Effect of reference set selection on speaker dependent speech recognition

Presented here for a speaker dependent system, is an algorithm which chooses a reference template for each word in the vocabulary from a set of N exemplars. The goal of the algorithm is to produce a reference set that minimizes the worst matching behavior and total error over the N sets of exemplars. The results of the experiments presented here show a reduction in the average error rate from 16.4% to 10.2% over a set of 4 male speakers and 4 female speakers.