Speech Emotion Recognition System Based on Integrating Feature and Improved HMM

DOI

10.2991/iccasm.2012.145How to use a DOI?

Keywords

Emotion recognition, Integrating feature, Hidden Markov Model, Speech signal

Abstract

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.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhiyan Han
AU  - Shuxian Lun
AU  - Jian Wang
PY  - 2012/08
DA  - 2012/08
TI  - Speech Emotion Recognition System Based on Integrating Feature and Improved HMM
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 571
EP  - 574
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.145
DO  - 10.2991/iccasm.2012.145
ID  - Han2012/08
ER  -