Isolated to connected Tamil digit speech recognition system based on hidden Markov model

Abstract

Speech recognition technology has improved with time to enhanced Human Computer Interaction (HCI).This paper proposed a system for isolated to connected Tamil digit speech recognition system using CMU Sphinx tools. The connected speech recognition important in many application such as voice-dialling telephone, automated banking system automated data entry, pin entry etc. the proposed system is tri phone based, small vocabularies, speaker specific and speaker-independent. The most powerful Mel Frequency Cepstral Coefficient (MFCC) feature extraction techniques are used to train the acoustic feature of speech database. The probabilistic Hidden Markov Model (HMM) is used to model the speech utterance. And the Viterbi beam search algorithm is used in decoding process. The system tested with random digit (0 to 100) in a various condition shows optimum result 96.7% recognition rates for speaker specific and 54.5% recognition rate for speaker independent in connected word recognition. We use CMU sphinx speech recognition tools to construction of speech recognizer.