期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：6
出版社：IJCSI Press
摘要：Speaker verification system shows poor performance when speaker model training is done in one language and the testing in another language. This is a major problem in multilingual speaker verification system. In this paper, we report the experiment carried out on a recently collected multilingual and multichannel speaker recognition database to study the impact of language variability on speaker verification system. The speech database consists of speech data recorded from 200 speakers with Arunachali languages of North-East India as mother tongue. The speech samples are collected in three different languages English, Hindi and a local language of Arunachal Pradesh. The collected database is evaluated with Gaussian Mixture Model based speaker verification system using universal background model (UBM) for alternative speaker representation and Mel-Frequency Cepstral Coefficients (MFCC) as a front end feature vectors. The impact of the mismatch in training and testing languages have been evaluated.
