Automated vocal emotion recognition using phoneme class specific features

Géza Kiss; Jan Van Santen

Automated vocal emotion recognition using phoneme class specific features

Géza Kiss, Jan Van Santen

Institute on Development & Disability

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Methods for automated vocal emotion recognition often use acoustic feature vectors that are computed for each frame in an utterance, and global statistics based on these acoustic feature vectors. However, at least two considerations argue for usage of phoneme class specific features for emotion recognition. First, there are well-known effects of phoneme class on some of these features. Second, it is plausible that emotion influences the speech signal in ways that differ between phoneme classes. A new method based on the concept of phoneme class specific features is proposed in which different features are selected for regions associated with different phoneme classes and then optimally combined, using machine learning algorithms. A small but significant improvement was found when this method was compared with an otherwise identical method in which features were used uniformly over different phoneme classes.

Original language	English (US)
Title of host publication	Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010
Publisher	International Speech Communication Association
Pages	1161-1164
Number of pages	4
State	Published - 2010

Publication series

Name	Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010

Keywords

Biomedical application
Emotion recognition
Phoneme class specific features

ASJC Scopus subject areas

Language and Linguistics
Speech and Hearing

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Cite this

Kiss, G., & Van Santen, J. (2010). Automated vocal emotion recognition using phoneme class specific features. In Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010 (pp. 1161-1164). (Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010). International Speech Communication Association.

Automated vocal emotion recognition using phoneme class specific features. / Kiss, Géza; Van Santen, Jan.

Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010. International Speech Communication Association, 2010. p. 1161-1164 (Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kiss, G & Van Santen, J 2010, Automated vocal emotion recognition using phoneme class specific features. in Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010. Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010, International Speech Communication Association, pp. 1161-1164.

Kiss G, Van Santen J. Automated vocal emotion recognition using phoneme class specific features. In Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010. International Speech Communication Association. 2010. p. 1161-1164. (Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010).

Kiss, Géza ; Van Santen, Jan. / Automated vocal emotion recognition using phoneme class specific features. Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010. International Speech Communication Association, 2010. pp. 1161-1164 (Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010).

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