Language Detection with GMM Optimization Using Neural Networks

The automatic language recognition of the speech signal consists of algorithms and methods which are used for modeling and classifying different languages. GMM (Gaussian Mixture Model), as a powerful instrument, can be used in classifying feature vectors. Persian language verification system, reported in [1], uses GMM as a basic system for tokenizing and Neural Network as the backend processor. In this paper a "Persian language detection system" is optimized to be used in "language verification system".