Long term examination of intra-session and inter-session speaker variability

Session variability in speaker recognition is a well recognized phenomena, but poorly understood largely due to a dearth of robust longitudinal data. The current study uses a large, longterm speaker database to quantify both speaker variability changes within a conversation and the impact of speaker variability changes over the long term (3 years). Results demonstrate that 1) change in accuracy over the course of a conversation is statistically very robust and 2) that the aging effect over three years is statistically negligible. Finally we demonstrate that voice change during the course of a conversation is, in large part, comparable across sessions. Index Terms: session variability, speaker recognition, speaker variability analysis, conversation analysis