This paper presents an evaluation of a robust Voiced-Unvoiced-based large-vocabulary Continuous-Speech Recognition (CSR) system in the presence of highly interfering noise. Comparative experiments have indicated that the inclusion of an accurate Voiced-Unvoiced (V-U) classifier in our design of a CSR system improves the performance of such a recognizer, for speech contaminated by both additive Gaussian and uniform noises. Our results show that the V-U-based CSR system outperforms the CMS-based and the RASTA-PLP-based CSR systems in such environments for a wide range of SNRs.
Cite as: Tolba, H., O'Shaughnessy, D. (1998) Comparative experiments to evaluate a voiced-unvoiced-based pre-processing approach to robust automatic speech recognition in low-SNR environments. Proc. 5th International Conference on Spoken Language Processing (ICSLP 1998), paper 0341, doi: 10.21437/ICSLP.1998-341
@inproceedings{tolba98_icslp,
author={Hesham Tolba and Douglas O'Shaughnessy},
title={{Comparative experiments to evaluate a voiced-unvoiced-based pre-processing approach to robust automatic speech recognition in low-SNR environments}},
year=1998,
booktitle={Proc. 5th International Conference on Spoken Language Processing (ICSLP 1998)},
pages={paper 0341},
doi={10.21437/ICSLP.1998-341}
}