Speech enhancement using improved phase spectrum compensation

被引:0
|
作者
Wang D. [1 ]
Jia H. [1 ]
机构
[1] College of Information Engineering, Taiyuan Univ. of Technology, Taiyuan
关键词
Noise power spectrum; Phase spectrum compensation; Speech enhancement; Speech presence probability; Wiener filter;
D O I
10.3969/j.issn.1001-2400.2017.03.015
中图分类号
学科分类号
摘要
The typical phase spectrum compensation method has the negative enhancement performance in a low SNR, so the improved phase spectrum compensation method is proposed for this problem. First, the algorithm compensates the speech spectrum through the phase compensation function obtained by calculating the signal to noise ratio of each frame; second, by the new speech presence probability algorithm to estimate the noise power spectral density; finally, we apply the new phase spectrum and the estimated noise in the wiener filter. Simulation results show that the improved algorithm proposed in this paper can effectively improve the ability of voice systems to remove noise especially in a low SNR. © 2017, The Editorial Board of Journal of Xidian University. All right reserved.
引用
收藏
页码:83 / 88
页数:5
相关论文
共 9 条
  • [1] Zhang J., Liu H., Fan Y., Speech Enhancement Method Using Self-adaptive Time-shift and Threshold Discrete Cosine Transform, Journal of Xidian University, 41, 6, pp. 155-159, (2014)
  • [2] Ephraim Y., Malah D., Speech Enhancement Using a Minimum-mean Square Error Short-time Spectral Amplitude Estimator, IEEE Transactions on Acoustics, Speech and Signal Processing, 32, 6, pp. 1109-1121, (1984)
  • [3] Gao Y., Deng Z., Yang Z., Design of Watermark Embedding System for Digital Audio Products Based on HAS, Journal of Nanjing University of Posts and Telecommunications, 26, 5, pp. 56-64, (2006)
  • [4] Paliwal K., Wojcicki K., Shannon B., The Importance of Phase in Speech Enhancement, Speech Communication, 53, 4, pp. 465-494, (2011)
  • [5] Stark A.P., Wojcicki K.K., Lyons J.G., Et al., Noise Driven Short-time Phase Spectrum Compensation Procedure for Speech Enhancement, Proceedings of the Annual Conference of the International Speech Communication Association, pp. 549-552, (2008)
  • [6] Krawczyk M., Gerkmann T., STFT Phase Reconstruction in Voiced Speech for an Improved Single-channel Speech Enhancement, IEEE/ACM Transactions on Speech and Language Processing, 22, 12, pp. 1931-1940, (2014)
  • [7] Gao Y., Liao G., Zhu S., Knowledge-aided Bayesian Rao Detection Approach in Compound Gaussian Noise, Journal of Xidian University, 40, 6, pp. 46-51, (2013)
  • [8] Gerkmann T., Hendriks R.C., Noise Power Estimation Based on the Probability of Speech Presence, Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 145-148, (2011)
  • [9] Rong Q., Xiao H., Study on MMSE Wiener Flitering-based Speech Enhancement Method and MATLAB Implementation, Computer Applications and Software, 32, 1, pp. 153-156, (2015)