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Speech Enhancement Algorithm Based on MMSE Short Time Spectral Amplitude in Whispered Speech 被引量：1

Speech Enhancement Algorithm Based on MMSE Short Time Spectral Amplitude in Whispered Speech
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摘要 An improved method based on minimum mean square error-short time spectral amplitude （MMSE-STSA） is proposed to cancel background noise in whispered speech. Using the acoustic character of whispered speech, the algorithm can track the change of non-stationary background noise effectively. Compared with original MMSE-STSA algorithm and method in selectable mode Vo-coder （SMV）, the improved algorithm can further suppress the residual noise for low signal-to-noise radio （SNR） and avoid the excessive suppression. Simulations show that under the non-stationary noisy environment, the proposed algorithm can not only get a better performance in enhancement, but also reduce the speech distortion. An improved method based on minimum mean square error-short time spectral amplitude （MMSE-STSA） is proposed to cancel background noise in whispered speech. Using the acoustic character of whispered speech, the algorithm can track the change of non-stationary background noise effectively. Compared with original MMSE-STSA algorithm and method in selectable mode Vo-coder （SMV）, the improved algorithm can further suppress the residual noise for low signal-to-noise radio （SNR） and avoid the excessive suppression. Simulations show that under the non-stationary noisy environment, the proposed algorithm can not only get a better performance in enhancement, but also reduce the speech distortion.
作者 Zhi-Heng Lu Huai-Zong Shao Tai-Liang Ju
机构地区 The authors are with School of Communication and InformationEngineering
出处 《Journal of Electronic Science and Technology of China》 2009年第2期115-118,共4页 中国电子科技（英文版）
关键词 Index Terms-Minimum mean square error shorttime spectral amplitude （MMSE-STSA） speechenhancement whispered speech. Index Terms-Minimum mean square error shorttime spectral amplitude （MMSE-STSA）, speechenhancement, whispered speech.
分类号 TN912.35 [电子电信—通信与信息系统] TN929.533 [电子电信—通信与信息系统]
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  • 1N. Virag.Single channel speech enhancement based on masking properties of the human auditory system[].IEEE Trans on Speech and Audio Proc- essing.1999
  • 2Y. Hu,,P. C. Loizou.Speech enhancement based on wavelet thresholding the multitaper spectrum[].IEEE Transactions on Speech and Audio Processing.2004
  • 3Y. Ephraim,,D. Malah.Speech enhancement using a minimum mean-square error log-spectral ampli- tude estimator[].IEEE Trans on Acoust Speech and Signal Processing.1985
  • 4O. Cappè.Elimination of the musical noise phe- nomenon with the Ephraim and Malah noise sup- pressor[].IEEE Trans on Speech and Audio Proc- essing.1994
  • 5M. Berouti,,R. Schwartz,,J. Makhoul.Enhancementof speech corrupted by acoustic noise[].Proc IEEE Int Conf Acoust Speech and Signal Processing.1979
  • 6Lincoln Laboratory Speech Enhancement Corpus. http:// www.ll.mit.edu/IST/corpora.html .
  • 7Y. Hu,,P. C. Loizou.Incorporating a psychoacous- tical model in frequency domain speech enhance- ment[].IEEE Signal Processing Letters.2004
  • 8I. Cohen.Relaxed statistical model for speech en- hancement and a priori SNR estimation[].IEEE Transactions on Speech and Audio Processing.2005
  • 9K. S. Riedel,,A. Sidorenko.Minimum bias multiple taper spectral estimation[].IEEE Trans on SignalProcessing.1995
  • 10W. Yang,,M. Benbouchta,,R. Yantorno.Perform- ance of the modified bark spectral distortion as an objective speech quality measure[].Proc IEEE Int Conf Acoust Speech and Signal Processing Seat- tle.1998

共引文献29

同被引文献9

  • 1Xiaojie Zou, Xueyao Li, Rubo Zhang. Speech enhance- ment based on Hilbert-Huang transform theory[J]. Pro- ceedings of the first international multi-symposiums on computer and computational sciences, 2006.
  • 2Chatlani N. Speech enhancement using adaptive empirical mode decomposition [C]. Soraghan J J. // DSP 2009: 16th International Conference on Digital Signal Process- ing, Proceedings, 2009.
  • 3Flogeras D,Doraiswami R, Kaye M. E. A real time spec- tral subtraction based speech enhancement scheme[J]. E- lectrical and Computer Engineering 2003. IEEE CCECE 2003. Canadian Conference on,2003.5(2): 1071-1074.
  • 4Guang-Yan Wang, XiacrQun Zhao, Xia Wang. Speech en- hancement based on the combination of spectral subtrac- tion and wavelet thresholding[J]. IEEE 2009 Internation-al Conference on Apperceiving Computing and Intelli- gence Analysis, ICACIA 2009.
  • 5Hairong Jia, Xueying Zhang,Chensheng Jin. A Modified Speech Enhancement Algorithm Based on the Subspace [J]. 2009 Second International Symposium on Knowl- edge Acquisition and Modeling.
  • 6Y. Ephraim, D. Malah. Speeeh enhancement using a mini- mum mean square error short time speetral amplitude es- timator[J]. IEEE Transaetionson Speeeh Audio Proeess- ing, 1984,32(6): 1109-1121.
  • 7Zhang Anbing, Liu Xinxia, Li xipan. The denosing based on the fusion method of Kalman filter and EMD[J]. Pro- ceedings-2009 International Conference on Information Engineering and Computer Science, ICIECS 2009.
  • 8Kais Khaldi, Abdel-Ouahab Boudraa, Abdelkhalek Bouchikhi, et al. Speech enhancement via EMD[J]. EURASIP Journal on Advances in Signal Processing, 2008,55(10): 1-8.
  • 9Khaldi. Kais, Turki-Hadi Alouane. Monia. Speech de- noising by adaptive weighted average filtering in the EMD framework. 2008 International Conference on Sig- nals, Circuits and Systems, SCS 2008,1.

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Journal of Electronic Science and Technology of China
2009年 第2期

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