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Communication Dans Un Congrès Année : 2006

Unsupervised model adaptation for speaker verification

Résumé

This paper deals with unsupervised model adaptation for speaker recognition. Two adaptation schemes are proposed, the first one is based on a test by test model adaptation and the second one proposes a batch mode, where the adaptation is performed using a set of tests before computing the decision score for each of them. The experiments are conducted thanks to the NIST SRE 2005 database. This paper shows clearly the interest of unsuper-vised model adaptation when enough test data is available (batch mode) and the intrinsic difficulty of an online (test by test) adaptation mode.
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Dates et versions

hal-01311548 , version 1 (04-05-2016)

Identifiants

  • HAL Id : hal-01311548 , version 1

Citer

Alexandre Preti, Jean-François Bonastre. Unsupervised model adaptation for speaker verification. Interspeech, 2006, Pittsburgh, United States. ⟨hal-01311548⟩

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