Abstract
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.
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Sneha, V., Hardhika, G., Jeeva Priya, K., Gupta, D. (2018). Isolated Kannada Speech Recognition Using HTK—A Detailed Approach. In: Saeed, K., Chaki, N., Pati, B., Bakshi, S., Mohapatra, D. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 564. Springer, Singapore. https://doi.org/10.1007/978-981-10-6875-1_19
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DOI: https://doi.org/10.1007/978-981-10-6875-1_19
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