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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/11928

タイトル: Speech recognition in noisy conditions based on speech separation using Non-negative Matrix Factorization
著者: Du, Yuxuan
Akagi, Masato
発行日: 2014
出版者: 2014 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'14)
誌名: 2014 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'14)
開始ページ: 429
終了ページ: 432
抄録: This paper proposes a speech recognition method for applications in adverse noisy environments. Speech recognition in noisy conditions is a challenging problem since speech observed in such conditions is corrupted by noise. To deal with this problem, we integrate non-negative matrix factorization (NMF) and modified restricted temporal decomposition (MRTD) into a recognition method based on the concept of “auditory scene analysis” (ASA). Experiments were conducted using 100 isolated words in 4 different noise conditions at a signal to noise ratio (SNR) of 0 dB. Experimental results showed the proposed method achieved recognition rates of 80%, which is about 50% higher than that of the method based on dynamic time warp (DTW).
Rights: This material is posted here with permission of the Research Institute of Signal Processing Japan. Yuxuan Du, Masato Akagi, 2014 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (NCSP'14), 2014, 429-432.
URI: http://hdl.handle.net/10119/11928
資料タイプ: publisher
出現コレクション:b11-1. 会議発表論文・発表資料 (Conference Papers)

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