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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Emotion-State Conversion for Speaker Recognition
verfasst von : Dongdong Li, Yingchun Yang, Zhaohi Wu, Tian Wu
Erschienen in: Affective Computing and Intelligent Interaction
Verlag: Springer Berlin Heidelberg
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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%.