This paper aims to discuss the development of an isolated word recognizer for the Indian language Kannada. The word recognizer is built using HTK, which is based on HMM. The system is trained using triphone HMMs for Kannada words in open space environment from 10 speakers and tested using data from 4 speakers. This paper also gives a comparison of results between MFCC and LPCC techniques for four different test sets. © Springer Nature Singapore Pte Ltd. 2018.
cited By 0; Conference of International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2016 ; Conference Date: 23 December 2016 Through 25 December 2016; Conference Code:208989
V. Sneha, Hardhika, G., K. Priya, J., and Gupta, D., “Isolated Kannada speech recognition using HTK—A detailed approach”, Advances in Intelligent Systems and Computing, vol. 564, pp. 185-194, 2018.