A Multiscale Chaotic Feature Extraction Method for Speaker Recognition
Joint Authors
Chao, Wang
Lin, Jiang
Yumei, Yi
Maosheng, Zhang
Defeng, Chen
Tonghan, Wang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-03
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
In speaker recognition systems, feature extraction is a challenging task under environment noise conditions.
To improve the robustness of the feature, we proposed a multiscale chaotic feature for speaker recognition.
We use a multiresolution analysis technique to capture more finer information on different speakers in the frequency domain.
Then, we extracted the speech chaotic characteristics based on the nonlinear dynamic model, which helps to improve the discrimination of features.
Finally, we use a GMM-UBM model to develop a speaker recognition system.
Our experimental results verified its good performance.
Under clean speech and noise speech conditions, the ERR value of our method is reduced by 13.94% and 26.5% compared with the state-of-the-art method, respectively.
American Psychological Association (APA)
Lin, Jiang& Yumei, Yi& Maosheng, Zhang& Defeng, Chen& Chao, Wang& Tonghan, Wang. 2020. A Multiscale Chaotic Feature Extraction Method for Speaker Recognition. Complexity،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1144570
Modern Language Association (MLA)
Lin, Jiang…[et al.]. A Multiscale Chaotic Feature Extraction Method for Speaker Recognition. Complexity No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1144570
American Medical Association (AMA)
Lin, Jiang& Yumei, Yi& Maosheng, Zhang& Defeng, Chen& Chao, Wang& Tonghan, Wang. A Multiscale Chaotic Feature Extraction Method for Speaker Recognition. Complexity. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1144570
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1144570