Hindi phoneme-viseme recognition from continuous speech
by A.N. Mishra; Mahesh Chandra; Astik Biswas; S.N. Sharan
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 6, No. 3, 2013

Abstract: Automatic Speech Recognition (ASR) system performs well under restricted conditions but the performance degrades under noisy environment. Audio-visual features play an important role in ASR systems in the presence of noise. In this paper, Hindi phoneme recognition system is designed using audio-visual features. The Discrete Cosine Transform (DCT) features of the lip region integrated with Mel Frequency Cepstral Coefficient (MFCC) audio features are used to get better recognition performance under noisy environments. Colour intensity, hybrid method and Pseudo-Hue methods have been used for lip-localisation approach with Linear Discriminant Analyser (LDA) as a classifier. Recognition performance using Pseudo-Hue method proved best among all the methods.

Online publication date: Fri, 13-Sep-2013

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