Automatic speaker identification for a large number of speakers

Design of speaker identification systems for a small number of speakers (around 10) with a high degree of accuracy has evolved over the past few years. A sequential identification technique gives better results when the number of speakers is large. This scheme is implemented as a decision tree classifier in which the final decision is made only after a predetermined number of stages. The error rate could be controlled consistent with the features selected. This paper describes a 2-stage decision tree classifier implemented on a HP Fourier analyser system for identification of 30 speakers. The scheme proceeds as follows. At the first stage of the decision tree the population under consideration is reduced by a factor of 3 with high degree of accuracy, and at the second stage, the scheme available for ten speaker identification is used, The computational savings and performance achieved are compared with that obtained in a single stage classifier.