|Table of Contents|

Complex plane spectral subtraction for speech enhancement in complicated environments


Research Field:
Publishing date:


Complex plane spectral subtraction for speech enhancement in complicated environments
Wang Shuiping123Tang Zhenmin3Chen Beijing12Jiang Ye3
1.School of Computer and Software;
2.Jiangsu Engineering Center of Network Monitoring,Nanjing University of Information Science and Technology,Nanjing 210044,China;
3.School of Computer Science and Engineering,NUST,Nanjing 210094,China
complicated environments speech enhancement complex plane spectral subtraction gain function
To reduce noise in complicated environments and eliminate the inferences of noise on the applications of speech recognition and speaker recognition systems in automatic military command and control fields,a new spectral subtraction is designed.Aiming at the incorrect assumption of the traditional spectral subtraction that the phase difference between the clean speech and noise signals is zero in the speech enhancement process,an improved spectral subtraction is proposed based on complex plane and considering the phase difference among the clean speech,the noise and the noisy speech signals.The gain function is corrected.The results of complicated battlefield simulation experiments show that the method proposed here performs better than the traditional spectral subtraction,especially in low signal noise ratio(SNR)conditions.For the noisy speech with input SNR of 5 dB,the output SNR is more than 12.21 dB after denoised by using the complex plane spectral subtraction,which increases 2.1 dB than the result of the traditional spectral subtraction.


[1] 路建伟,丁庆海,朱雪平,等.战场环境下的军事命令识别技术[J].南京理工大学学报,2002,26(4):438-441,445.
Lu Jianwei,Ding Qinghai,Zhu Xueping,et al.The military order recognition technology in battlefield environment[J].Journal of Nanjing University of Science and Technology,2002,26(4):438-441,445.
[2]Loizou P C.Speech enhancement algorithms:A survey:Recent advances in robust speech recognition technology[M].Spain:Bentham Science,2011:60-102.
Lei Jianjun,Yang Zhen,Liu Gang,et al.Review of noise robust speech recognition[J].Application Research of Computers,2009,26(4):1210-1216.
[4]Boll S F.Suppression of acoustic noise in speech using spectral subtraction[J].IEEE Transactions on Acoustics,Speech,and Signal Processing,1979,ASSP-27(2):113-120.
[5]Berouti M,Schwartz R,Makhoul J.Enhancement of speech corrupted by acoustic noise[A].IEEE Interna-tional Conference on ICASSP'79[C].Washington,DC,USA:IEEE,1979:208-211.
He Yiming,Zhang Gangbing,Qian Xianyi.Salt and pepper noise removal algorithm based on neighbourhood mean[J].Journal of Nanjing University of Science and Technology,2011,35(6):764-767,785.
[7]Preuss R.A frequency domain noise cancelling prepro-cessor for narrowband speech communications systems[A].IEEE International Conference on ICASSP'79[C].Washington,DC,USA:IEEE,1979:212-215.
[8]Martin R.Noise power spectral density estimation based on optimal smoothing and minimum statistics[J].IEEE Transactions on Speech and Audio Processing,2001,9(5):504-512.
Zhang Jun.Research on speech enhancement based on spectral subtraction method[J].Information Techno-logy,2009(3):74-76.
[11]Loizou P C.Speech enhancement based on perceptually motivated bayesian estimators of the magnitude spectrum[J].IEEE Transactions on Speech and Audio Processing,2005,13(5):857-869.
Jiang Ye,Tang Zhenmin.Research on the speaker identification based on short utterance[J].Acta Electronica Sinica,2011,39(4):953-957.
Wang Jiayong.Speech enhancement research based on improved spectral subtraction[J].Journal of Luoyang Technology College(Natural Sciences Edition),2009,19(2):53-55,72.
[14]Paliwal K,Wójcicki K,Shannon B.The importance of phase in speech enhancement[J].Speech Communica-tion,2011,53(4):465-494.


Last Update: 2013-12-31