DocumentCode :
2696842
Title :
Efficient Language Identification using Anchor Models and Support Vector Machines
Author :
Noor, Elad ; Aronowitz, Hagai
Author_Institution :
Weizmann Inst. of Sci., Rehovot
fYear :
2006
fDate :
28-30 June 2006
Firstpage :
1
Lastpage :
6
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
Keywords :
natural languages; speaker recognition; speech processing; support vector machines; LID; NIST-2003; anchor model; language identification; speaker identification; speaker indexing; speech utterance; support vector machine; Computer science; Data mining; Databases; Error analysis; Indexing; Natural languages; Speech; Support vector machine classification; Support vector machines; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Speaker and Language Recognition Workshop, 2006. IEEE Odyssey 2006: The
Conference_Location :
San Juan
Print_ISBN :
1-424400471-1
Electronic_ISBN :
1-4244-0472-X
Type :
conf
DOI :
10.1109/ODYSSEY.2006.248101
Filename :
4013518
Link To Document :
بازگشت