On model quality and evaluation in speaker verification

This paper addresses differences between operational speaker verification (SV) systems and laboratory experiments in terms of performance and methods for measuring performance. It is concluded that operational SV systems need an indication of the quality of newly enrolled speaker models, to decide whether to re-enrol or request more enrolment material. We have investigated the impact of ASR errors on model quality. While attempting to design measures for the quality of speaker models we have developed a novel method for assigning weights to the contribution of models in accordance with their discriminative ability