Comparison of Four Distance Measures for Long Time Text-Independent Speaker Identification

Abstract

In this study, four distance measures were compared for text-independent speaker identitication using the long time statistical feature averaging method. The four methods were the City block, the Euclidean, the Weighted Euclidean, and the Mahalanobis distance measures. Identification decision was based on the minimum distance criterion. This study showed that the Weighted Euclidean distance measure performed best, and the Mahalanobis distance measure did not perform well. An explanation is advanced for this result.