Evaluation of a Noise-Robust Multi-Stream Speaker Verification Method Using F_0 Information
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概要
- 論文の詳細を見る
We have previously proposed a noise-robust speaker verification method using fundamental frequency (F0) extracted using the Hough transform. The method also incorporates an automatic stream-weight and decision threshold estimation technique. It has been confirmed that the proposed method is effective for white noise at various SNR conditions. This paper evaluates the proposed method in more practical in-car and elevator-hall noise conditions. The paper first describes the noise-robust F0 extraction method and details of our robust speaker verification method using multi-stream HMMs for integrating the extracted F0 and cepstral features. Details of the automatic stream-weight and threshold estimation method for multi-stream speaker verification framework are also explained. This method simultaneously optimizes stream-weights and a decision threshold by combining the linear discriminant analysis (LDA) and the Adaboost technique. Experiments were conducted using Japanese connected digit speech contaminated by white, in-car, or elevator-hall noise at various SNRs. Experimental results show that the F0 features improve the verification performance in various noisy environments, and that our stream-weight and threshold optimization method effectively estimates control parameters so that FARs and FRRs are adjusted to achieve equal error rates (EERs) under various noisy conditions.
- (社)電子情報通信学会の論文
- 2008-03-01
著者
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FURUI Sadaoki
Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Instit
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IWANO Koji
Department of Computer Science, Tokyo Institute of Technology
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Iwano Koji
Department Of Computer Science Tokyo Institute Of Technology
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Furui Sadaoki
Department Of Computer Science Graduate School Of Information Science And Engineering Tokyo Institut
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Furui Sadaoki
Tokyo Inst. Technol. Meguro‐ku Jpn
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ASAMI Taichi
Department of Computer Science, Tokyo Institute of Technology
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Asami Taichi
Department Of Computer Science Tokyo Institute Of Technology
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