Speech Emotion Recognition Application for Education
Keywords:Speech Emotion Recognition; PAD Dimensions; Convolutional Neural Network (CNN); Least Squares Support Vector Machine (LSSVM).
Based on convolutional neural networks, a speech recognition application capable of analyzing human emotions is designed. This speech emotion recognition can better assist teachers to understand students' emotional status in the learning process and enable them to improve their teaching methods with the help of the system, thus achieving the goal of improving students' learning efficiency. 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.
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