Robust Emotion Recognition using Speaking Rate Features

Chapter
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

In this chapter speaking rate characteristics of speech are explored for discriminating the emotions. In real life, we observe that certain emotions are very active with high speaking rate and some are passive with low speaking rate. With this motivation, in this chapter, we have proposed a two stage emotion recognition system, where the emotions are classified into three broad groups (active, neutral and passive) at the first stage and during second stage emotions in each broad group are further classified. Spectral and prosodic features are explored in each stage for discriminating the emotions. Combination of spectral and prosodic features is observed to be performed better.

References

  1. 1.
    S.G. Koolagudi, K.S. Rao, Two stage emotion recognition based on speaking rate. Int. J. Speech Technol. 14, 35–48 (2011)Google Scholar
  2. 2.
    S.G. Koolagudi, S. Ray, K.S. Rao, Emotion classification based on speaking rate, in Communications in Computer and Information Science, ed. by S. Ranka, A. Banerjee, K.K. Biswas, S. Dua, P. Mishra, R. Moona, S.-H. Poon, C.-L. Wang. International Conference on Contemporary Computing, vol. 94, pp. 316–327, Springer, USA, 6–8 Aug 2010Google Scholar
  3. 3.
    K.S. Rao, B. Yegnanarayana, Modeling durations of syllables using neural networks. Comput. Speech Lang. 21, 282–295 (2007)Google Scholar
  4. 4.
    A.L. Francis, H.C. Nusbaum, Paying attention to speaking rate, in Fourth International Conference on Spoken Language, 1996 ICSLP 96, (Philadelphia, PA, USA), pp. 1537–1540 (V3), IEEE, October 1996. Center for Computational Psychology, Department of Psychology, The University of ChicagoGoogle Scholar
  5. 5.
    J. Yuan, M. Liberman, C. Cieri, Towards an integrated understanding of speaking rate in conversation, in Interspeech 2006, (Pittsburgh, PA, 2006), pp. 541–544Google Scholar
  6. 6.
    M.S.H. Reddy, K.S. Kumar, S. Guruprasad, B. Yegnanarayana, Subsegmental features for analysis of speech at different speaking rates, in International Conference on Natural Language Processing, (Macmillan, India, 2009), pp. 75–80Google Scholar
  7. 7.
    A. LI, Y. ZU, Speaking rate effects on discourse prosody in standard chinese, in Fourth International Conference on Speech Prosody, (Campinas, Brazil, 2008), pp. 449–452, 6–9 May 2008Google Scholar
  8. 8.
    H. Yang, W. Guo, Q. Liang, A speaking rate adjustable digital speech repeater for listening comprehension in second-language learning, in International Conference on Computer Science and, Software Engineering, vol. 5, pp. 893–896, 12–14 Dec 2008Google Scholar
  9. 9.
    S.G. Koolagudi, S. Maity, V.A. Kumar, S. Chakrabarti, K.S. Rao, IITKGP-SESC : speech database for emotion analysis. Communications in Computer and Information Science, JIIT University, Noida, India: Springer, ISSN: 1865–0929 ed., 17–19 Aug 2009Google Scholar
  10. 10.
    E.F. Lussier, N. Morgan, Effects of speaking rate and word frequency on pronunciations in convertional speech. Speech Commun. 29, 137–158 (1999)CrossRefGoogle Scholar
  11. 11.
    M. Richardson, M.Y. Hwang, A. Acero, X. Huang, Improvements on speech recognition for fast talkers, in Eurospeech Conference, Sept 1999Google Scholar

Copyright information

© The Author(s) 2013

Authors and Affiliations

  1. 1.School of Information TechnologyIndian Institute of Technology KharagpurKharagpurIndia

Personalised recommendations