Abstract:
verification system development and evaluation, especially in
the presence of large intersession variability. This paper introduces
a source and utterance-duration normalized linear discriminant
analysis (SUN-LDA) approaches to compensate session
variability in short-utterance i-vector speaker verification
systems. Two variations of SUN-LDA are proposed where
normalization techniques are used to capture source variation
from both short and full-length development i-vectors, one
based upon pooling (SUN-LDA-pooled) and the other on concatenation
(SUN-LDA-concat) across the duration and sourcedependent
session variation. Both the SUN-LDA-pooled and
SUN-LDA-concat techniques are shown to provide improvement
over traditional LDA on NIST 08 truncated 10sec-10sec
evaluation conditions, with the highest improvement obtained
with the SUN-LDA-concat technique achieving a relative improvement
of 8% in EER for mis-matched conditions and over
3% for matched conditions over traditional LDA approaches.
