Hindi Automatic Speech Recognition Using HTK

  ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2013 by IJETT Journal
Volume-4 Issue-6                      
Year of Publication : 2013
Authors : Preeti Saini , Parneet Kaur , Mohit Dua

Citation 

Preeti Saini , Parneet Kaur , Mohit Dua. "Hindi Automatic Speech Recognition Using HTK". International Journal of Engineering Trends and Technology (IJETT). V4(6):2223-2229 Jun 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.

Abstract

Automated Speech Recognition (ASR) is the ability of a machine or program to recognize the voice commands or take dictation which involves the ability to matc h a voice pattern against a provided or acquired vocabulary. At present , mainly Hidden Markov Model (HMMs) based speech recognizers are used. This paper aims to build a speech recognition system for Hindi language. Hidden Markov Model Toolkit (HTK) is used to develop the system. It recognizes the isolated words using acoustic word model. The system is trained for 113 Hindi words. Training data has been collected from nine speakers. The experimental results show that the overall accuracy of the presented sys tem with 10 states in HMM topology is 96.61 and 95.49 %

References

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Keywords
HMM; HTK; Mel Frequency Cepstral Coefficient (MFCC); Automatic Speech Recognition (ASR); Hindi; Isolated word ASR .