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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/50560


    Title: Robust Speaker Identification System Based on Two-Stage Vector Quantization
    Authors: Chen, Wan-chen;謝景棠;Hsieh, Ching-tang;Hsu, Chih-hsu
    Contributors: 淡江大學電機工程學系
    Keywords: Speaker Identification;Wavelet Transform;Linear Predictive Cepstral Coefficient (LPCC);2-Stage Vector Quantization
    Date: 2008-12-01
    Issue Date: 2010-08-09 19:49:00 (UTC+8)
    Publisher: 淡江大學
    Abstract: This paper presents an effective method for speaker identification system. 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. In order to effectively utilize these multi-band speech features, 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. Finally, the KING speech database is used to evaluate the proposed method for text-independent speaker identification. The experimental results show that the proposed method gives better performance than other recognition models proposed previously in both clean and noisy environments.
    Relation: 淡江理工學刊 = Tamkang Journal of Science and Engineering 11(4), pp.357-366
    DOI: 10.6180/jase.2008.11.4.05
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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