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- KUROIWA Shingo
- Faculty of Engineering, the University of Tokushima
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- UMEDA Yoshiyuki
- Faculty of Engineering, the University of Tokushima
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- TSUGE Satoru
- Faculty of Engineering, the University of Tokushima
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- REN Fuji
- Faculty of Engineering, the University of Tokushima
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抄録
In this paper, we propose a distributed speaker recognition method using a nonparametric speaker model and Earth Mover's Distance (EMD). In distributed speaker recognition, the quantized feature vectors are sent to a server. The Gaussian mixture model (GMM), the traditional method used for speaker recognition, is trained using the maximum likelihood approach. However, it is difficult to fit continuous density functions to quantized data. To overcome this problem, the proposed method represents each speaker model with a speaker-dependent VQ code histogram designed by registered feature vectors and directly calculates the distance between the histograms of speaker models and testing quantized feature vectors. To measure the distance between each speaker model and testing data, we use EMD which can calculate the distance between histograms with different bins. We conducted text-independent speaker identification experiments using the proposed method. Compared to results using the traditional GMM, the proposed method yielded relative error reductions of 32% for quantized data.
収録刊行物
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- IEICE transactions on information and systems
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IEICE transactions on information and systems 89 (3), 1074-1081, 2006-03-01
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詳細情報 詳細情報について
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- CRID
- 1572261551842025344
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- NII論文ID
- 110004719383
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- NII書誌ID
- AA10826272
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- ISSN
- 09168532
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- 本文言語コード
- en
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- データソース種別
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- CiNii Articles