Automatic Emotion Recognition from Speech A PhD Research Proposal

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• 作者：Yazid Attabi (12) Yazid.attabi@crim.ca
  Pierre Dumouchel (12) pierre.dumouchel@crim.ca
• 关键词：Emotion recognition &#8211 ; simililarity concept &#8211 ; speech signal
• 刊名：Lecture Notes in Computer Science
• 出版年：2011
• 出版时间：2011
• 年：2011
• 卷：6975
• 期：1
• 页码：191-199
• 全文大小：200.2 KB
• 参考文献：1. Li, W., Zhang, Y., Fu, Y.: Speech emotion recognition in E-learning system based on affective computing. In: Proceedings - Third International Conference on Natural Computation, ICNC, Hainan, China, pp. 809–813 (2007)
  2. Jones, C.M., Jonsson, I.-M.: Performance analysis of acoustic emotion recognition for in-car conversational interfaces. In: Stephanidis, C. (ed.) UAHCI 2007 (Part II). LNCS, vol. 4555, pp. 411–420. Springer, Heidelberg (2007)
  3. Clavel, C., et al.: De la construction du corpus 茅motionnel au syst猫me de d茅tection le point de vue applicatif de la surveillance dans les lieux publics. Revue d’Intelligence Artificielle 20(4-5), 529–551 (2006)
  4. Inanoglu, Z., Caneel, R.: Emotive alert: HMM-based emotion detection in voicemail messages. In: International Conference on Intelligent User Interfaces, Proceedings IUI, San Diego, CA, United States, pp. 251–253 (2005)
  5. Panat, A.R., Ingole, V.T.: Affective state analysis of speech for speaker verification: Experimental study, design and development. In: Proceedings - International Conference on Computational Intelligence and Multimedia Applications, India, pp. 255–261 (2007)
  6. Devillers, L., Vidrascu, L.: Real-life emotion recognition in speech. In: M眉ller, C. (ed.) Speaker Classifcation II. LNCS (LNAI), vol. 4441, pp. 34–42. Springer, Heidelberg (2007)
  7. Lee, C.M., Narayanan, S.: Emotion Recognition Using a Data-Driven Fuzzy Inference System. In: Eurospeech, Geneva (2003)
  8. Banse, R., Scherer, K.R.: Acoustic Profiles in Vocal Emotion Expression. Journal of Personality and Social Psychology, 614–636 (1996)
  9. Ververidis, D., Kotropolos, C.: Automatic speech classification to five emotional states based on gender information. In: Proc. of Eusipco, pp. 341–344 (2004)
  10. Scherer, K.R.: Vocal communication of emotion: A review of research paradigms. Speech Communication 40(1-2), 227–256 (2003)
  11. Sethu, V., Ambikairajah, E., Epps, J.: Speaker normalisation for speech-based emotion detection. In: 15th International Conference on Digital Signal Processing, Cardiff, UK, pp. 611–614 (2007)
  12. Grimm, M., Kroschel, K.: Rule-based emotion classification using acoustic features. In Proc. 3rd Internat. Conf. on Telemedicine and Multimedia Communication. Kajetany, Poland (2005)
  13. Lee, C.M., et al.: Emotion Recognition based on Phoneme Classes. In: ICSLP, Korea (2004)
  14. Schuller, B., et al.: Comparing one and two-stage acoustic modeling in the recognition of emotion in speech. In: IEEE Workshop on Automatic Speech Recognition and Understanding, Japan (2007)
  15. Schuller, B., et al.: Towards more reality in the recognition of emotional. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI, USA, pp. 941–944 (2007)
  16. Attabi, Y.: Reconnaissance automatique des 茅motions 脿 partir du signal acoustique, Master Thesis, 脡cole de technologie sup茅rieure (脡TS), Montr茅al (2009)
  17. Huang, R., Ma, C.: Toward a speaker-independent real-time affect detection system. In: 18th International Conference on Pattern Recognition, Hong Kong, China (2006)
  18. Chen, C., You, M., Song, M., Bu, J., Liu, J.: An enhanced speech emotion recognition system based on discourse information. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3991, pp. 449–456. Springer, Heidelberg (2006)
  19. Lee, C.M., Narayanan, S.: Emotion Recognition Using a Data-Driven Fuzzy Inference System. In: Eurospeech, Geneva (2003)
  20. Schuller, B., Steidl, S., Batliner, A.: The Interspeech 2009 Emotion Challenge. In: Interspeech. ISCA, Brighton (2009)
  21. Lee, C., Mower, E., Busso, C., Lee, S., Narayanan, S.: Emotion Recognition Using a Hierarchical Binary Decision Tree Approach. In: Interspeech, ISCA, Brighton (2009)
  22. Kockmann, M., Burget, L., Černock媒, J.: Brno University of Technology System for Interspeech 2009 Emotion Challenge. In: Interspeech. ISCA, Brighton (2009)
  23. Attabi, Y., Dumouchel, P.: Weighted Ordered Classes - Nearest Neighbors: A New Framework for Automatic Emotion Recognition From Speech. In: Interspeech. ISCA, Florence (2011)
  24. Dehak, N., Kenny, et al.: Front-End Factor Analysis for Speaker Verification Submitted to IEEE Transactions on Audio, Speech and Language Processing (2009)
• 作者单位：1. 脡cole de technologie sup茅rieure, Montr茅al, Canada2. Centre de recherche informatique de Montr茅al, Montr茅al, Canada
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

This paper contains a PhD research proposal related to the domain of automatic emotion recognition from speech signal. We started by identifying our research problem, namely the acute confusion problem between emotion classes and we have cited different sources of this ambiguity. In the methodology section, we presented a method based on simililarity concept between a class and an instance patterns. We dubbed this method as Weighted Ordered classes – Nearest Neighbors. The first result obtained exceeds in performance the best result of the state-of-the art. Finally, as future work, we have made a proposition to improve the performance of the proposed system.