Abstract:
This paper analyses the probabilistic linear discriminant analysis
(PLDA) speaker verification approach with limited development
data. This paper investigates the use of the median
as the central tendency of a speaker’s i-vector representation,
and the effectiveness of weighted discriminative
techniques on the performance of state-of-the-art lengthnormalised
Gaussian PLDA (GPLDA) speaker verification
systems. The analysis within shows that the median (using
a median fisher discriminator (MFD)) provides a better
representation of a speaker when the number of representative
i-vectors available during development is reduced, and
that further, usage of the pair-wise weighting approach in
weighted LDA and weighted MFD provides further improvement
in limited development conditions. Best performance is
obtained using a weighted MFD approach, which shows over
10% improvement in EER over the baseline GPLDA system
on mismatched and interview-interview conditions.
