HINDI SPEECH RECOGNITION TECHNIQUE USING HTK

This paper is based on SR system. In the speech recognition process computer takes a voice signal which is recorded using a microphone and converted into words in real - time. This SR system has been developed using different feature extraction techniques wh ich include MFCC, HMM. All are used as the classifier. ASR i.e . automated speech recognition is program or we can called it as a machine, and it has ability to recognize the voice signal (speech signal or voice commands) or take dictation which involves th e ability to match a voice pattern opposite to a given vocabulary. HTK i.e . The Hidden Markov model Toolkit is used to develop the SR System. HMM consist of the Acoustic word model which is used to recognize the isolated word. In this paper , we collect Hi ndi database, with a vocabulary size a bit extended. HMM has been implemented using the HTK Toolkit.