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 [BibTeX] [Marc21]
Entropy Based Combination of Tandem Representations for Noise Robust ASR
Type of publication: Idiap-RR
Citation: ikbal-rr-04-19
Number: Idiap-RR-19-2004
Year: 2004
Institution: IDIAP
Address: Martigny, Switzerland
Abstract: In this paper, we present an entropy based method to combine tandem representations of the recently proposed Phase AutoCorrelation (PAC) based features and Mel-Frequency Cepstral Coefficients (MFCC) features. PAC based features, derived from a nonlinear transformation of autocorrelation coefficients and shown to be noise robust, improve their robustness to additive noise in their tandem representation. On the other hand, MFCC features in their tandem representation show a significant improvement in recognition performance on clean speech. An entropy based combination method investigated in this paper adaptively gives a higher weighting to the representation of MFCC features in clean speech and to the representation of PAC based features in noisy speech, thus yielding a robust recognition performance in all conditions.
Userfields: ipdinar={2004}, ipdmembership={speech}, language={English},
Projects Idiap
Authors Ikbal, Shajith
Misra, Hemant
Sivadas, Sunil
Hermansky, Hynek
Bourlard, Hervé
Crossref by ikbal-rr-04-19p
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