HMM based isolated Kannada digit recognition system using MFCC

Abstract

In this paper we have implemented Kannada isolated digit recognition system using Mel frequency cepstral coefficients (MFCC) as feature vector. The system is designed to recognize isolated utterances of Kannada numbers. MFCC are used as the features and Hidden Markov Model (HMM) as pattern recognizer. K-means procedure is performed on the feature vectors to obtain the observation sequence. Discrete HMM is used in the system. The system is developed by considering the requirement of a voice controlled machine in Kannada language. Performance of the system is evaluated and compared based on the MFCC along with its first and second order derivatives.