Abstract
Automatic speech recognition system converts recorded audio speech signal into text output. Speech recognition has variety of applications in various domains. Hidden Markov Model (HMM) is widely used statistical approach in speech recognition system. The proposed work represents a speaker independent continuous speech recognition system for Indian English speakers using Hidden Markov Model Toolkit (HTK). Mel frequency cepstral coefficients (MFCC) are used as a feature vector. The results for automatic speech recognition system using HTK in different experiments are presented. These three different experiments includes cross-validation mode, without adapting HMMs and with adaptation of HMMs. Also the comparison in the accuracy of the recognized speech is discussed.
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