Spoken Word Recognition Strategy for Tamil Language
This paper outlines a strategy for recognizing a preferred
vocabulary of words spoken in Tamil language. The basic philosophy is to extract the features using mel frequency cepstral coefficients (MFCC) from the spoken words that are used as representative features of the speech to create models that aid in recognition. The models chosen for the task are hidden Markov models (HMM) and autoassociative neural networks (AANN). The HMM is used to model the temporal nature of speech and the AANNs to capture the distribution of feature vectors in the feature space. The created models provide a way to investigate an unexplored speech recognition arena for the Tamil language. The performance of the strategy is evaluated for a number of test utterances through HMM and AANN and the results project the reliability of HMM for emerging applications in regional languages.
Keywords: Speech recognition, Mel frequency cepstral coefficients, Hidden Markov models, Autoassociative neural networks.
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ABOUT THE AUTHORS
An. Sigappi
AN. Sigappi received her Bachelors degree in Computer Science and Engineering from Annamalai University in 1993 and her Masters degree in the same discipline from Anna University in 2001. She is currently pursuing her doctoral research work at Annamalai University. Her career includes both administrative and academic experience spanning over 15 years and she is presently working as Associate Professor in the Department of Computer Science and Engineering at Annamalai University. Her research interest includes speech and image processing, software engineering, management information systems and intelligent systems.
S. Palanivel
S. Palanivel received the B.E(Hons) degree in Computer Science and Engineering from Bharathidasan University in 1989 and followed it up with Masters degree in the same discipline from Bharathiar University in 1994. He completed his Ph.D in Computer Science and Engineering from the Indian Institute of Technology Madras in the year 2005. He is currently serving as Associate Professor in Computer Science and Engineering at Annamalai University. He carries with him 17 years of teaching experience and over 20 publications in international conferences and journals. His research interests include speech processing, image and video processing, pattern classification and neural networks.
An. Sigappi
AN. Sigappi received her Bachelors degree in Computer Science and Engineering from Annamalai University in 1993 and her Masters degree in the same discipline from Anna University in 2001. She is currently pursuing her doctoral research work at Annamalai University. Her career includes both administrative and academic experience spanning over 15 years and she is presently working as Associate Professor in the Department of Computer Science and Engineering at Annamalai University. Her research interest includes speech and image processing, software engineering, management information systems and intelligent systems.
S. Palanivel
S. Palanivel received the B.E(Hons) degree in Computer Science and Engineering from Bharathidasan University in 1989 and followed it up with Masters degree in the same discipline from Bharathiar University in 1994. He completed his Ph.D in Computer Science and Engineering from the Indian Institute of Technology Madras in the year 2005. He is currently serving as Associate Professor in Computer Science and Engineering at Annamalai University. He carries with him 17 years of teaching experience and over 20 publications in international conferences and journals. His research interests include speech processing, image and video processing, pattern classification and neural networks.