Title :
Spoken language identification based on GMM models
Author :
Dustor, Adam ; Szwarc, Pawel
Author_Institution :
Inst. of Electron., Silesian Univ. of Technol., Gliwice, Poland
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;
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
