id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
bcpe-2691	Xian, Weijia	Speech Emotion Recognition Application for Education	2022	6	.pdf	application/pdf	2384	142	54	The application is based on PAD dimension, convolutional neural network to extract deep speech emotion features, and Least squares support vector machine for emotion recognition, thus improving the recognition accuracy of this application. For example, Zbancioc et al. apply improved MFCC and LPCC features to emotion recognition, and the recognition rate reaches 75%[2].	cache/bcpe-2691.pdf	txt/bcpe-2691.txt