Emotion recognition from speech using sub-syllabic and pitch synchronous spectral features

Author:

Koolagudi Shashidhar G.,Krothapalli Sreenivasa Rao

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Reference60 articles.

1. Bitouk, D., Verma, R., & Nenkova, A. (2010). Class-level spectral features for emotion recognition. Speech Communication, 52, 613–625.

2. Bozkurt, E., Erzin, E., Erdem, C. E., & Erdem, A. T. (2009). Improving automatic emotion recognition from speech signals. In 10th annual conference of the international speech communication association (interspeech), Brighton, UK, 6–10 September 2009 (pp. 324–327).

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

4. Busso, C., Deng, Z., Yildirim, S., Bulut, M., Lee, C. M., Kazemzadeh, A., Lee, S., Neumann, U., & Narayanan, S. (2004). Analysis of emotion recognition using facial expressions, speech and multimodal information. In ACM 6th international conference on multimodal interfaces (ICMI 2004), State College, PA, The USA, October 2004.

5. Chen, J., Huang, Y. A., Li, Q., & Paliwal, K. K. (2004). Recognition of noisy speech using dynamic spectral subband centroids. IEEE Signal Processing Letters, 11, 258–261 (February 2004).

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