Open-Set Speaker Identification under Mismatch Conditions

Abstract

This paper presents investigations into the performance of open-set, text-independent speaker identification (OSTI-SI) under mismatched data conditions. The scope of the study includes attempts to reduce the adverse effects of such conditions through the introduction of a modified parallel model combination (PMC) method together with condition-adjusted T-Norm (CT-Norm) into the OSTI-SI framework. The experiments are conducted using examples of real world noise. Based on the outcomes, it is demonstrated that the above approach can lead to considerable improvements in the accuracy of open-set speaker identification operating under severely mismatched data conditions. The paper details the realisation of the modified PMC method and CT-Norm in the context of OSTI-SI, presents the experimental investigations and provides an analysis of the results.