Speaker verification without background speaker models

Speaker verification concerns the problem of verifying whether a given utterance has been pronounced by a claimed authorized speaker. This problem is important because an accurate speaker verification system can be applied to many security applications. We present a new algorithm for speaker verification called OSCILLO. By applying tolerance interval analysis in statistics, OSCILLO can verify a speaker´s ID without background speaker models. This greatly reduces the space requirement of the system and the time for both training and verification. Experimental results show that OSCILLO can achieve error rates comparable or better than the GMM-based system with background speaker models for three benchmark databases: TCC-300, TIMIT and NIST 2000.