Performance Improvement of Automatic Language Identification Using GMM-SVM Method

GMM is one of the most successful models in the field of automatic language identification. In this paper we have proposed a new model named adapted weight GMM (AW-GMM). This model is similar to GMM but the weights are determined using GMM-VSM LID system based on the power of each component in discriminating one language from the others. Also considering the computational complexity of GMM-VSM، we have proposed a technique for constructing bigram sequences of components which could be used for higher sequence orders and decreases the complexity. Experiments on four languages of OGI corpus including English، Farsi، French and German have shown the effectiveness of proposed techniques.