PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Efficient language Identification using Anchor Models and Support Vector Machines
Elad Noor and Hagai Aronowitz
In: ODYSSEY 2006, 28-30 June 2006, San Juan, Puerto Rico.

Abstract

Anchor models have been recently shown to be useful for speaker identification and speaker indexing. The advantage of the anchor model representation of a speech utterance is its compactness (relative to the original size of the utterance) which is achieved with only a small loss of speaker-relevant information. This paper shows that speaker-specific anchor model representation can be used for language identification as well, when combined with support vector machines for doing the classification, and achieve state-of-the-art identification performance. On the NIST-2003 Language Identification task, it has reached an equal error rate of 4.8%for 30 second test utterances.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Speech
ID Code:2685
Deposited By:Hagai Aronowitz
Deposited On:22 November 2006