Automatic language identification based on GMBM-UBBM

Gaussian mixture model is an effective method for speaker-independent language identification tasks. Gaussian mixture bigram model integrates bigram time correlation to extend the GMM. A language identification algorithm of GMBM-UBBM is proposed based on GMBM and GMM-UBM and some experiments are conducted using OGI-TS multilanguage telephone speech corpus. Simulation results demonstrate the effectiveness of GMBM-UBBM for language identification tasks and use of this model allows the proposed system to distinguish between the three languages with maximal 4.378% improvement accuracy superior to conventional GMM-UBM.