Compensating for Ageing and Quality variation in Speaker Verification

Performing speaker verification in the simultaneous presence of ageing progression and changing speech sample quality is an important, open problem. The issues of ageing and quality variation go hand in hand; the effect of ageing increases with time, while variations in quality are also more likely to be encountered as time passes. In this work we demonstrate the effect of ageing on speaker verification performance, and show the relationship between quality variation and verification score via a range of established quality measures. We employ a stacked classifier framework to combine the output of the baseline verification system with ageing information and quality measures. This new approach to long-term speaker verification allows for a multi-dimensional decision boundary that significantly improves upon the baseline performance. The proposed framework is evaluated on the Trinity College Dublin Speaker Ageing Database.