Speech Emotion Recognition System Based on Integrating Feature and Improved HMM

摘要：

　　This paper described a new speech emotion recognition system by use of Hidden Markov Model (HMM)aiming at improving speech emotion recognition rate.Seven discrete emotional states (anger,disgust,fear,joy,neutral,sadness,surprise) are classified throughout the work.It integrated different speech features into the system,the system is comprised of three main sections,a pre-processing section,a feature extracting section and a HMM processing section.Results are given on speaker dependent case using the Chinese corpus of emotional speech synthesis database.Recognition experiments show that the method is effective and high speed and accuracy for emotion recognition.

关键词： Emotion recognition Integrating feature Hidden Markov Model Speech signal

作者: Han Zhiyan Lun Shuxian Wang Jian

作者单位: College of Engineering, Bohai University Jinzhou, Liaoning, China

会议类型: 国际会议

会议名称: 2012 2nd International Conference on Computer Application and System Modeling(2012第二届计算机应用与系统建模国际会议)(ICCASM-2012)

会议地点: 沈阳

会议语种:英文

页码: 571-574

在线出版日期: 2012-07-27（万方平台首次上网日期，不代表论文的发表时间）