An Adaptive Wind Noise Reduction Method Based on a priori SNR Estimation for Speech Eenhancement

음성 강화를 위한 a priori SNR 추정기반 적응 바람소리 저감 방법

  • Received : 2015.11.02
  • Accepted : 2015.11.27
  • Published : 2015.12.01


This paper focuses on a priori signal to noise ratio (SNR) estimation method for the speech enhancement. There are many researches for speech enhancement with several ambient noise cancellation methods. The method based on spectral subtraction (SS) which is widely used in noise reduction has a trade-off between the performance and the distortion of the signals. So the need of adaptive method like an estimated a priori SNR being able to making a high performance and low distortion is increasing. The decision directed (DD) approach is used to determine a priori SNR in noisy speech signals. A priori SNR is estimated by using only the magnitude components and consequently follows a posteriori SNR with one frame delay. We propose a modified a priori SNR estimator and the weighted rational transfer function for speech enhancement with wind noises. The experimental result shows the performance of our proposed estimator is better Perceptual Evaluation of Speech Quality scores (PESQ, ITU-T P.862) compare to the conventional DD approach-based systems and different noise reduction methods.


Noise reduction;A priori SNR;Speech enhancement


  1. K. Daqrouq, I. N. Abu-Isbeih, M. Alfauri,"Speech signal enhancement using neural network and wavelet transform", 2009 6th International Multi-Conference on Systems, Signals and Devices, pp. 1-6, 2009.
  2. Y. Shao, C.H. Chang, "A Kalman filter based on wavelet filter-bank and psychoacoustic modeling for speech enhancement", 2006 IEEE International Symposium on Circuits and Systems, ISCAS 2006. Proceedings, May, 2006.
  3. Steven F. Boll, "Suppression of Acoustic Noise in Speech Using Spectral Subtraction", IEEE Transactions on Signal Processing, 27(2), pp. 113-120, 1979
  4. Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean square error short-time spectral amplitude estimator", IEEE.Transactions in Acoust., Speech, Signal Process., vol. 32, no. 6, pp. 1109-1121, Dec. 1984.
  5. Sinha, Deepen, and Ahmed H. Tewfik. "Low bit rate transparent audio compression using adapted wavelets", Signal Processing, IEEE Transactions on 41.12 (1993): 3463-3479.
  6. M. Bhatnagar, "A modified spectral subtraction method combined with perceptual weighting for speech enhancement", Master's thesis, University of Texas at Dallas, pp. 1-10, 2003.
  7. O. Cappe, "Elimination of the musical noise phenomenon with the Ephraim and Malah noise suppressor", IEEE Trans. Speech Audio Processing, 2 (2), pp. 346-349, 1994.
  8. J. Freudenberger, S. Stenzel, "Blind Matched Filtering for Speech Recording in Uncorrelated Noise", International Workshop on Acoustic Signal Enhancement, pp. 1-4, September 2012.
  9. Haykin, Simon, and Bernard Widrow. "Least-meansquare adaptive filters." Vol. 31. John Wiley & Sons, 2003.
  10. Guopin, H., Wei, Z., Qin, Z. "Improvement of audio noise reduction system based on RLS algorithm." Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on. IEEE, 2013.
  11. ITU-T P.862, Perceptual Evaluation of Speech Quality (PESQ): An Objective Method for End-to-End Speech Quality Assessment of Narrow-band Telephone Networks and Speech Codecs, 2001.
  12. TIMIT: acoustic-phonetic continuous speech corpus. Linguistic Data Consortium, 1993.
  13. S. F. Boll, "Suppression of acoustic noise in speech using spectral subtraction", IEEE Trans. Acoust., Speech, Signal Processing, Vol. 27, No. 2, pp. 113-120, 1979.
  14. Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean square error short-time spectral amplitude estimator," IEEE Transactions in Acoust., Speech, Signal Process., vol. 32, no. 6, pp. 1109-1121, Dec. 1984.
  15. Y. Ephraim and D. Malah, "Speech Enhancement Using a Minimum Mean-Sqaure Error Log-Spectral Amplitude Estimator", IEEE Transactions on Acoustic, Speech and Signal Processing, vol. 33, no. 2, 1985, pp. 443-445.
  16. P. C. Loizou, "Speech Enhancement based on Perceptually Motivated Bayesian Estimators of the Magnitude Spectrum", IEEE Transactions on Speech and Audio Processing, vol. 13, no. 5, 2005, pp. 857-869.