English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 57042/90725 (63%)
造访人次 : 12449651      在线人数 : 147
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: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107377

    题名: Speech Enhancement based on Sparse Representation under Color Noisy Environment
    作者: Ching-Tang Hsieh, Piao-Yu Huang, Ting-Wen Chen, Yan-heng Chen
    关键词: Speech enhancement, sparse representations, K-SVD, discrete cosine transform (DCT), orthogonal matching pursuit (OMP)
    日期: 2015/11/10
    上传时间: 2016-08-18 13:39:17 (UTC+8)
    摘要: Recently, sparse algorithm for signal enhancement is more and more popular issues. In this paper, we apply it to enhance speech signal. The process of sparse theory is classified into two parts, one is for dictionary training part and the other is signal reconstruction part. We focus environment on both white Gaussian noise and color noise filtering based on sparse. The orthogonal matching pursuit (OMP) algorithm is used to optimize the sparse coefficients X of clean speech dictionary, where clean speech dictionary is trained by K-SVD algorithm. Then, we multiply these two matrixes D' and X' to reconstruct the clean speech signal. Denoising performance of the experiments shows that our proposed method is superior to other state of art methods in four kinds of objective quality measures as SNR, LLR, SNRseg and PESQ.
    關聯: International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2015. pp.134-138.
    显示于类别:[電機工程學系暨研究所] 會議論文





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