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  • 标题:Speech Enhancement Using Iterative Kalman Filter with Time and Frequency Mask in Different Noisy Environment
  • 本地全文:下载
  • 作者:G.Manmadha Rao ; Ummidala Santosh Kumar
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2016
  • 卷号:9
  • 期号:9
  • 页码:317-324
  • 出版社:SERSC
  • 摘要:The main aim of the Speech Enhancement algorithms is to improve the Quality of speech. The Quality of speech is expressed in two parameters. One is clarity,and another is intelligibility. In this paper,we proposed a method to improve the quality of speech based on computationally efficient AR modeled Iterative Kalman Filter with time and frequency mask. This approach is based on reconstruction of noisyspeech signalsusing Auto Regressive modeled Kalman filter and further to reduce artifact noise time and frequency mask is applied to the Kalman filter output. The results of the proposed method are found to be better compared to spectral subtraction, wiener filter and Kalman filter methods
  • 关键词:Kalman filter; intelligibility; Spectral Subtraction; Wiener filter; speech ;enhancement; white;-;colored noises
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