HMM based isolated Kannada digit recognition system using MFCC

H. Muralikrishna, T. Ananthakrishna, Kumara Shama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
Pages730-733
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 - Mysore, India
Duration: 22-08-201325-08-2013

Conference

Conference2013 2nd International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013
CountryIndia
CityMysore
Period22-08-1325-08-13

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

Cite this

Muralikrishna, H., Ananthakrishna, T., & Shama, K. (2013). HMM based isolated Kannada digit recognition system using MFCC. In Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013 (pp. 730-733). [6637264] https://doi.org/10.1109/ICACCI.2013.6637264