Investigation On Broad Phone Based Text Independent Speaker Verification

As an important branch in the area of pattern recognition, text-independent speaker verification has attracted attention from more and more scientists since the last twenty years of the last century. Currently, Gaussian Mixture Model-Universal Background Model based speaker verification, dominates the field of text-independent speaker verification. Unfortunately, due to the regardless of content and language information, this kind of system has its limitation when applied to commercial tasks. To compensate the drawback of the Gaussian Mixture Model-Universal Background Model based speaker verification system, researchers have proposed speaker verification using broad phones, which could not only take use of techniques in the sphere of speech recognition, text-independent and text-dependent speaker verification, but also address problems introduced by the diversity of languages spoken by the speakers enrolling in the system.In this research work, the author proposed the definition of the broad phones, training method of the broad phonetic Hidden Markov Modes, and the framework of the broad phonetic Hidden Markov Modes based speaker verification system that has equivalent performance compared to Gaussian Mixture Model-Universal Background Model based speaker verification system. To boost the computational efficiency of the front-end processing in the phone recognizer, the author proposed a novel rapid Vocal Tract Length Normalization algorithm. Besides, the author proposed a algorithm to enhance the efficiency in speaker adaptation phase. In addition, the author successfully introduced the weights of Eigen Voice Speaker Adaptation into the Support Vector Machine, and constructed a new kind of speaker verification system which could provide complementary information to conventional Gaussian Mixture Model-Universal Background Model based speaker verification system.