Abstract
In this paper, we present an emotion recognition system using wavelet neural network and BP neural network for special human affective state in the speech signal. 750 short emotional sentences with different contents from 5 speakers were collected as experiment materials. The features relevant with energy, speech rate, pitch and formant are extracted from speech signals. Neural network are used as the classifier for 5 emotions including anger, calmness, happiness, sadness and boredom. Compared with the traditional BP network, the results of experiments show that the wavelet neural network has faster convergence speed and higher recognition rate.
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References
Fragopanagos, N., Taylor, G.: Emotion Recognition in Human-Computer Interaction. Neural Networks 18, 389–405 (2005)
Cheriyadat, A.: Limitations of principal component analysis for dimensionality-reduction for classification of hyperspectral data, pp. 31–56. Mississippi State University, America (2003)
Bhatti, M.W., Wang, Y., Guan, L.: A Neural Network Approach for Human Emotion Recognition in Speech. In: ISCAS 2004, pp. 181–184 (2004)
Murry, I.R., Arnott, J.L.: Applying an analysis of acted vocal emotions to improve the simulation of synthetic speech. Computer Speech and Lauguage 22, 107–129 (2008)
Ververidis, D., Kotrropoulos, K.: Emotional speech recognition: Resource, features, and methods. Speech Communication 48, 1162–1181 (2006)
Nicholson, J., Takahashi, K., Nakatsu, R.: Emotion Recognition in Speech Using Neural Networks. Neural Computing & Applications 9, 290–296 (2000)
Zhongzhe, X., Dellandrea, E., Weibei Deal, E.: Features Extraction and Selection for Emotional Speech Classification. IEEE, 411–416 (2005)
Temko, A., Nadeu, C.: Classification of acoustic events using SVM-based clustering schemes. Patttern Recognition 39, 682–694 (2006)
Amir, N.: Classifying emotions in speech: a comparison of methods. In: EUROSPEECH 2001 Sandinavia 7th European Conference on Speech Communication and Technology 2th INTERSPEECH Even, pp. 127–130 (2001)
Bhatti, M.W., Wang, Y., Guan, L.: A Neural Network Approach for Human Emotion Recognition in Speech. In: ISCAS 2004, pp. 181–184 (2004)
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© 2009 Springer-Verlag Berlin Heidelberg
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Huang, Y., Zhang, G., Xu, X. (2009). Speech Emotion Recognition Research Based on Wavelet Neural Network for Robot Pet. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science(), vol 5755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04020-7_107
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DOI: https://doi.org/10.1007/978-3-642-04020-7_107
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04019-1
Online ISBN: 978-3-642-04020-7
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