淡江大學機構典藏:Item 987654321/103467
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 62822/95882 (66%)
造访人次 : 4015742      在线人数 : 531
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧：
  • 您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果
  • 若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据
    •  进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/103467


    题名: SPEECH ENHANCEMENT BASED ON SPARSE THEORY UNDER NOISY ENVIRONMENT
    作者: Hsieh, Ching-Tang;Chen, Yan-heng;Chen, Ting-Wen;Chen, Li-Ming
    贡献者: 電機工程學系暨研究所
    关键词: Speech enhancement, sparse representations, K-SVD, discrete cosine transform (DCT), orthogonal matching pursuit (OMP)
    日期: 2015-07-18
    上传时间: 2015-07-27 14:05:46 (UTC+8)
    出版者: Academy of Taiwan Information Systems Research (ATISR)
    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.
    關聯: International Conference on Internet Studies (NETs 2015)
    显示于类别:[電機工程學系暨研究所] 會議論文

    文件中的档案:

    档案 描述 大小格式浏览次数
    NETs2015_127_SPEECH_ENHANCEMENT.pdf會議文獻1012KbAdobe PDF462检视/开启

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈