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Speech Recognition System For North-East Indian Accent

Moirangthem Tiken Singh, Abdur Razzaq Fayjie, Biswajeet Kachari Published in Signal Processing

International Journal of Applied Information Systems
Year of Publication: 2015
© 2015 by IJAIS Journal
10.5120/ijais15-451398
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  1. Moirangthem Tiken Singh, Abdur Razzaq Fayjie and Biswajeet Kachari. Article: Speech Recognition System For North-East Indian Accent. International Journal of Applied Information Systems 9(4):1-9, July 2015. BibTeX

    @article{key:article,
    	author = "Moirangthem Tiken Singh and Abdur Razzaq Fayjie and Biswajeet Kachari",
    	title = "Article: Speech Recognition System For North-East Indian Accent",
    	journal = "International Journal of Applied Information Systems",
    	year = 2015,
    	volume = 9,
    	number = 4,
    	pages = "1-9",
    	month = "July",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

Speech recognition is the process of converting an acoustic waveform into the text containing the similar information conveyed by the speaker. This paper presents a speech recognition system for English digits in Indian (especially North Eastern) accent. Hidden Markov Model Tool kit (HTK-3. 4. 1) is chosen to implement the Hidden Markov Model as classifier with several set of Hidden Markov Model mixture. Mel Frequency Cepstral Coefficients are used as speech features. Experiments were performed for data collected in natural noise environment. The performance is evaluated using recognition rate. Hidden Markov Model state numbers and number of mixtures are investigated and possible directions for future research work are suggested.

Reference

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Keywords

Regional accent, HMM, HMM mixture, MFCC