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2012 (Vol. 4, Issue: 1)
Article Information:

Parameter Compensation for Mel-LP based Noisy Speech Recognition

Md. Mahfuzur Rahman, Md. Robiul Hoque and M. Babul Islam
Corresponding Author:  M. Babul Islam 

Key words:  Aurora-2 database, BEQ, bilinear transformation, CMN, Mel-LPC, ,
Vol. 4 , (1): 7-12
Submitted Accepted Published
2011 July, 13 2011 August, 30 2012 March, 10

This study deals with a noise robust distributed speech recognizer for real-world applications by deploying feature parameter compensation technique. To realize this objective, Mel-LP based speech analysis has been used in speech coding on the linear frequency scale by applying a first-order all-pass filter instead of a unit delay. To minimize the mismatch between training and test phases, Cepstral Mean Normalization (CMN) and Blind Equalization (BEQ) have been applied to enhance Mel-LP cepstral coefficients as an effort to reduce the effect of additive noise and channel distortion. The performance of the proposed system has been evaluated on Aurora-2 database which is a subset of TIDigits database contaminated by additive noises and channel effects. The baseline performance, that is, for Mel-LPC the average word accuracy for test set A has found to be 59.05%. By applying the CMN and BEQ with the Mel-LP cepstral coefficients, the performance has been improved to 68.02 and 65.65%, respectively.
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  Cite this Reference:
Md. Mahfuzur Rahman, Md. Robiul Hoque and M. Babul Islam, 2012. Parameter Compensation for Mel-LP based Noisy Speech Recognition.  Research Journal of Information Technology , 4(1): 7-12.
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ISSN (Online):  2041-3114
ISSN (Print):   2041-3106
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