An automatic language identification method based on subspace analysis

Gaussian mixture models (GMM) have become one of the standard acoustic approaches for language identification. Furthermore, the GMM-SVM is proven to work well by introducing the discriminative method into the GMM-based acoustic systems. In these systems, the intersession variability within language has become an important adverse factor that degrades the system performance. To tackle this problem, we propose a subspace analysis method, termed as Intra-language Difference Subspace Estimatio (IDSE), under the GMM-SVM framework. In IDSE method, the difference vector is modeled with three components: Extra-language difference, Intra-language difference and noise difference. Then the Intra-language and noise difference are effectively estimated and eliminated from the difference vector. The experiments on NIST 07 evaluation tasks show effectiveness of the proposed method.