Abstract
In this paper, combined features of global and time-sequence were used as the characteristic parameters for speech emotional recognition. A new method based on formula of MMD (Modified Mahalanobis Distance) was proposed to decrease the estimated errors and simplify the calculation. Four emotions including happiness, anger, surprise and sadness are considered in the paper. 1000 recognizing sentences collected from 10 speakers were used to demonstrate the effectiveness of the new method. The average emotion recognition rate reached at 95%. Comparison with method of MQDF [1] (Modified quadratic discriminant function), Data analysis also displayed that the MMD is better than MQDF.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Cai, L., Jiang, C., Wang, Z., Zhao, L., Zou, C.: A Method Combining The Global And Time Series Structure Features For Emotion Recognition In Speech. In: IEEE Int. Conf. Neural Networks & Signal Processing (2003)
Iida, A., Campbell, N., Iga, S., Higuchi, F., Yasumura, M.: Acoustic Nature and perceptual testing of corpora of emotional speech
Banse, R., Scherer, K.R.: Acoustic profiles in vocal emotion expression. Journal of Personality and Social Psychology 70(3) (1996)
Mozziconacc, S.: Speech Variability and Emotion: Production and Perception. Technische Universiteit Eindhoven, Eindhoven (1998)
Scherer, K.R.: Speech and Emotional States. In: Darby, J.K. (ed.) Speech Evaluation in Psychiatry. Grune and Stratton, New York (1981)
Soskin, W.F., Kauffman, P.E.: Judgements of Emotions in Word-free Voice Samples. Journal of Communication (1961)
Li, Z., Xiangmin, Q., Cairong, Z., Zhenyang, W.: A Study on Emotional Recognition in Speech Signal. Journal of Software 12(7) (2001)
Cowie, R.: Emotion Recognition in Human-Computer Interaction. IEEE Signal Processing Magazine 18(1), 32–80 (2001)
Muraka, S.: Emotional Constituents in Text and Emotional Components in Speech, Ph. D. Theis, Kyoto, Kyoto Institute of Technology, Japan (1998)
Shigenaga, M.: Features of Emotionally Uttered Speech Revealed by Discriminant Analysis (VI), The preprint of the acoustical society of Japan, pp. 2–18 (1999)
Li, Z., Xiangmin, Q., Cairong, Z., Zhenyang, W.: A Study on Emotional Feature Analysis and Recognition in Speech Signal. Journal of China Institute of Communications 21(1), 18–25 (2000)
Li, Z., Xiangmin, Q., Cairong, Z., Zhenyang, W.: A Study on Emotional Feature Extract in Speech signal. Data Collection and Process 15(1), 120–123 (2000)
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
Zhao, L., Cao, Y., Wang, Z., Zou, C. (2005). Speech Emotional Recognition Using Global and Time Sequence Structure Features with MMD. 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_40
Download citation
DOI: https://doi.org/10.1007/11573548_40
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)