R. Mathur, Babita and A. Kansal, “Domain Specific Speaker Independent Continuous Speech Recognition Using Julius,” ASCNT 2010.

has been cited by the following article:

• TITLE: Development of Application Specific Continuous Speech Recognition System in Hindi

  AUTHORS: Gaurav Gaurav, Devanesamoni Shakina Deiv, Gopal Krishna Sharma, Mahua Bhattacharya

  KEYWORDS: Automatic Speech Recognition; Mel Frequency Cepstral Coefficients; Hidden Markov Modeling

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.3 No.3, August 31, 2012

  ABSTRACT: 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.