DocumentCode
528670
Title
Spoken language identification based on GMM models
Author
Dustor, Adam ; Szwarc, Pawel
Author_Institution
Inst. of Electron., Silesian Univ. of Technol., Gliwice, Poland
fYear
2010
fDate
7-10 Sept. 2010
Firstpage
105
Lastpage
108
Abstract
The paper describes application of gaussian mixture models GMM to the task of spoken language identification. The influence of the length of the test utterances on identification error rate was examined. During identification procedure recordings for 15 languages were used, both European and Asian ones. As a language model GMM with full covariance matrix was applied. Obtained results of identification error rate were discussed.
Keywords
Gaussian processes; covariance matrices; natural language processing; speech recognition; GMM models; Gaussian mixture models; covariance matrix; identification error rate; identification procedure recordings; language model GMM; spoken language identification; test utterances; Covariance matrix; Feature extraction; Read only memory; Speech; Speech recognition; Testing; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals and Electronic Systems (ICSES), 2010 International Conference on
Conference_Location
Gliwice
Print_ISBN
978-1-4244-5307-8
Electronic_ISBN
978-83-9047-4-2
Type
conf
Filename
5595243
Link To Document