NMF features for speech emotion recognition

Authors:
Kyungjoong Jeong;Jaiyoun Song;Hong Jeong
Affiliations:
Pohang University of Science and Technology, Pohang, South Korea;Pohang University of Science and Technology, Pohang, South Korea;Pohang University of Science and Technology, Pohang, South Korea
Venue:
Proceedings of the 2009 International Conference on Hybrid Information Technology
Year:
2009

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Abstract

There are numerous algorithms to detect emotion from speech signals. Among the algorithms, we selected spectral analysis and fused Non-negative Matrix Factorization (NMF) for obvios emotion classification. The algorithm has been tested in several different ways by varying NMF and the speech database. The experimental results show performance of 90% and classification success of 77% for speaker dependent and independent cases, respectively.