A realtime implementation of a text independent speaker recognition system

This paper describes the design and implementation of a realtime speaker recognition system. The system performs text independent, closed set speaker recognition with up to 30 talkers in realtime. In addition, the reference speech used to characterize the 30 talkers can be extracted from as little as 10 seconds of speech from each talker, and the actual recognition performed with less than one minute of speech from the unknown talker. Two speaker recognition algorithms previously developed by Markel and Pfeifer were investigated for use in the realtime system. The results of this investigation clearly show that Markel´s technique is superior for applications using very short speech segments for both the speaker models and the recognition trials. Markel´s technique was implemented in realtime in a high speed progranmable signal processor. A test of this implementation with a set of 30 male speakers resulted in recognition accuracies of 93-100% for models generated with only 10 seconds of speech, and recognition trials using only 10 seconds of unknown speech.