In this paper, to find the best noise robustness approach, we study on approaches implemented at both-end (i.e. front-end and back-end) of speech recognition system. To reduce the noise with lower speech distortion at front-end, we investigate the Two-stage Mel-warped Wiener Filtering (TMWF) in the integrated Parallel Model Combination (PMC) approach. Furthermore, the first-stage of TMWF (i.e. One-stage Mel-warped Wiener Filtering (OMWF)), as well as the well-known Wiener Filtering (WF), is effective to reduce the noise, so we integrate PMC with those front-end noise reduction approaches. From the recognition performance, TMWF-PMC shows improved performance comparing with the well-known WF-PMC, and OMWF-PMC also shows a comparable performance in all noises.
Cite as: Shen, G., Suk, S.-Y., Chung, H.-Y. (2009) Performance comparisons of the integrated parallel model combination approaches with front-end noise reduction. Proc. Interspeech 2009, 2387-2390, doi: 10.21437/Interspeech.2009-365
@inproceedings{shen09_interspeech,
author={Guanghu Shen and Soo-Young Suk and Hyun-Yeol Chung},
title={{Performance comparisons of the integrated parallel model combination approaches with front-end noise reduction}},
year=2009,
booktitle={Proc. Interspeech 2009},
pages={2387--2390},
doi={10.21437/Interspeech.2009-365}
}