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March 2014 Volume.1 Issue.1
 
’Shreshta Bhasha’ Malayalam Speech Recognition using HTK
International Journal of Advanced Computing and Communication Systems (IJACCS)
© 2014 by IJACCS Journal
Volume - 1, Issue - 1
Year of Publication: March 2014
Author's: Smrithy K Mukundan Paper ID: IJCS122
 
Full Text
 
Citation
Smrithy K Mukundan. ’Shreshta Bhasha’ Malayalam Speech Recognition using HTK International Journal of Advanced Computing and Communication Systems (IJACCS). Volume.1 Issue.1 March 2014.
 
Abstract
This paper is aimed to discuss the development of an isolated, speaker independent word Automatic Speech Recognition system (ASR) for an Indian regional language Malayalam. The implementation of the system has been done using Hidden Markov Model Toolkit (HTK) with Hidden Markov Model (HMM) for acoustic modeling and Mel-Frequency Cepstral Coefficient (MFCC) for feature extraction. The system was trained with 21 speakers (8 male, 8 female and 5 children) in the age group ranging from 4 to 76 years. The database included 210 isolated spoken words recorded from 21 speakers. Each speaker uttered Malayalam words for the numbers 0 (‘poojyam’) to 9 (‘onpathu’) separately. For training and testing the system, the data base was divided into three equal parts and the experiment was conducted for both speaker dependence and speaker independence. And as an extension, a speech to text (STT) system was made using the decoder software JULIUS.
 
References
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Keywords
Automatic Speech Recognition system (ASR), Wave surfer, Mel Frequency Cepstral Coefficient (MFCC), HMM, HTK, JULIUS
 

 

 
 
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