The aim of this paper is to present and evaluate two adaptive speech enhancement methods in the frequency domain by measuring the recognition rate of a speaker-independent word recognition system of isolated words. In a hands-free speech recognition experiment, a factory noise source and a speaker are the acoustic sources in a real room environment. A close-talking microphone is positioned near the noise source while the primary omni-directional microphone captures the convoluted speech and noise signals. Adaptive noise cancellation reduces the presence of noise in the primary microphone followed by a blind deconvolution algorithm used to minimize reverberations. Experimental results showed that the proposed speech enhancement methods increase 2.4 times the recognition rate for a vocabulary of 21 words of the Greek language, but the achieved recognition rate of 16% is inapplicable for commercial applications.
Cite as: Nokas, G., Dermatas, E. (1999) Speech recognition in noisy reverberant rooms using a frequency domain blind deconvolution method. Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999), 2853-2856, doi: 10.21437/Eurospeech.1999-631
@inproceedings{nokas99_eurospeech,
author={G. Nokas and E. Dermatas},
title={{Speech recognition in noisy reverberant rooms using a frequency domain blind deconvolution method}},
year=1999,
booktitle={Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999)},
pages={2853--2856},
doi={10.21437/Eurospeech.1999-631}
}