Development of Application Specific Continuous Speech Recognition System in Hindi


Application specific voice interfaces in local languages will go a long way in reaching the benefits of technology to rural India. A continuous speech recognition system in Hindi tailored to aid teaching Geometry in Primary schools is the goal of the work. This paper presents the preliminary work done towards that end. We have used the Mel Frequency Cepstral Coefficients as speech feature parameters and Hidden Markov Modeling to model the acoustic features. Hidden Markov Modeling Tool Kit —3.4 was used both for feature extraction and model generation. The Julius recognizer which is language independent was used for decoding. A speaker independent system is implemented and results are presented.

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G. Gaurav, D. Deiv, G. Sharma and M. Bhattacharya, "Development of Application Specific Continuous Speech Recognition System in Hindi," Journal of Signal and Information Processing, Vol. 3 No. 3, 2012, pp. 394-401. doi: 10.4236/jsip.2012.33052.

Conflicts of Interest

The authors declare no conflicts of interest.


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