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Speaker normalization for template based speech recognition

Sébastien Demange 1 Dirk van Compernolle
1 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Vocal Tract Length Normalization (VTLN) has been shown to be an efficient speaker normalization tool for HMM based systems. In this paper we show that it is equally efficient for a template based recognition system. Template based systems, while promising, have as potential drawback that templates maintain all non phonetic details apart from the essential phonemic properties; i.e. they retain information on speaker and acoustic recording circumstances. This may lead to a very inefficient usage of the database. We show that after VTLN significantly more speakers - also from opposite gender - contribute templates to the matching sequence compared to the non-normalized case. In experiments on the Wall Street Journal database this leads to a relative word error rate reduction of 10%.
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https://hal.inria.fr/inria-00583853
Contributor : Sébastien Demange <>
Submitted on : Wednesday, April 6, 2011 - 5:57:27 PM
Last modification on : Thursday, January 11, 2018 - 6:19:56 AM

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  • HAL Id : inria-00583853, version 1

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Sébastien Demange, Dirk van Compernolle. Speaker normalization for template based speech recognition. 10th Annual Conference of the International Speech Communication Association - Interspeech 2009, Sep 2009, Brighton, United Kingdom. pp.560--563. ⟨inria-00583853⟩

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