Supervized Mixture of PLDA Models for Cross-Channel Speaker Verification

This paper presents a development of previous research by P.Kenny, which deals with using a supervised PLDA mixture of two gender-dependent speaker verification systems under the conditions of gender uncertainty. We propose using PLDA mixtures for speaker verification in different channels. However, in contrast to creating a gender-independent mixture, the optimal decision for training a channel-independent mixture for two channels in our task was mixing three channel-dependent PLDA systems. The experiments conducted on different conditions of NIST 2010 showed the superior robustness of the PDLA system mixture compared to each of its component PDLA subsystems not only in EER value but also in the stability of the decision threshold. The latter fact is very significant for using this approach not just for obtaining a good NIST SRE actual cost but also for commercial applications.