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    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/50560

    題名: Robust Speaker Identification System Based on Two-Stage Vector Quantization
    作者: Chen, Wan-chen;謝景棠;Hsieh, Ching-tang;Hsu, Chih-hsu
    貢獻者: 淡江大學電機工程學系
    關鍵詞: Speaker Identification;Wavelet Transform;Linear Predictive Cepstral Coefficient (LPCC);2-Stage Vector Quantization
    日期: 2008-12-01
    上傳時間: 2010-08-09 19:49:00 (UTC+8)
    出版者: 淡江大學
    摘要: 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.
    關聯: 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
    顯示於類別:[電機工程學系暨研究所] 期刊論文


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