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ISOLATED WORDS RECOGNITION USING MFCC, LPC AND NEURAL NETWORK
Mayur R Gamit, Kinnal Dhameliya
Abstract: Automatic speech recognition is an important topic of speech processing. This paper presents the use of an Artificial Neural Network (ANN) for isolated word recognition. The Pre-processing is done and voiced speech is detected based on energy and zero crossing rates (ZCR). The proposed approach used in speech recognition is Mel Frequency Cepstral Coefficients (MFCC) and combine features of both MFCC and Linear Predictive Coding (LPC). The back-propagation is used as a classifier. The recognition accuracy is increased when combine features of both LPC and MFCC are used as compared to only MFCC approach using Neural Network as a classifier
Keywords: Pre-processing, Mel frequency Cepstral Coefficient (MFCC), Linear Predictive Coding (LPC), Artificial Neural Network (ANN).
DOI: https://doi.org/10.15623/ijret.2015.0406024
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