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Improved Jacobian Adaptation for Robust Speaker Verification

Jan ANGUITA, Javier HERNANDO, Alberto ABAD

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Summary :

Jacobian Adaptation (JA) has been successfully used in Automatic Speech Recognition (ASR) systems to adapt the acoustic models from the training to the testing noise conditions. In this work we present an improvement of JA for speaker verification, where a specific training noise reference is estimated for each speaker model. The new proposal, which will be referred to as Model-dependent Noise Reference Jacobian Adaptation (MNRJA), has consistently outperformed JA in our speaker verification experiments.

Publication
IEICE TRANSACTIONS on Information Vol.E88-D No.7 pp.1767-1770
Publication Date
2005/07/01
Publicized
Online ISSN
DOI
10.1093/ietisy/e88-d.7.1767
Type of Manuscript
LETTER
Category
Speech and Hearing

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