This paper accounts the performance of the Hidden Markov Model (HMM) decomposition recognition algorithm for speech recognition in a number of stationary and non-stationary background noises. Speaker dependent and speaker independent digit recognition tasks are evaluated and the results are also compared with those of a similar 'model adaptation to noise' scheme.
Cite as: Kadirkamanathan, M. (1992) Hidden Markov model decomposition recognition of speech in noise: a comprehensive experimental study. Proc. ETRW on Speech Processing in Adverse Conditions, 187-190
@inproceedings{kadirkamanathan92_spac,
author={M. Kadirkamanathan},
title={{Hidden Markov model decomposition recognition of speech in noise: a comprehensive experimental study}},
year=1992,
booktitle={Proc. ETRW on Speech Processing in Adverse Conditions},
pages={187--190}
}