A Modified Perceptual Constrained Spectral Weighting Technique For Speech Enhancement
| International Journal of Computer Trends and Technology (IJCTT) | |
© - December Issue 2013 by IJCTT Journal | ||
Volume-6 Issue-1 | ||
Year of Publication : 2013 | ||
Authors :Gowder Praveena Hiriyan , A.Indhumathi |
Gowder Praveena Hiriyan , A.Indhumathi"A Modified Perceptual Constrained Spectral Weighting Technique For Speech Enhancement"International Journal of Computer Trends and Technology (IJCTT),V6(1):64-71 December Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- -Presently Speech Communication becomes active area in signal processing. Many approaches are developed previously for enhancing of speech. Perceptual speech enhancement methods perform better than the non perceptual methods, but most of them still return annoying residual musical noise. When noise above the noise masking threshold is filtered then noise below the noise masking threshold can become audible if its maskers are filtered is the main reason for residual noise. This affect the performance of perceptual speech enhancement method that process audible noise only. To overcome this drawback here proposed a new speech enhancement technique by modifying the Perceptual Wiener filter. The simulation results shows that the performance of this method which is improved when compared to other perceptual speech enhancement methods.
References:-
[1] . Ephraim Y and D. Malah, “Speech enhancement using a minimum mean square error short-time spectral amplitude estimator,” IEEE Trans. Acoust., Speech, Signal Processing,vol. ASSP-32, pp. 1109– 1121, Dec 1984.
[2] Schwartz R. M. Berouti and J. Makhoul, “Enhancement of speech corrupted by acoustic noise,” Proc. of ICASSP, 1979, vol. I, pp. 208–211
[3] Virag N, “Single channel speech enhancement based on masking properties of the human auditory system,” IEEE Trans. Speech and Audio Processing, vol. 7, pp. 126–137, 1999.
[4] Ephraim Y and H.L. Van Trees, “A signal subspace approach for speech enhancement,” IEEE Trans. Speech and Audio Processing, vol. 3, pp. 251–266, 1995
[5] Ephraim Y. “Statistical model based speech enhancement systems," Proc. IEEE, vol. 80, pp. 1526-1555, Oct. 1992.
[6] Atal B.S., Cuperman V and A.Gersho. Advances in Speech Coding. Kluwer Academic Publishers, 1991.
[7] Vaseghi S.V and B.P. Milner. “Noise Compensation Methods for Hidden Markov Model Speech Recognition in Adverse Environments”, IEEE Transactions on Speech and Audio Signal Processing, 5(1):11-21, Jan. 1997.
[8] H-Sameti. Model-Based Approaches to Speech Enhancement: Stationary State and Nonstationary-State HMMs. PhD thesis, University of Waterloo, Department of Electrical Engineering, 1994.
[9] Boll S.F. (1979). “Suppression of acoustic noise in speech using spectral subtraction”, IEEE Trans. Acoust. Speech Signal Process. 27, 113–120.
[10] Wittkop T and Hohmann V (2003) “Strategy selective noise reduction for binaural digital hearing aids,” Speech Commun. 39, 111–138
[11] Ephraim Y. “Statistical model based speech enhancement systems," Proc. IEEE, vol. 80, pp. 1526-1555, Oct. 1992.
[12] Doclo S and Moonen M. (2002). “GSVD-based optimal filtering forsingle and multi-microphone speech enhancement,” IEEE Trans. Signal Process. 50, 2230–2244.
[13] Doclo S, Klasen T. J, Van den Bogaert T, Wouters J and Moonen M (2006). “Theoretical analysis of binaural cue preservation using multichannel Wiener filtering and interaural transfer functions,” in Proceeding International Workshop on Acoustic Echo and Noise Control _IWAENC_, Paris, France, pp. 1– 4.
[14] Evans N.W.D, Mason J.S, Roach M.J. (2002). “Noise compensation using spectrogram morphological filtering”, In: Proc. 4th IASTED Internat. Conf. Signal Image Process, pp. 157–161.
[15] Yi Hu and Philipos C. Loizou, “Evaluation of Objective Quality Measures for Speech Enhancement,” IEEE Trans. on Audio, Speech and Language Processing, vol. 16, no. 1, pp. 229- 238, January 2008.
[16] Muni Kumar T, M.B.Rama Murthy , Ch.V.Rama Rao , K.Srinivasa Rao,’ A New Speech Enhancement Technique Using Perceptual Constrained Spectral Weighting Factors’, International Journal of Electronics Signals and Systems (IJESS), ISSN No. 2231- 5969, Volume-1, Issue-2, 2012
Keywords:-Signal to Noise Ratio (SNR), Perceptual Speech Enhancement, Perceptual Wiener filter (PWF), Wiener Filter, Perceptual Evaluation of Speech Quality Measure.