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Conference Papers Year : 2003

Towards Missing Data Recognition with Cepstral Features

Abstract

We study in this work the Missing Data Recognition (MDR) framework applied to a large vocabulary continuous speech recognition (LVCSR) task with cepstral models when the speech signal is corrupted by musical noise. We do not propose a full system that solves this difficult problem, but we rather present some of the issues involved and study some possible solutions to them. We focus in this work on the issues concerning the application of masks to cepstral models. We further identify possible errors and study how some of them affect the performances of the system.
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Dates and versions

inria-00107648 , version 1 (19-10-2006)

Identifiers

  • HAL Id : inria-00107648 , version 1

Cite

Christophe Cerisara. Towards Missing Data Recognition with Cepstral Features. 8th European Conference on Speech Communication and Technology - EUROSPEECH'03, Sep 2003, Geneva, Switzerland, 4 p. ⟨inria-00107648⟩
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