Speaker Recognition and Speech Emotion Recognition Based on GMM

DOI

10.2991/eeic-13.2013.102How to use a DOI?

Keywords

Speaker recognition; speech emotion recognition; MFCC; GMM

Abstract

This paper put forward a method for speaker recognition and speech emotion recognition based on GMM. The reason of using this model is its ability to the dependency among extracted speech signal feature vectors and the multi-modality in their distribution. Firstly, we extracted the Mel Frequency Cepstral Coefficients (MFCC) from each frame of the speech signal as speech features, and then apply Gaussian mixture model as a statistical classifier. The results of experiment show that we proposed method is effective than others.

Copyright

© 2013, 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  - Shupeng Xu
AU  - Yan Liu
AU  - Xiping Liu
PY  - 2013/12
DA  - 2013/12
TI  - Speaker Recognition and Speech Emotion Recognition Based on GMM
BT  - Proceedings of the 3rd International Conference on Electric and Electronics
PB  - Atlantis Press
SP  - 434
EP  - 436
SN  - 1951-6851
UR  - https://doi.org/10.2991/eeic-13.2013.102
DO  - 10.2991/eeic-13.2013.102
ID  - Xu2013/12
ER  -