Abstract
The performance of speaker recognition system is easily disturbed by the changes of the internal states of human. The ongoing work proposes an approach of speech emotion-state conversion to improve the performance of speaker identification system over various affective speech. The features of neutral speech are modified according to statistical prosodic parameters of emotion utterances. Speaker models are generated based on the converted speech. The experiments conducted on an emotion corpus with 14 emotion states shows promising results with an improved performance by 7.2%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Scherer, K.R., Johnstone, T., Klasmeyer, G.: Can automatic speaker verification be improved by training the algorithms on emotional speech? In: Proceedings of the 6th International Conference on Spoken Language Processing, Beijing, China (2000)
Scherer, K.R., Johnstone, T., Bänziger, T.: Automatic verification of emotionally stressed speakers: The problem of individual differences. In: Proc. of SPECOM 1998 (1998)
Sato, J., Morishima, S.: Emotion modeling in speech production using emotion space. In: Proc. IEEE Int. Workshop on Robot and Human Communication (1996)
Thévenaz, P., Hügli, H.: Usefulness of the LPC-Residue in Text-Independent Speaker Verification. Speech Communication 17, 145–157 (1995)
Galanis, D., Darsinos, V., Kokkinakis, G.: Investigating Emotional Speech Parameter for Speech Synthesis. In: ICECS 1996, pp. 1227–1230 (1996)
LDC: The Linguistic Data Consortium, web pages at www.ldc.upenn.edu
Banse, R., Scherer, K.R.: Acoustic profiles in vocal emotion expression. Journal of Per-sonality and Social Psychology 70, 614–636 (1996)
Frank, D., Thomas, P., Alex, W.: Recognizing Emotion in Speech. In: ICSLP 1996, pp. 1970–1973 (1996)
Sun, S.: Pitch Determination and Voice Quality Analysis Using Subharmonic-TO-Harmonic Ratio. In: IEEE International Conference on Acoustics, Speech, and Signal processing (2002)
Feustel, T.C., Velius, G.A., Logan, R.J.: Human and Machine Performance on Speaker Identity Verification. Speech Tech., 169–170 (1989)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, D., Yang, Y., Wu, Z., Wu, T. (2005). Emotion-State Conversion for Speaker Recognition. In: Tao, J., Tan, T., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2005. Lecture Notes in Computer Science, vol 3784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573548_52
Download citation
DOI: https://doi.org/10.1007/11573548_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29621-8
Online ISBN: 978-3-540-32273-3
eBook Packages: Computer ScienceComputer Science (R0)