SPEECH ENHANCEMENT BASED ON SPARSE THEORY UNDER NOISY ENVIRONMENT
學年 103
學期 2
發表日期 2015-07-18
作品名稱 SPEECH ENHANCEMENT BASED ON SPARSE THEORY UNDER NOISY ENVIRONMENT
作品名稱（其他語言）
著者 Hsieh, Ching-Tang;Chen, Yan-heng;Chen, Ting-Wen;Chen, Li-Ming
作品所屬單位 電機工程學系暨研究所
出版者 Academy of Taiwan Information Systems Research (ATISR)
會議名稱 International Conference on Internet Studies 2015 (NETs 2015)
會議地點 Tokyo, Japan
摘要 Recently, the sparse algorithm for sparse enhancement is more and more popular issues. In this paper, we classify the process of the sparse theory to enhance speech signal into two parts, one is for dictionary training part and the other is signal reconstruction part. We focus on the White Gaussian Noise. Clean speech dictionary D is trained by K-SVD algorithm. The orthogonal matching pursuit(OMP) algorithm is used to obtain the sparse coefficients X of clean speech dictionary D. Denoising performance of the experiments shows that our proposed method is superior than other methods in SNR, LLR, SNRseg and PESQ.
關鍵字 Speech enhancement, sparse representations, K-SVD, discrete cosine transform (DCT), orthogonal matching pursuit (OMP)
語言 en_US
收錄於
會議性質 國際
校內研討會地點
研討會時間 20150718~20150719
通訊作者 Chen, Ting-Wen
國別 JPN
公開徵稿 Y
出版型式 電子版
出處 International Conference on Internet Studies (NETs 2015)
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機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/103467 )

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