Speech Emotion Recognition Based on Fuzzy K-NN Algorithm with Fractionally Spaced Blind Equalization

DOI

10.2991/wartia-16.2016.357How to use a DOI?

Keywords

Fuzzy KNN, speech emotion, fractional spaced equalizer, k nearest neighbor algorithm.

Abstract

Due to the noise and multi-channel room acoustic environment, practical speech emotion recognition remains an unsolved challenge. In this paper, we first study the fractional spaced blind equalizer for speech preprocessing. The noise interference is effectively removed and more detailed emotional features are reserved. Second, the fuzzy k nearest neighbor algorithm is used to classify speech. Finally, the proposed algorithm is compared with traditional speech emotion recognition algorithms. Experimental results show that the fractionally spaced equalization is effective for practical speech emotion recognition.

Copyright

© 2016, 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  - Tao Yuan
AU  - Chunhong Deng
AU  - WangYang Shi
PY  - 2016/05
DA  - 2016/05
TI  - Speech Emotion Recognition Based on Fuzzy K-NN Algorithm with Fractionally Spaced Blind Equalization
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1804
EP  - 1807
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.357
DO  - 10.2991/wartia-16.2016.357
ID  - Yuan2016/05
ER  -