Decision Templates Ensemble and Diversity Analysis for Segment-Based Speech Emotion Recognition
- 10.2991/iske.2007.134How to use a DOI?
- Speech emotion recognition. Decision templates ensemble. Diversity analysis. Information fusion. Ensemble classifiers.
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.
- © 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/).
Cite this article
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 -