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.
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.
|EPrint Type:||Conference or Workshop Item (Paper)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Deposited By:||Hagai Aronowitz|
|Deposited On:||22 November 2006|