PLDA speaker verification with limited speech data

Abstract

In some speaker verification applications the amount of data available for enrolment and verification can be limited. One of the aims of this paper is to study the impact of the volume of enrolment and verification data on the performance of the system. The second aim is focused on the improvement of the speaker verification using PLDA. The PLDA is generally used to model the speaker and channel variability in the i-vector space using data from several recording sessions. In our experiment, only data from single-session per speaker was available. Therefore, we divided the development recordings into shorter segments and these segments were treated as if they were recorded in different sessions. This approach does not model the inter-session speaker variability, nor the channel variability. However, we assumed that statistical modelling of the intra-session speaker variability could bring an improvement to the results of the verification. Different granularity of segmentation was studied at various amount of enrolment and verification data.