International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 58 - Number 10 |
Year of Publication: 2012 |
Authors: Md. Mahfuzur Rahman, Sanjit Kumar Saha, Md. Zakir Hossain, Md. Babul Islam |
10.5120/9316-3548 |
Md. Mahfuzur Rahman, Sanjit Kumar Saha, Md. Zakir Hossain, Md. Babul Islam . Performance Evaluation of CMN for Mel-LPC based Speech Recognition in Different Noisy Environments. International Journal of Computer Applications. 58, 10 ( November 2012), 6-10. DOI=10.5120/9316-3548
This study is intended to develop a noise robust distributed speech recognizer for real-world applications by employing Cepstral Mean Normalization (CMN) for robust feature extraction. The main focus of the work is to cope with different noisy environments. 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. Mismatch between training and test phases is reduced through robust feature extraction by applying CMN on Mel-LP cepstral coefficients as an effort to reduce additive noise and channel distortion. The performance of the proposed system has been evaluated on test set A of Aurora-2 database which is a subset of TIDigits database contaminated by additive noises and channel effects. The experiment is conducted on four different noisy environments and the baseline performance, that is, for Mel-LPC the average word accuracy has found to be 59. 05%. By applying the CMN on Mel-LP cepstral coefficients, the performance has been improved to 68. 02%. It is found that CMN performs significantly better for different noisy environments.