Large Vocabulary Continuous Speech Recognition System for Marathi

Lots of efforts have been made in the development of Automatic Speech Recognition systems for Indian languages, and good progress has been made for Hindi, Tamil, Telugu & Bengali, and Indian English. However, practically usable robust systems are still not available for many regional Indian languages including Marathi. This paper presents an effort toward the development of a large vocabulary continuous speech recognition system for Marathi and its integration into practical application, such as Speech-based typing system. This speech recognition system has been developed using the Kaldi toolkit. The Kaldi toolkit facilitates the exploration of different acoustic models such as Gaussian Mixture Model with Hidden Markov Model (GMM-HMM) and Deep Neural Networks with Hidden Markov Model (DNN-HMM). In this paper we have developed Marathi Speech Recognition system which is trained around 95 hours of audio data. We have used the trigram language model which is having 29 lakhs of words and 3 lakhs of vocabulary size. This system gives average word error rate of 19%.