September 22-25, 1997
This paper presents a text-independent speaker recognition system based on vowel spotting and Continuous Mixture Hidden Markov Models. The same modeling technique is applied both to vowel spotting and speaker identification/verification procedures. The system is evaluated on two speech databases, TIMIT and NTIMIT, resulting in high accuracy rates. Closed-set identification accuracy on TIMIT and NTIMIT databases is 98.09% and 59.32%, respectively. Concerning the verification experiments, accuracy of 98.28% for TIMIT, and 83.04% for NTIMIT databases is obtained. The nearly real time response of the classification procedure, the low memory requirements and the small amount of training and testing data are some of the additional advantages of the proposed speaker recognition system.
Bibliographic reference. Fakotakis, Nikos / Georgila, Kallirroi / Tsopanoglou, Anastasios (1997): "A continuous HMM text-independent speaker recognition system based on vowel spotting", In EUROSPEECH-1997, 2347-2350.