期刊文献+

基于拉普拉斯模型和掩蔽效应的语音增强 被引量:1

Speech enhancement based on Laplacian model and masking
下载PDF
导出
摘要 提出了一种有效的消除噪声且减小语音失真的语音增强方法。首先实现了语音信号服从Laplacian分布、噪声服从Gaussian分布假设下的MMSE增强算法。为了进一步提高语音增强效果,在增强语音谱幅度阈值的计算上将该方法与人的掩蔽特性相结合。通过语音增强方法性能客观评测表明,该语音增强方法更好地抑制了噪声,有效地减小语音失真。 An effective approach for attenuating acoustic noise and mitigating speech distortion is proposed.First,MMSE method is analysed when the clean speech is modeled by a Laplacian distribution and the noise is modeled by a Gaussian distribution. Then,human perceptual auditory masking threshold is incorporated into this approach when the threshold of spectral amplitude of enhanced speech is computed.The experiment result evaluated by objective more significant noise reduction and reduce the chances of speech distortion.
出处 《计算机工程与应用》 CSCD 北大核心 2010年第7期153-154,161,共3页 Computer Engineering and Applications
关键词 语音增强 听觉掩蔽阈值 最小均方误差(MMSE) speech enhancement masking properties Minimum Mean-Square measure shows the proposed method can achieve a Error(MMSE)
  • 相关文献

参考文献8

  • 1Cohen I.Speech enhancement using super-Gaussian speech models and noncausal a priori SNR estimation[J].Speeeh Communication, 2005,47 : 336-350.
  • 2Porter J,Boll S.Optimal estimators for spectral restoration of noisy speech[C]//Proc IEEE Internat Conf Acoust Speech,Signal Process (ICASSP) ,San Diego,CA, 1984:18A.2.1-18A.2.4.
  • 3Martin R.Speech enhancement using MMSE short time spectral estimation with Gamma distributed speech priors[C]//Proc 27th IEEE Internat Conf Acoust Speech Signal Process,ICASSP-02,Orlando, FL, 2002:I-253-I-256.
  • 4Martin R,Breithaupt C.Speech enhancement in the DFT domain using Laplacian speech priors[C]//Proc 8th Intemat Workshop on Acoustic Echo and Noise Control (IWAENC), Kyoto,Japan,2003 : 87-90.
  • 5You Chang-huai,Koh Soh-ngee.Rahardja S.Masking-based β-order MMSE speech enhancement[J].Speech Communication,2006,48: 57-70.
  • 6Virag N.Single channel speech enhancement based on masking properties of the human auditory system[J].IEEE Transactions on Speech and Audio Processing, 1999,7(2).
  • 7Johnston J D.Transform coding of audio signals using perceptual noise criteria[J].IEEE Journal on Selected Areas in Communications, 1988,6(2 ).
  • 8Ephraim Y,Malah D.Speech enhancement using minimum meansquare error short-time spectral amplitude estimator[J].IEEE Transactions on Acoustics,Speech and Signal Processing, 1984,32(6).

同被引文献11

  • 1Gannot S,Burshtein D, Weinstein E.Iterative and sequential Kalman filter-based speech enhancement algorithms[J].IEEE Trans Speech and Audio Process, 1998,6(4):373-385.
  • 2Jax P, Vary P.Artificial bandwidth extension of speech signals using MMSE estimation based on a hidden Markov model[C]// IEEE International Conference on Acoustics, Speech, and SignalProcessing, 2003,8 ( 1 ) : 680-683.
  • 3Martin R.Noise power spectral density estimation based on optimal smoothing and minimum statistics[J].IEEE Trans Speech and Audio Processing, 2001,9 (5) : 504-512.
  • 4Cohen I.Noise spectrum estimation in adverse environments:Improved minima controlled recursive averaging[J].IEEE Transactions on Speech and Audio Processing,2003,11 (5) :466-475.
  • 5Ephraim Y,Malah D.Speech enhancement using a minimum meansquare short-time spectral amplitude estimator[J].IEEE Trans Acoustic Speech Signal Process, 1984,32(6) : 1109-1121.
  • 6Cohen I.Speech enhancement using a noncausal a priori SNR estimator[J].IEEE Signal Processing Letters, 2004,11 (9) : 725-728.
  • 7Cohen I.On the decision-directed estimation approach of Ephraim and Malah[C]//IEEE International Conference on Acoustics, Speech and Signal Processing,2004: 293-296.
  • 8Cappe O.Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor[J].IEEE Transactions, Speech and Audio Processing, 1994,2(2) :345-349.
  • 9Ren Yao, Johnson M T.An improved SNR estimator for speech enhancement[C]//IEEE International Conference on Acoustics, Speech and Signal Processing,2008:4901-4904.
  • 10杨秋成,范炜玮.基于先验信噪比估计的语音增强方法[J].信号处理,2008,24(2):329-332. 被引量:9

引证文献1

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部