Vocal tract length normalization and sub-band spectral subtraction based robust assamese vowel recognition system

In this paper, vocal tract length normalization (VTLN) and sub-band spectral subtraction (SSS) have been used for speaker adaptation and noise reduction to develop an Assamese vowel recognition system which is robust to the speaker and environment variabilities. In the present work VTLN has been implemented to reduce the effects of inter speaker variabilities and sub-band spectral subtraction has been used to reduce the effects of environmental variabilities. The effectiveness of VTLN in noisy and noise-free environment has been evaluated for Assamese vowel recognition system. The Assamese vowel recognition system has been implemented using Hidden Markov Model (HMM). Mel Frequency Cepstral Coefficient (MFCC) has been used as feature vector. Experimented result shows that the performance of the system improved considerably after applying VTLN technique in noise-free and some of the noisy conditions.