Robust Feature-Estimation and Objective Quality Assessment for Noisy Speech Recognition using the Credit Card Corpus (1994)
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BibTeX
@MISC{Hansen94robustfeature-estimation,
author = {John H.L. Hansen and Levent M. Arslan},
title = {Robust Feature-Estimation and Objective Quality Assessment for Noisy Speech Recognition using the Credit Card Corpus},
year = {1994}
}
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Abstract
It is well known that the introduction of acoustic background distortion into speech causes recognition algorithms to fail. In order to improve the environmental robustness of speech recognition in adverse conditions, a novel constrained-iterative feature-estimation algorithm, which was previously formulated for speech enhancement, is considered and shown to produce improved feature characterization in a variety of actual noise conditions such as computer fan, large crowd, and voice communications channel noise. In addition, an objective measure based MAP estimator is formulated as a means of predicting changes in robust recognition performance at the speech feature extraction stage. The four measures considered include (i) NIST SNR, (ii) Itakura-Saito log-likelihood, (iii) log-area-ratio, and (iv) the weighted-spectral slope measure. A continuous distribution, monophone based, hidden Markov model recognition algorithm is used for objective measure based MAP estimator analysis and reco...
