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Efficient Speech Enhancement Approach based on Minima Controlled Recursive Averaging through Modified Map Criterion using Hidden Markov Model
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 44 - Number 14 |
| Year of Publication: 2012 |
| Authors: M. Mathivanan, S.chenthur Pandian |
10.5120/6333-8708
|
M. Mathivanan, S.chenthur Pandian . Efficient Speech Enhancement Approach based on Minima Controlled Recursive Averaging through Modified Map Criterion using Hidden Markov Model. International Journal of Computer Applications. 44, 14 ( April 2012), 27-34. DOI=10.5120/6333-8708
Abstract
Speech coding has become one of the most essential techniques in telecommunications and in the multimedia infrastructure. Existing speech coding techniques are applicable only for stationary environment and degrade the speech quality. This paper proposes a novel speech coding technique with better speech quality through MCRA and modified MAP. Maximum A Posteriori (MAP) criterion is extensively utilized in the statistical model-based Minima Controlled Recursive Averaging (MCRA) approaches. In the traditional MAP criterion, the inter-frame correlation of the voice activity is not taken into account. A novel technique to enhance the MCRA depending on the modified MAP via two-state Hidden Markov Model (HMM) is presented in this paper. With the proposed MAP criterion, the decision rule is obtained by clearly integrating the a priori, a posteriori, and inter-frame correlation information into the Likelihood Ratio Test (LRT).
References
- Milan Jelinek, and Redwan Salami, "Wideband Speech Coding Advances in VMR-WB Standard", IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, No. 4, 2007.
- "AMR Wideband Speech Codec: Transcoding Functions" [Online]. Available: http://www. 3gpp. org 3GPP Technical Specification TS 26. 190.
- N. S Kim and J. -H. Chang, "Spectral Enhancement Based on Global Soft Decision", IEEE Signal Processing Letters, Vol. 7, No. 5, pp. 108{110, May 2000.
- D. Malah, R. V. Cox and A. J. Accardi, "Tracking speech-presence uncertainty to improve speech enhancement in non-stationary noise environments," Proc. 24th IEEE Internat. Conf. Acoust. Speech Signal Process. , ICASSP-99, Phoenix, Arizona, 15-19 March 1999, pp. 789-792.
- H. G. Hirsch and C. Ehrlicher, "Noise Estimation Techniques for Robust Speech Recognition", Proc. 20th IEEE Internat. Conf. Acoust. Speech Signal Process. , ICASSP-95, Detroit, Michigan, 1995, pp. 153-156.
- R. J. McAulay and M. L. Malpass "Speech enhancement using a soft-decision noise suppression filter," IEEE Trans. Acoustics, Speech and Signal Processing, Vol. ASSP-28, No. 2, pp. 137{145, April 1980.
- V. Stahl, A. Fischer and R. Bippus, "Quantile based noise estimation for spectral subtraction and Wiener filtering," Proc. 25th IEEE Internat. Conf. Acoust. Speech Signal Process, ICASSP-2000, Istanbul, Turkey, 2000, pp. 1875-1878.
- Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator," IEEE Trans. Acoust. , Speech, Signal Process. , vol. ASSP-32, no. 6, pp. 1109–1121, Dec. 1984.
- Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean-square error log-spectral amplitude estimator," IEEE Trans. Acoust. , Speech, Signal Process. , vol. ASSP-32, no. 2, pp. 443–445, 1985.
- S. F. Boll, "Suppression of acoustic noise in speech using spectral subtraction," IEEE Trans. Acoust. , Speech, Signal Process. , vol. ASSP-27, no. 2, pp. 113–120, Apr. 1979.
- I. Cohen and B. Berdugo, "Noise estimation by minima controlled recursive averaging for robust speech enhancement," IEEE Signal Process. Lett. , vol. 9, no. 1, pp. 12–15, Jan. 2002.
- I. Cohen, "Noise spectrum estimation in adverse environments: Improved minima controlled recursive averaging," IEEE Trans. Speech Audio Process. , vol. 11, no. 5, pp. 466–475, Sep. 2003.
- V. Stouten, H. V. hamme, and P. Wambacq, "Application of minimum statistics and minima controlled recursive averaging methods to estimate a cepstral noise model for robust ASR," in Proc. ICASSP, Toulouse, France, May 2006, pp. 765–768.
- N. Fan, J. Rosca, and R. Balan, "Speech noise estimation using enhanced minima controlled recursive averaging," in Proc. ICASSP, Honolulu, HI, Apr. 2007, pp. 581–584.
- J. W. Shin, H. J. Kwon, S. H. Jin, and N. S. Kim, "Voice activity detection based on conditional map criterion," IEEE Signal Process. Lett. , vol. 15, no. 2, pp. 257–260, 2008.
- Jong-Mo Kum and Joon-Hyuk Chang, "Speech Enhancement Based on Minima Controlled Recursive Averaging Incorporating Second-Order Conditional MAP Criterion", IEEE Signal Processing Letters, Vol. 16, No. 7, 2009.
- Zavarehei, E. ; Vaseghi, S. ; Qin Yan, "Noisy Speech Enhancement Using Harmonic-Noise Model and Codebook-Based Post-Processing", IEEE Transactions on Audio, Speech, and Language Processing, Volume: 15, Issue: 4, Page(s): 1194 – 1203, 2007.
- Wa Maina, C. ; Walsh, J. M. ; "Joint Speech Enhancement and Speaker Identification Using Approximate Bayesian Inference", IEEE Transactions on Audio, Speech, and Language Processing, Page(s): 1517 – 1529, 2011.
- Shiwen Deng, Jiqing Han, Tieran Zheng, Guibin Zheng, "A Modified Map Criterion based on Hidden Markov Model for Voice Activity Detection", IEEE Trans. on Speech and Audio Processing, vol. 7, no. 2, pp. 126–137,1999.
- Y. Ephraim and D. Malah, "Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator," IEEE Trans. Acoust. , Speech, Signal Process. , vol. ASSP-32, pp. 1109–1121, 1984.
- A W Rix, J G Beerends, M P Hollier, A P Hekstra, "Perceptual Evaluation of Speech Quality (PESQ), an Objective Method for End-to-End Speech Quality Assessment of Narrow- and Telephone Networks and Speech Codecs",, ITU-T P. 862, 2001.
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