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Robust Language Classification on Short Utterances

Publication Date : 02/05/2016

Author(s) :

Ms. Snehal V.Gite , Prof. J.V.Shinde.

Conference Name :
International Conference on Recent Trends in Engineering and Technology

Abstract :

Automatic Language Identification is the process of classifying spoken words as belonging to one of a number of previously encountered languages. Achieving accurate performance with the shortest possible speech segment in a robust fashion is the main challenge in language identification. The proposed system works on robust language identification that involves rapid learning of new language identities and reduce the computational complexity. The proposed approach that transforms the spoken words to a low dimensional i-vector representation on which classification methods are applied. Universal background model (UBM) and i-vector extraction is used in proposed system in order to meet the challenges involved in rapidly making reliable decisions about the spoken language. By the deployment of a robust feature extraction scheme that capture the relevant language under acoustic conditions.

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