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Cost-Sensitive Learning for Emotion Robust Speaker Recognition
Joint Authors
Dai, Weihui
Li, Dongdong
Yang, Yingchun
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-04
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
In the field of information security, voice is one of the most important parts in biometrics.
Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed.
In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity.
However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system.
This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively.
Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper.
The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.
American Psychological Association (APA)
Li, Dongdong& Yang, Yingchun& Dai, Weihui. 2014. Cost-Sensitive Learning for Emotion Robust Speaker Recognition. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1050414
Modern Language Association (MLA)
Li, Dongdong…[et al.]. Cost-Sensitive Learning for Emotion Robust Speaker Recognition. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1050414
American Medical Association (AMA)
Li, Dongdong& Yang, Yingchun& Dai, Weihui. Cost-Sensitive Learning for Emotion Robust Speaker Recognition. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1050414
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050414