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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/107475

    Authors: Hsieh, Ching-Tang;Chiang, Cheng-Yuan;Chen, Ting-Wen
    Keywords: Speech enhancement;sparse representations;K-SVD;Label Consistent K-SVD(LCKSVD)
    Date: 2016-06-25
    Issue Date: 2016-09-13 02:11:17 (UTC+8)
    Abstract: The sparse algorithm for sparse enhancement is more and more popular issues, recently. In previous research, the sparse algorithm for sparse enhancement will spend much time, so we propose LC K-SVD(Label Consistent K-SVD) to reduce spending time. We focus on the White Gaussian Noise. The experiments show that denoising performance of our proposed method is very closed to sparse algorithm in SNR, LLR, SNRseg and PESQ, even better then it. Our method only need half time then sparse algorithm.
    Relation: Advances in Computer Science Research
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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