A multi-modal approach to emotion recognition using undirected topic models

Proceedings - IEEE International Symposium on Circuits and Systems

Volumn , Issue , 2014, Pages 754-757

  Shah, Mohit ^a   Chakrabarti, Chaitali ^a   Spanias, Andreas ^a  

^a Arizona State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX STRUCTURE; EMOTION RECOGNITION; LANGUAGE FEATURES; MULTI-MODAL APPROACH; MULTI-MODAL FUSION; REAL-TIME IMPLEMENTATIONS; STATE-OF-THE-ART APPROACH; TEMPORAL INFORMATION;

REAL TIME CONTROL;

EID: 84907409936     PISSN: 02714310     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISCAS.2014.6865245     Document Type: Conference Paper

References (17)

1. G. Caridakis, G. Castellano, L. Kessous, A. Raouzaiou, L. Malatesta, S. Asteriadis, and K. Karpouzis, "Multimodal emotion recognition from expressive faces, body gestures and speech," Artificial intelligence and innovations: From theory to applications, pp. 375-388, 2007.
2. N. Sebe, I. Cohen, and T. S. Huang, "Multimodal emotion recognition," Handbook of Pattern Recognition and Computer Vision, vol. 4, pp. 387-419, 2005.
3. R. Cowie, E. Douglas-Cowie, N. Tsapatsoulis, G. Votsis, S. Kollias, W. Fellenz, and J. G. Taylor, "Emotion recognition in human-computer interaction," IEEE Signal Processing Magazine, vol. 18, no. 1, pp. 32-80, 2001.
4. M. El Ayadi, M. S. Kamel, and F. Karray, "Survey on speech emotion recognition: Features, classification schemes, and databases," Pattern Recognition, vol. 44, no. 3, pp. 572-587, 2011.
5. B. Schuller, B. Vlasenko, F. Eyben, G. Rigoll, and A. Wendemuth, "Acoustic emotion recognition: A benchmark comparison of performances," IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU), pp. 552-557, 2009.
6. G. E. Hinton and R. Salakhutdinov, "Replicated softmax: an undirected topic model," Advances in neural information processing systems (NIPS), pp. 1607-1614, 2009.
7. M. Shah, L. Miao, C. Chakrabarti, and A. Spanias, "A speech emotion recognition framework based in latent Dirichlet allocation: Algorithms and FPGA implementation," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2553-2556, 2013.
8. C. Busso, M. Bulut, C.-C. Lee, A. Kazemzadeh, E. Mower, S. Kim, J. N. Chang, S. Lee, and S. S. Narayanan, "IEMOCAP: Interactive emotional dyadic motion capture database," Language resources and evaluation, vol. 42, no. 4, pp. 335-359, 2008.
9. A. Metallinou, S. Lee, and S. Narayanan, "Decision level combination of multiple modalities for recognition and analysis of emotional expression," ICASSP, pp. 2462-2465, 2010.
10. C.-C. Lee, E. Mower, C. Busso, S. Lee, and S. Narayanan, "Emotion recognition using a hierarchical binary decision tree approach," Speech Communication, vol. 53, no. 9, pp. 1162-1171, 2011.
11. Y. Kim, H. Lee, and E. Mower Provost, "Deep learning for robust feature generation in audio-visual emotion recognition," ICASSP, 2013.
12. D. M. Blei, A. Y. Ng, and M. I. Jordan, "Latent Dirichlet allocation," The Journal of Machine Learning research, vol. 3, pp. 993-1022, 2003.
13. N. Srivastava and R. Salakhutdinov, "Multimodal learning with deep boltzmann machines," NIPS, pp. 2231-2239, 2012.
14. T. Huynh, M. Fritz, and B. Schiele, "Discovery of activity patterns using topic models," Proceedings of the 10th International Conference on Ubiquitous Computing, pp. 10-19, 2008.
15. S. Kim, S. Narayanan, and S. Sundaram, "Acoustic topic model for audio information retrieval," IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), pp. 37-40, 2009.
16. B. Schuller, S. Steidl, and A. Batliner, "The INTERSPEECH 2009 emotion challenge. " INTERSPEECH, pp. 312-315, 2009.
17. G. E. Dahl, D. Yu, L. Deng, and A. Acero, "Context-dependent pretrained deep neural networks for large-vocabulary speech recognition," IEEE Transactions on Audio, Speech, and Language Processing, vol. 20, no. 1, pp. 30-42, 2012.