Boosting selection of speech related features to improve performance of multi-class SVMs in emotion detection

Author:

Altun Halis,Polat Gökhan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference30 articles.

1. Non-parametric classifier-independent feature selection;Abe;Pattern Recognition,2006

2. Altun, H., & Polat, G. (2007). New Frameworks to boost feature selection algorithms in emotion detection for improved human–computer interaction, brain vision and artificial intelligent. In Lecturer notes in computer science, LNCS (Vol. 4729, pp. 533–541). Berlin, Heidelberg: Springer-Verlag.

3. Altun, H., Shawe-Taylor, J., & Polat, G. (2007). New feature selection frameworks. In Emotion recognition to evaluate the informative power of speech related features, ISSPA07, ninth international symposium on signal processing and its applications.

4. Dimensionality reduction via sparse support vector machines;Bennett;Journal of Machine Learning Research, JMLR,2003

5. Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W., & Weiss, B. (2005). A database of german emotional speech. In Proceedings Interspeech.

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