Title :
HMM based isolated Kannada digit recognition system using MFCC
Author :
Muralikrishna, H. ; Ananthakrishna, T. ; Shama, Kumara
Author_Institution :
Dept. of E&C, MIT, Manipal, India
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.
Keywords :
hidden Markov models; natural language processing; speech recognition; HMM based isolated Kannada digit recognition system; K-means procedure; Kannada language; Mel frequency cepstral coefficients; discrete HMM; feature vector; first order derivatives; hidden Markov model; isolated utterances recognition; observation sequence; pattern recognition; second order derivatives; voice controlled machine; Data models; Feature extraction; Hidden Markov models; Mel frequency cepstral coefficient; Speech; Speech processing; Speech recognition; Hidden Markov Model (HMM); Kannada language; Mel frequency cepstral coefficients (MFCC); speech recognition; vector quantization;
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4799-2432-5
DOI :
10.1109/ICACCI.2013.6637264
