NDLI: Two-Stage Vector Quantization Based Multi-band Models for Speaker Identification

Content Provider	IEEE Xplore Digital Library
Author	Wan-Chen Chen Ching-Tang Hsieh Chih-Hsu Hsu
Copyright Year	2007
Description	Author affiliation: St. John's Univ., Taipei (Wan-Chen Chen)
Abstract	This paper presents an effective method for speaker identification. Based on the wavelet transform, the input speech signal is decomposed into several frequency bands, and then the linear predictive cepstral coefficients (LPCC) of each band are calculated. Furthermore, the cepstral mean normalization technique is applied to all computed features in order to provide similar parameter statistics in all acoustic environments. We propose a multi-band 2-stage vector quantization (VQ) as the recognition model in which different 2-stage VQ classifiers are applied independently to each band and the errors of all 2-stage VQ classifiers are combined to yield total error and a global recognition decision. The experimental results show that the proposed method gives better performance than other recognition models proposed previously in both clean and noisy environments.
Starting Page	2336
Ending Page	2341
File Size	315053
Page Count	6
File Format	PDF
ISBN	0769530389
DOI	10.1109/ICCIT.2007.41
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-21
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Loudspeakers Cepstral analysis Speech coding Vector quantization Acoustic noise Working environment noise Speech enhancement Feature extraction Mel frequency cepstral coefficient Information technology
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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