Linear Predictive Coding and Cepstral Analysis for Telugu Speech Recognition

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-47 Number-1
Year of Publication : 2017
Authors : P. Jeethendra, M. Chandrashekar
DOI :  10.14445/22312803/IJCTT-V47P106


P. Jeethendra, M. Chandrashekar "Linear Predictive Coding and Cepstral Analysis for Telugu Speech Recognition". International Journal of Computer Trends and Technology (IJCTT) V47(1):50-60, May 2017. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
This research work focused on feature extraction of in speech signal applied to Telugu Language processing. Telugu is a third largest spoken Indian Language which is widely spoken in Southern Indian States of India Talangana and Andhra Pradesh. Telugu is spoken in different accents even in the Telugu speaking geographic area. The feature extraction becomes more challenging when it is for a speaker independent speech recognition in nature. Every languages having different speaking styles called as accents or dialects. Identification of the accent before the speech recognition can improve performance of Speech recognition system. If the number of accents are more, then this becomes a crucial part of the study. If we can understand the different sources of variability in the signal accent then we can begin to approach the problem by separating them out in subsequent analysis stages Speech signal is analyzed in two ways – signal Processing and linguistic processing. During linguistic processing, signals are cut into chunks of varying degrees of abstraction such as acoustic-phonetic segments(APS), allophones, phonemes, morphophonemic, etc, which will be ultimately correlated with the letters in the script of a language by computational technique. Among the various techniques presently available in speech processing technology such as Fast Fourier Transforms, Linear Predictive Coding, Mel Frequency Cepstral Coefficients, Cepstral Analysis, Discrete Wavelet Transforms, Wavelet Packet Transforms, Hybrid Algorithm DWPD and their applications in speech processing, we have studied, Out of these LPC and Cepstral Analysis in this research work.

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Feature extraction, Speaker Independent, Linear Predictive Coding (LPC), Cepstral Analysis, Telugu, Acoustic Phonetic Segments (APS).