis-29907	81	25	.	.	PUNCT
fcis-29907	82	1	selfsupervised	selfsupervise	VERB
fcis-29907	82	2	pre	pre	ADJ
fcis-29907	82	3	-	-	NOUN
fcis-29907	82	4	training	training	ADJ
fcis-29907	82	5	+	+	CCONJ
fcis-29907	82	6	cnn	cnn	PROPN
fcis-29907	82	7	-	-	NOUN
fcis-29907	82	8	bilstm	bilstm	NOUN
fcis-29907	82	9	:	:	PUNCT
fcis-29907	82	10	although	although	SCONJ
fcis-29907	82	11	there	there	PRON
fcis-29907	82	12	is	be	VERB
fcis-29907	82	13	still	still	ADV
fcis-29907	82	14	a	a	DET
fcis-29907	82	15	slight	slight	ADJ
fcis-29907	82	16	gender	gender	NOUN
fcis-29907	82	17	difference	difference	NOUN
fcis-29907	82	18	,	,	PUNCT
fcis-29907	82	19	it	it	PRON
fcis-29907	82	20	is	be	AUX
fcis-29907	82	21	very	very	ADV
fcis-29907	82	22	small	small	ADJ
fcis-29907	82	23	compared	compare	VERB
fcis-29907	82	24	to	to	ADP
fcis-29907	82	25	other	other	ADJ
fcis-29907	82	26	models	model	NOUN
fcis-29907	82	27	.	.	PUNCT
fcis-29907	83	1	the	the	DET
fcis-29907	83	2	slightly	slightly	ADV
fcis-29907	83	3	better	well	ADJ
fcis-29907	83	4	performance	performance	NOUN
fcis-29907	83	5	on	on	ADP
fcis-29907	83	6	female	female	ADJ
fcis-29907	83	7	samples	sample	NOUN
fcis-29907	83	8	in	in	ADP
fcis-29907	83	9	the	the	DET
fcis-29907	83	10	experimental	experimental	ADJ
fcis-29907	83	11	results	result	NOUN
fcis-29907	83	12	of	of	ADP
fcis-29907	83	13	table	table	NOUN
fcis-29907	83	14	3	3	NUM
fcis-29907	83	15	may	may	AUX
fcis-29907	83	16	be	be	AUX
fcis-29907	83	17	related	relate	VERB
fcis-29907	83	18	to	to	ADP
fcis-29907	83	19	the	the	DET
fcis-29907	83	20	fact	fact	NOUN
fcis-29907	83	21	that	that	SCONJ
fcis-29907	83	22	females	female	NOUN
fcis-29907	83	23	are	be	AUX
fcis-29907	83	24	more	more	ADV
fcis-29907	83	25	likely	likely	ADJ
fcis-29907	83	26	to	to	PART
fcis-29907	83	27	express	express	VERB
fcis-29907	83	28	emotions	emotion	NOUN
fcis-29907	83	29	,	,	PUNCT
fcis-29907	83	30	making	make	VERB
fcis-29907	83	31	speech	speech	NOUN
fcis-29907	83	32	features	feature	VERB
fcis-29907	83	33	more	more	ADV
fcis-29907	83	34	pronounced	pronounced	ADJ
fcis-29907	83	35	.	.	PUNCT
fcis-29907	84	1	complex	complex	ADJ
fcis-29907	84	2	models	model	NOUN
fcis-29907	84	3	(	(	PUNCT
fcis-29907	84	4	such	such	ADJ
fcis-29907	84	5	as	as	ADP
fcis-29907	84	6	cnn	cnn	PROPN
fcis-29907	84	7	-	-	PUNCT
fcis-29907	84	8	bilstm	bilstm	NOUN
fcis-29907	84	9	)	)	PUNCT
fcis-29907	84	10	may	may	AUX
fcis-29907	84	11	be	be	AUX
fcis-29907	84	12	better	well	ADJ
fcis-29907	84	13	at	at	ADP
fcis-29907	84	14	capturing	capture	VERB
fcis-29907	84	15	speech	speech	NOUN
fcis-29907	84	16	features	feature	NOUN
fcis-29907	84	17	of	of	ADP
fcis-29907	84	18	different	different	ADJ
fcis-29907	84	19	genders	gender	NOUN
fcis-29907	84	20	,	,	PUNCT
fcis-29907	84	21	thus	thus	ADV
fcis-29907	84	22	resulting	result	VERB
fcis-29907	84	23	in	in	ADP
fcis-29907	84	24	smaller	small	ADJ
fcis-29907	84	25	performance	performance	NOUN
fcis-29907	84	26	differences	difference	NOUN
fcis-29907	84	27	.	.	PUNCT
fcis-29907	85	1	self	self	NOUN
fcis-29907	85	2	-	-	PUNCT
fcis-29907	85	3	supervised	supervise	VERB
fcis-29907	85	4	pre	pre	ADJ
fcis-29907	85	5	-	-	ADJ
fcis-29907	85	6	training	training	ADJ
fcis-29907	85	7	further	far	ADV
fcis-29907	85	8	reduces	reduce	VERB
fcis-29907	85	9	gender	gender	NOUN
fcis-29907	85	10	differences	difference	NOUN
fcis-29907	85	11	,	,	PUNCT
fcis-29907	85	12	possibly	possibly	ADV
fcis-29907	85	13	because	because	SCONJ
fcis-29907	85	14	it	it	PRON
fcis-29907	85	15	can	can	AUX
fcis-29907	85	16	learn	learn	VERB
fcis-29907	85	17	more	more	ADJ
fcis-29907	85	18	universal	universal	ADJ
fcis-29907	85	19	speech	speech	NOUN
fcis-29907	85	20	feature	feature	NOUN
fcis-29907	85	21	representations	representation	NOUN
fcis-29907	85	22	.	.	PUNCT
fcis-29907	86	1	109	109	NUM
fcis-29907	86	2	table	table	NOUN
fcis-29907	86	3	3	3	NUM
fcis-29907	86	4	.	.	PUNCT
fcis-29907	86	5	comparison	comparison	NOUN
fcis-29907	86	6	of	of	ADP
fcis-29907	86	7	training	training	NOUN
fcis-29907	86	8	results	result	NOUN
fcis-29907	86	9	by	by	ADP
fcis-29907	86	10	gender	gender	NOUN
fcis-29907	86	11	grouping	grouping	NOUN
fcis-29907	86	12	method	method	NOUN
fcis-29907	86	13	gender	gender	NOUN
fcis-29907	86	14	acc	acc	PROPN
fcis-29907	86	15	pre	pre	PROPN
fcis-29907	86	16	rec	rec	PROPN
fcis-29907	86	17	f1	f1	PROPN
fcis-29907	86	18	rnn	rnn	VERB
fcis-29907	86	19	male	male	NOUN
fcis-29907	86	20	0.620	0.620	NUM
fcis-29907	86	21	0.585	0.585	NUM
fcis-29907	86	22	0.640	0.640	NUM
fcis-29907	86	23	0.611	0.611	NUM
fcis-29907	86	24	female	female	NOUN
fcis-29907	86	25	0.648	0.648	NUM
fcis-29907	86	26	0.605	0.605	NUM
fcis-29907	86	27	0.668	0.668	NUM
fcis-29907	86	28	0.635	0.635	NUM
fcis-29907	86	29	gru	gru	NOUN
fcis-29907	86	30	male	male	NOUN
fcis-29907	86	31	0.695	0.695	NUM
fcis-29907	86	32	0.630	0.630	NUM
fcis-29907	86	33	0.835	0.835	NUM
fcis-29907	86	34	0.718	0.718	NUM
fcis-29907	86	35	female	female	ADJ
fcis-29907	86	36	0.711	0.711	NUM
fcis-29907	86	37	0.648	0.648	NUM
fcis-29907	86	38	0.849	0.849	NUM
fcis-29907	86	39	0.736	0.736	NUM
fcis-29907	86	40	lstm	lstm	ADJ
fcis-29907	86	41	male	male	NOUN
fcis-29907	86	42	0.763	0.763	NUM
fcis-29907	86	43	0.768	0.768	NUM
fcis-29907	86	44	0.790	0.790	NUM
fcis-29907	86	45	0.779	0.779	NUM
fcis-29907	86	46	female	female	ADJ
fcis-29907	86	47	0.779	0.779	NUM
fcis-29907	86	48	0.782	0.782	NUM
fcis-29907	86	49	0.804	0.804	NUM
fcis-29907	86	50	0.793	0.793	NUM
fcis-29907	86	51	cnn	cnn	PROPN
fcis-29907	86	52	-	-	PUNCT
fcis-29907	86	53	bilstm	bilstm	NOUN
fcis-29907	86	54	male	male	NOUN
fcis-29907	86	55	0.782	0.782	NUM
fcis-29907	86	56	0.800	0.800	NUM
fcis-29907	86	57	0.808	0.808	NUM
fcis-29907	86	58	0.804	0.804	NUM
fcis-29907	86	59	female	female	NOUN
fcis-29907	87	1	0.798	0.798	NUM
fcis-29907	87	2	0.814	0.814	NUM
fcis-29907	87	3	0.822	0.822	NUM
fcis-29907	87	4	0.818	0.818	NUM
fcis-29907	87	5	self	self	NOUN
fcis-29907	87	6	-	-	PUNCT
fcis-29907	87	7	supervised	supervise	VERB
fcis-29907	87	8	+	+	PROPN
fcis-29907	87	9	cnn	cnn	ADJ
fcis-29907	87	10	-	-	PUNCT
fcis-29907	87	11	bilstm	bilstm	NOUN
fcis-29907	87	12	male	male	NOUN
fcis-29907	87	13	0.855	0.855	NUM
fcis-29907	87	14	0.844	0.844	NUM
fcis-29907	87	15	0.861	0.861	NUM
fcis-29907	87	16	0.852	0.852	NUM
fcis-29907	87	17	female	female	ADJ
fcis-29907	87	18	0.871	0.871	NUM
fcis-29907	87	19	0.858	0.858	NUM
fcis-29907	87	20	0.875	0.875	NUM
fcis-29907	87	21	0.866	0.866	NUM
fcis-29907	87	22	5	5	NUM
fcis-29907	87	23	.	.	PUNCT
fcis-29907	88	1	summary	summary	NOUN
fcis-29907	88	2	this	this	DET
fcis-29907	88	3	paper	paper	NOUN
fcis-29907	88	4	proposes	propose	VERB
fcis-29907	88	5	an	an	DET
fcis-29907	88	6	audio	audio	NOUN
fcis-29907	88	7	embedding	embed	VERB
fcis-29907	88	8	pre	pre	ADJ
fcis-29907	88	9	-	-	ADJ
fcis-29907	88	10	training	training	ADJ
fcis-29907	88	11	method	method	NOUN
fcis-29907	88	12	for	for	ADP
fcis-29907	88	13	the	the	DET
fcis-29907	88	14	automatic	automatic	ADJ
fcis-29907	88	15	detection	detection	NOUN
fcis-29907	88	16	of	of	ADP
fcis-29907	88	17	depression	depression	NOUN
fcis-29907	88	18	.	.	PUNCT
fcis-29907	89	1	features	feature	NOUN
fcis-29907	89	2	are	be	AUX
fcis-29907	89	3	extracted	extract	VERB
fcis-29907	89	4	using	use	VERB
fcis-29907	89	5	a	a	DET
fcis-29907	89	6	self	self	NOUN
fcis-29907	89	7	-	-	PUNCT
fcis-29907	89	8	supervised	supervise	VERB
fcis-29907	89	9	pre	pre	ADJ
fcis-29907	89	10	-	-	ADJ
fcis-29907	89	11	training	training	ADJ
fcis-29907	89	12	approach	approach	NOUN
fcis-29907	89	13	and	and	CCONJ
fcis-29907	89	14	then	then	ADV
fcis-29907	89	15	input	input	VERB
fcis-29907	89	16	into	into	ADP
fcis-29907	89	17	a	a	DET
fcis-29907	89	18	cnn	cnn	PROPN
fcis-29907	89	19	-	-	PUNCT
fcis-29907	89	20	bilstm	bilstm	NOUN
fcis-29907	89	21	network	network	NOUN
fcis-29907	89	22	for	for	ADP
fcis-29907	89	23	depressive	depressive	ADJ
fcis-29907	89	24	state	state	NOUN
fcis-29907	89	25	detection	detection	NOUN
fcis-29907	89	26	.	.	PUNCT
fcis-29907	90	1	data	datum	NOUN
fcis-29907	90	2	pre	pre	VERB
fcis-29907	90	3	-	-	VERB
fcis-29907	90	4	trained	train	VERB
fcis-29907	90	5	on	on	ADP
fcis-29907	90	6	the	the	DET
fcis-29907	90	7	daic	daic	ADJ
fcis-29907	90	8	dataset	dataset	NOUN
fcis-29907	90	9	demonstrate	demonstrate	NOUN
fcis-29907	90	10	that	that	SCONJ
fcis-29907	90	11	the	the	DET
fcis-29907	90	12	results	result	NOUN
fcis-29907	90	13	from	from	ADP
fcis-29907	90	14	the	the	DET
fcis-29907	90	15	cnn	cnn	PROPN
fcis-29907	90	16	-	-	PUNCT
fcis-29907	90	17	bilstm	bilstm	NOUN
fcis-29907	90	18	network	network	NOUN
fcis-29907	90	19	with	with	ADP
fcis-29907	90	20	self	self	NOUN
fcis-29907	90	21	-	-	PUNCT
fcis-29907	90	22	supervised	supervise	VERB
fcis-29907	90	23	embedding	embed	VERB
fcis-29907	90	24	pre	pre	ADJ
fcis-29907	90	25	-	-	NOUN
fcis-29907	90	26	training	training	NOUN
fcis-29907	90	27	are	be	AUX
fcis-29907	90	28	significantly	significantly	ADV
fcis-29907	90	29	better	well	ADV
fcis-29907	90	30	compared	compare	VERB
fcis-29907	90	31	to	to	ADP
fcis-29907	90	32	those	those	PRON
fcis-29907	90	33	without	without	ADP
fcis-29907	90	34	self	self	NOUN
fcis-29907	90	35	-	-	PUNCT
fcis-29907	90	36	supervised	supervise	VERB
fcis-29907	90	37	pre	pre	ADJ
fcis-29907	90	38	-	-	NOUN
fcis-29907	90	39	training	training	NOUN
fcis-29907	90	40	and	and	CCONJ
fcis-29907	90	41	other	other	ADJ
fcis-29907	90	42	methods	method	NOUN
fcis-29907	90	43	that	that	PRON
fcis-29907	90	44	do	do	AUX
fcis-29907	90	45	not	not	PART
fcis-29907	90	46	employ	employ	VERB
fcis-29907	90	47	this	this	DET
fcis-29907	90	48	technique	technique	NOUN
fcis-29907	90	49	.	.	PUNCT
fcis-29907	91	1	for	for	ADP
fcis-29907	91	2	similar	similar	ADJ
fcis-29907	91	3	tasks	task	NOUN
fcis-29907	91	4	that	that	PRON
fcis-29907	91	5	require	require	VERB
fcis-29907	91	6	summarizing	summarize	VERB
fcis-29907	91	7	long	long	ADJ
fcis-29907	91	8	sequences	sequence	NOUN
fcis-29907	91	9	into	into	ADP
fcis-29907	91	10	a	a	DET
fcis-29907	91	11	given	give	VERB
fcis-29907	91	12	single	single	ADJ
fcis-29907	91	13	output	output	NOUN
fcis-29907	91	14	label	label	NOUN
fcis-29907	91	15	,	,	PUNCT
fcis-29907	91	16	such	such	ADJ
fcis-29907	91	17	as	as	ADP
fcis-29907	91	18	most	most	ADJ
fcis-29907	91	19	medical	medical	ADJ
fcis-29907	91	20	speech	speech	NOUN
fcis-29907	91	21	tasks	task	NOUN
fcis-29907	91	22	,	,	PUNCT
fcis-29907	91	23	the	the	DET
fcis-29907	91	24	use	use	NOUN
fcis-29907	91	25	of	of	ADP
fcis-29907	91	26	a	a	DET
fcis-29907	91	27	cnn	cnn	PROPN
fcis-29907	91	28	-	-	PUNCT
fcis-29907	91	29	bilstm	bilstm	NOUN
fcis-29907	91	30	model	model	NOUN
fcis-29907	91	31	with	with	ADP
fcis-29907	91	32	self	self	NOUN
fcis-29907	91	33	-	-	PUNCT
fcis-29907	91	34	supervised	supervise	VERB
fcis-29907	91	35	pretraining	pretraine	VERB
fcis-29907	91	36	can	can	AUX
fcis-29907	91	37	be	be	AUX
fcis-29907	91	38	a	a	DET
fcis-29907	91	39	universal	universal	ADJ
fcis-29907	91	40	method	method	NOUN
fcis-29907	91	41	.	.	PUNCT
fcis-29907	92	1	acknowledgments	acknowledgment	NOUN
fcis-29907	92	2	talents	talent	NOUN
fcis-29907	92	3	'	'	PART
fcis-29907	92	4	plan	plan	PROPN
fcis-29907	92	5	foundation	foundation	PROPN
fcis-29907	92	6	of	of	ADP
fcis-29907	92	7	guangdong	guangdong	PROPN
fcis-29907	92	8	second	second	PROPN
fcis-29907	92	9	provincial	provincial	ADJ
fcis-29907	92	10	general	general	ADJ
fcis-29907	92	11	hospital	hospital	NOUN
fcis-29907	92	12	(	(	PUNCT
fcis-29907	92	13	2024c003	2024c003	NUM
fcis-29907	92	14	)	)	PUNCT
fcis-29907	92	15	science	science	NOUN
fcis-29907	92	16	and	and	CCONJ
fcis-29907	92	17	technology	technology	NOUN
fcis-29907	92	18	project	project	NOUN
fcis-29907	92	19	(	(	PUNCT
fcis-29907	92	20	no	no	NOUN
fcis-29907	92	21	.	.	NOUN
fcis-29907	92	22	202102010115	202102010115	NUM
fcis-29907	92	23	)	)	PUNCT
fcis-29907	92	24	guangdong	guangdong	PROPN
fcis-29907	92	25	yiyang	yiyang	PROPN
fcis-29907	92	26	healthcare	healthcare	PROPN
fcis-29907	92	27	charity	charity	PROPN
fcis-29907	92	28	foundation	foundation	PROPN
fcis-29907	92	29	(	(	PUNCT
fcis-29907	92	30	no	no	INTJ
fcis-29907	92	31	.	.	PUNCT
fcis-29907	93	1	jz2022001	jz2022001	PROPN
fcis-29907	93	2	-	-	PUNCT
fcis-29907	93	3	3	3	NUM
fcis-29907	93	4	)	)	PUNCT
fcis-29907	93	5	references	reference	NOUN
fcis-29907	93	6	[	[	X
fcis-29907	93	7	1	1	NUM
fcis-29907	93	8	]	]	X
fcis-29907	93	9	niizumi	niizumi	PROPN
fcis-29907	93	10	d	d	PROPN
fcis-29907	93	11	,	,	PUNCT
fcis-29907	93	12	takeuchi	takeuchi	PROPN
fcis-29907	93	13	d	d	PROPN
fcis-29907	93	14	,	,	PUNCT
fcis-29907	93	15	ohishi	ohishi	VERB
fcis-29907	93	16	y	y	PROPN
fcis-29907	93	17	,	,	PUNCT
fcis-29907	93	18	et	et	PROPN
fcis-29907	94	1	al	al	PROPN
fcis-29907	94	2	.	.	PUNCT
fcis-29907	94	3	byol	byol	NOUN
fcis-29907	94	4	for	for	ADP
fcis-29907	94	5	audio	audio	NOUN
fcis-29907	94	6	:	:	PUNCT
fcis-29907	94	7	selfsupervised	selfsupervise	VERB
fcis-29907	94	8	learning	learning	NOUN
fcis-29907	94	9	for	for	ADP
fcis-29907	94	10	general	general	ADJ
fcis-29907	94	11	-	-	PUNCT
fcis-29907	94	12	purpose	purpose	NOUN
fcis-29907	94	13	audio	audio	NOUN
fcis-29907	94	14	representation	representation	NOUN
fcis-29907	94	15	[	[	X
fcis-29907	94	16	conference	conference	NOUN
fcis-29907	94	17	proceedings	proceeding	NOUN
fcis-29907	94	18	]	]	PUNCT
fcis-29907	94	19	//	//	SYM
fcis-29907	94	20	2021	2021	NUM
fcis-29907	94	21	international	international	ADJ
fcis-29907	94	22	joint	joint	ADJ
fcis-29907	94	23	conference	conference	NOUN
fcis-29907	94	24	on	on	ADP
fcis-29907	94	25	neural	neural	ADJ
fcis-29907	94	26	networks	network	NOUN
fcis-29907	94	27	(	(	PUNCT
fcis-29907	94	28	ijcnn	ijcnn	PROPN
fcis-29907	94	29	)	)	PUNCT
fcis-29907	94	30	.	.	PUNCT
fcis-29907	95	1	2021	2021	NUM
fcis-29907	96	1	[	[	X
fcis-29907	96	2	accessed	access	VERB
fcis-29907	96	3	2022	2022	NUM
fcis-29907	96	4	-	-	SYM
fcis-29907	96	5	01	01	NUM
fcis-29907	96	6	-	-	PUNCT
fcis-29907	96	7	07	07	NUM
fcis-29907	96	8	]	]	PUNCT
fcis-29907	96	9	.	.	PUNCT
fcis-29907	97	1	doi:10	doi:10	PROPN
fcis-29907	97	2	.	.	PUNCT
fcis-29907	98	1	1109/	1109/	NUM
fcis-29907	99	1	ijcnn52387.2021.9534474	ijcnn52387.2021.9534474	NOUN
fcis-29907	99	2	.	.	PUNCT
fcis-29907	100	1	[	[	X
fcis-29907	100	2	2	2	NUM
fcis-29907	100	3	]	]	X
fcis-29907	100	4	zhang	zhang	PROPN
fcis-29907	100	5	p	p	X
fcis-29907	100	6	,	,	PUNCT
fcis-29907	100	7	wu	wu	PROPN
fcis-29907	100	8	m	m	PROPN
fcis-29907	100	9	,	,	PUNCT
fcis-29907	100	10	dinkel	dinkel	PROPN
fcis-29907	100	11	h	h	PROPN
fcis-29907	100	12	,	,	PUNCT
fcis-29907	100	13	et	et	PROPN
fcis-29907	100	14	al	al	PROPN
fcis-29907	100	15	.	.	PROPN
fcis-29907	100	16	depa	depa	PROPN
fcis-29907	100	17	:	:	PUNCT
fcis-29907	100	18	self	self	NOUN
fcis-29907	100	19	-	-	PUNCT
fcis-29907	100	20	supervised	supervise	VERB
fcis-29907	100	21	audio	audio	NOUN
fcis-29907	100	22	embedding	embed	VERB
fcis-29907	100	23	for	for	ADP
fcis-29907	100	24	depression	depression	NOUN
fcis-29907	100	25	detection	detection	NOUN
fcis-29907	100	26	[	[	X
fcis-29907	100	27	conference	conference	NOUN
fcis-29907	100	28	proceedings	proceeding	NOUN
fcis-29907	100	29	]	]	PUNCT
fcis-29907	101	1	//	//	NUM
fcis-29907	101	2	proceedings	proceeding	NOUN
fcis-29907	101	3	of	of	ADP
fcis-29907	101	4	the	the	DET
fcis-29907	101	5	29th	29th	ADJ
fcis-29907	101	6	acm	acm	PROPN
fcis-29907	101	7	international	international	ADJ
fcis-29907	101	8	conference	conference	NOUN
fcis-29907	101	9	on	on	ADP
fcis-29907	101	10	multimedia	multimedia	NOUN
fcis-29907	101	11	,	,	PUNCT
fcis-29907	101	12	mm	mm	PROPN
fcis-29907	101	13	2021	2021	NUM
fcis-29907	101	14	.	.	PUNCT
fcis-29907	102	1	2021	2021	NUM
fcis-29907	102	2	:	:	PUNCT
fcis-29907	103	1	135143	135143	NUM
fcis-29907	103	2	[	[	X
fcis-29907	103	3	accessed	access	VERB
fcis-29907	103	4	2021	2021	NUM
fcis-29907	103	5	-	-	SYM
fcis-29907	103	6	01	01	NUM
fcis-29907	103	7	-	-	PUNCT
fcis-29907	103	8	01	01	NUM
fcis-29907	103	9	]	]	PUNCT
fcis-29907	103	10	.	.	PUNCT
fcis-29907	104	1	doi:10.1145/3474085.3479236	doi:10.1145/3474085.3479236	PROPN
fcis-29907	104	2	.	.	PUNCT
fcis-29907	105	1	[	[	X
fcis-29907	105	2	3	3	X
fcis-29907	105	3	]	]	X
fcis-29907	105	4	sun	sun	PROPN
fcis-29907	105	5	l	l	PROPN
fcis-29907	105	6	,	,	PUNCT
fcis-29907	105	7	lian	lian	PROPN
fcis-29907	105	8	z	z	NOUN
fcis-29907	105	9	,	,	PUNCT
fcis-29907	105	10	liu	liu	PROPN
fcis-29907	105	11	b	b	PROPN
fcis-29907	105	12	,	,	PUNCT
fcis-29907	105	13	et	et	PROPN
fcis-29907	105	14	al	al	PROPN
fcis-29907	105	15	.	.	PROPN
fcis-29907	105	16	hicmae	hicmae	PROPN
fcis-29907	105	17	:	:	PUNCT
fcis-29907	105	18	hierarchical	hierarchical	ADJ
fcis-29907	105	19	contrastive	contrastive	ADJ
fcis-29907	105	20	masked	mask	VERB
fcis-29907	105	21	autoencoder	autoencoder	NOUN
fcis-29907	105	22	for	for	ADP
fcis-29907	105	23	self	self	NOUN
fcis-29907	105	24	-	-	PUNCT
fcis-29907	105	25	supervised	supervise	VERB
fcis-29907	105	26	audio	audio	ADJ
fcis-29907	105	27	-	-	ADJ
fcis-29907	105	28	visual	visual	ADJ
fcis-29907	105	29	emotion	emotion	NOUN
fcis-29907	105	30	recognition	recognition	NOUN
fcis-29907	105	31	[	[	X
fcis-29907	105	32	journal	journal	NOUN
fcis-29907	105	33	article	article	PROPN
fcis-29907	105	34	]	]	PUNCT
fcis-29907	105	35	//	//	PUNCT
fcis-29907	105	36	information	information	NOUN
fcis-29907	105	37	fusion	fusion	NOUN
fcis-29907	105	38	,	,	PUNCT
fcis-29907	105	39	2024	2024	NUM
fcis-29907	105	40	,	,	PUNCT
fcis-29907	105	41	108	108	NUM
fcis-29907	105	42	[	[	X
fcis-29907	105	43	accessed	access	VERB
fcis-29907	105	44	2024	2024	NUM
fcis-29907	105	45	-	-	SYM
fcis-29907	105	46	05	05	NUM
fcis-29907	105	47	-	-	SYM
fcis-29907	105	48	20	20	NUM
fcis-29907	105	49	]	]	PUNCT
fcis-29907	105	50	.	.	PUNCT
fcis-29907	106	1	doi	doi	NOUN
fcis-29907	106	2	:	:	PUNCT
fcis-29907	106	3	10.1016	10.1016	NUM
fcis-29907	106	4	/	/	SYM
fcis-29907	106	5	j.	j.	PROPN
fcis-29907	106	6	inffus	inffus	PROPN
fcis-29907	106	7	.	.	PUNCT
fcis-29907	107	1	2024.102382	2024.102382	X
fcis-29907	107	2	.	.	PUNCT
fcis-29907	108	1	[	[	X
fcis-29907	108	2	4	4	X
fcis-29907	108	3	]	]	PUNCT
fcis-29907	108	4	gong	gong	NOUN
fcis-29907	108	5	x	x	PROPN
fcis-29907	108	6	,	,	PUNCT
fcis-29907	108	7	duan	duan	PROPN
fcis-29907	108	8	h	h	PROPN
fcis-29907	108	9	,	,	PUNCT
fcis-29907	108	10	yang	yang	PROPN
fcis-29907	108	11	y	y	PROPN
fcis-29907	108	12	,	,	PUNCT
fcis-29907	108	13	et	et	PROPN
fcis-29907	108	14	al	al	PROPN
fcis-29907	108	15	.	.	PUNCT
fcis-29907	108	16	improving	improve	VERB
fcis-29907	108	17	audio	audio	ADJ
fcis-29907	108	18	classification	classification	NOUN
fcis-29907	108	19	method	method	NOUN
fcis-29907	108	20	by	by	ADP
fcis-29907	108	21	combining	combine	VERB
fcis-29907	108	22	self	self	NOUN
fcis-29907	108	23	-	-	PUNCT
fcis-29907	108	24	supervision	supervision	NOUN
fcis-29907	108	25	with	with	ADP
fcis-29907	108	26	knowledge	knowledge	NOUN
fcis-29907	108	27	distillation	distillation	NOUN
fcis-29907	108	28	[	[	X
fcis-29907	108	29	journal	journal	NOUN
fcis-29907	108	30	article	article	NOUN
fcis-29907	108	31	]	]	X
fcis-29907	108	32	//	//	SYM
fcis-29907	108	33	electronics	electronic	NOUN
fcis-29907	108	34	,	,	PUNCT
fcis-29907	108	35	2024	2024	NUM
fcis-29907	108	36	,	,	PUNCT
fcis-29907	108	37	13(1	13(1	NUM
fcis-29907	108	38	)	)	PUNCT
fcis-29907	109	1	[	[	X
fcis-29907	109	2	accessed	access	VERB
fcis-29907	109	3	2024	2024	NUM
fcis-29907	109	4	-	-	SYM
fcis-29907	109	5	01	01	NUM
fcis-29907	109	6	-	-	SYM
fcis-29907	109	7	29	29	NUM
fcis-29907	109	8	]	]	PUNCT
fcis-29907	109	9	.	.	PUNCT
fcis-29907	110	1	doi:10.3390/	doi:10.3390/	PROPN
fcis-29907	110	2	electronics	electronic	NOUN
fcis-29907	110	3	13010052	13010052	NUM
fcis-29907	110	4	.	.	PUNCT
fcis-29907	111	1	[	[	X
fcis-29907	111	2	5	5	X
fcis-29907	111	3	]	]	X
fcis-29907	111	4	liu	liu	PROPN
fcis-29907	111	5	a	a	DET
fcis-29907	111	6	h	h	NOUN
fcis-29907	111	7	,	,	PUNCT
fcis-29907	111	8	glass	glass	PROPN
fcis-29907	111	9	j	j	PROPN
fcis-29907	111	10	r	r	PROPN
fcis-29907	111	11	,	,	PUNCT
fcis-29907	111	12	gan	gan	PROPN
fcis-29907	111	13	c	c	NOUN
fcis-29907	111	14	,	,	PUNCT
fcis-29907	111	15	et	et	PROPN
fcis-29907	111	16	al	al	PROPN
fcis-29907	111	17	.	.	PROPN
fcis-29907	111	18	method	method	PROPN
fcis-29907	111	19	for	for	ADP
fcis-29907	111	20	self	self	NOUN
fcis-29907	111	21	-	-	PUNCT
fcis-29907	111	22	supervised	supervise	VERB
fcis-29907	111	23	speech	speech	NOUN
fcis-29907	111	24	recognition	recognition	NOUN
fcis-29907	111	25	through	through	ADP
fcis-29907	111	26	sparse	sparse	ADJ
fcis-29907	111	27	subnetwork	subnetwork	NOUN
fcis-29907	111	28	discovery	discovery	NOUN
fcis-29907	111	29	in	in	ADP
fcis-29907	111	30	pre	pre	ADJ
fcis-29907	111	31	-	-	ADJ
fcis-29907	111	32	trained	train	VERB
fcis-29907	111	33	speech	speech	NOUN
fcis-29907	111	34	self	self	NOUN
fcis-29907	111	35	-	-	PUNCT
fcis-29907	111	36	supervised	supervise	VERB
fcis-29907	111	37	learning	learning	NOUN
fcis-29907	111	38	,	,	PUNCT
fcis-29907	111	39	involves	involve	VERB
fcis-29907	111	40	pruning	prune	VERB
fcis-29907	111	41	weights	weight	NOUN
fcis-29907	111	42	of	of	ADP
fcis-29907	111	43	lowest	low	ADJ
fcis-29907	111	44	magnitude	magnitude	NOUN
fcis-29907	111	45	in	in	ADP
fcis-29907	111	46	new	new	ADJ
fcis-29907	111	47	subnetwork	subnetwork	NOUN
fcis-29907	111	48	regardless	regardless	ADV
fcis-29907	111	49	of	of	ADP
fcis-29907	111	50	network	network	NOUN
fcis-29907	111	51	structure	structure	NOUN
fcis-29907	111	52	to	to	PART
fcis-29907	111	53	satisfy	satisfy	VERB
fcis-29907	111	54	target	target	NOUN
fcis-29907	111	55	sparsity	sparsity	NOUN
fcis-29907	111	56	:	:	PUNCT
fcis-29907	111	57	us2023360642	us2023360642	PROPN
fcis-29907	111	58	-	-	PUNCT
fcis-29907	111	59	a1	a1	NOUN
fcis-29907	112	1	[	[	X
fcis-29907	112	2	patent	patent	NOUN
fcis-29907	112	3	]	]	PUNCT
fcis-29907	112	4	.	.	PUNCT
fcis-29907	113	1	[	[	X
fcis-29907	113	2	2023	2023	NUM
fcis-29907	113	3	-	-	SYM
fcis-29907	113	4	11	11	NUM
fcis-29907	113	5	-	-	SYM
fcis-29907	113	6	20	20	NUM
fcis-29907	113	7	]	]	PUNCT
fcis-29907	113	8	.	.	PUNCT