Tom Claes

Tom Claes
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Main area of research
Speech recognition

Selected articles

A novel feature transformation for vocal tract length normalisation in automatic speech recognition

This paper proposes a method to transform acoustic models that have been trained with a certain group of speakers for use on different speech in

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Speaker normalization for automatic speech recognition – an on-line approach

We propose a method to transform the on line speech signal so as to comply with the specifications of an HMM-based automatic speech recognizer. The

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New transformations of Cepstral parameters for automatic vocal tract length normalization in speech recognition

This paper proposes a method to transform acoustic modĀ­els (HMM gaussian mixtures) that have been trained on a certain group of speakers for use on

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Spectral estimation and normalisation for robust speech recognition

Speech recognition in adverse conditions remains a difficult but challenging problem. It has already been shown that normalization of the dynamic range (SNR) of the

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SNR-normalisation for robust speech recognition

A new normalization technique for speech recognition in adverse conditions is presented. Specifically the influence of additive noise in combination with convolutive distortions is considered.

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