A SVM/HMM system for speaker recognition
William M. Campbell · 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). · 2003
A framework for combining support vector machines with hidden Markov models (HMM) is given. A HMM is used with a Viterbi alignment to generate a set of subsequences of feature vectors. Each subsequence is then scored using a support vector machine sequence kernel. Experiments are performed for both text-independent and text-prompted speaker recognition tasks. Results show that the method can dramatically reduce error rates over a support vector machine (SVM) only system.