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%.
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© 2005 Springer-Verlag Berlin Heidelberg
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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
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DOI: https://doi.org/10.1007/11573548_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29621-8
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