Emotional Speech Recognition Based on ECG

摘要：

Application of Principal Component Analysis (PCA) for emotional speech recognition using Electrocardiogram (ECG) parameters andprosodic parameters is presented in this paper. We choose people who speak stand mandarin to record emotional speeches and measure the ECG during recording. The ECG signal is filtered using wavelet transform to remove power line interference,base line wander and electromyography interference. R wave amplitude,RR interval and QRS complex duration is selected as ECG parameters. Combined with prosodic parameters,such as amplitude energy,fundamental frequency,first formant s frequency and so on,the emotional speech can be converted into a ten-dimension eigenvector. Using PCA algorithm,the emotional recognition experiment is carried out,and the result show that the recognition rate based on ECG parameters and prosodic parameters is obviously better than that based on prosodic parameters with 3 to 4 percentage points higher on average.

关键词： emotional recognition ECG PCA wavelet transform.

作者: Bo Li Yutai Wang Lihao Wang

作者单位: School of Information Science and Engineering,University of Jinan Jinan 250022,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 3167-3171

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）