Implementation of A New Speech Negative Emotion Recognition System. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Wang, Yuqiong; Zhao, Zehui; Huang, Zhiwei
• Is Part Of: Journal of physics. Volume 1757:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Emotionrecognition -- Characteristic parameters -- Group recognition -- Back Propagation Neural Network; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1757/1/012021
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: A new emotion recognition system based on speech is constructed to improve the ability of recognizing negative emotions. Multi-dimensional acoustic characteristics were tested and among them, short-term energy and Mel-frequency cepstral coefficients (MFCC) were selected to be used as parameters for recognition. The system consists two modes: single recognition and group recognition. Single recognition adopts BP neural network model based on MFCC, while group recognition adds support vector machine model based on short-term energy on the basis of single recognition which the group recognition rate of 20 speech can reach 97%. With the increase of the number of speech in each group, the recognition accuracy of negative emotion tends to 100%.