Effects of Different coefficients on MFCC and PLP for Bangla Speech Corpus using Tied-state Triphone Model

This paper has observed the effects of different coefficients for MFCC and PLP feature extraction techniques for Bangla corpus System. We have first observed the effects of 12 coefficients for every 10 ms frames, and then added the delta and accelerating coefficients to get 24 and 36 coefficient vectors per frame respectively. Then we have also observed the effect of appending the power coefficient and its first and second derivative while getting a 39 coefficient feature vector per frame. In addition, we have further appended 13 third differential coefficients to make a vector set of 52 coefficients per frame to observe the effect of third differential coefficients too. From the experimental results, we have observed that for gender unbiased models, delta addition has shown the maximum detection both for speaker dependent and independent system. But for speaker independent gender biased models, acceleration, power, and third differential coefficients addition have increased the detection for both MFCC and PLP in noise-free audio samples with the sampling rate of 44.1 KHz.