Decision Templates Ensemble and Diversity Analysis for Segment-Based Speech Emotion Recognition

DOI

10.2991/iske.2007.134How to use a DOI?

Keywords

Speech emotion recognition. Decision templates ensemble. Diversity analysis. Information fusion. Ensemble classifiers.

Abstract

In this paper, we propose a novel scheme for speech emotion recognition, which uses decision-templates ensemble algorithm (DT) to combine base classifiers built on segment-level feature sets. Different feature sets from segments can provide sufficient diversity among base classifiers, which is known as a necessary condition for improvement in ensemble performance. Compared with those methods of majority voting ensemble and support vector machine, our ensemble scheme can achieve the highest performance at suitable segment levels. On the other hand, we investigate which segment-level and strategy of training base classifiers can provide potential performance in speech emotion recognition, in terms of diversity analysis.

Copyright

© 2007, 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  - Fukun Bi
AU  - Jian Yang
AU  - Ying Yu
AU  - Dan Xu
PY  - 2007/10
DA  - 2007/10
TI  - Decision Templates Ensemble and Diversity Analysis for Segment-Based Speech Emotion Recognition
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 781
EP  - 785
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.134
DO  - 10.2991/iske.2007.134
ID  - Bi2007/10
ER  -