7 citations · 13 across the 5 of their papers we have counts for
5 papers · 1 filter
Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings
Niko Brümmer, Albert Swart, Ladislav Mošner +4
In speaker recognition, where speech segments are mapped to embeddings on the unit hypersphere, two scoring backends are commonly used, namely cosine scoring or PLDA. Both have adv…
Language-depedent I-Vectors for LRE15
Niko Brümmer, Albert Swart
A standard recipe for spoken language recognition is to apply a Gaussian back-end to i-vectors. This ignores the uncertainty in the i-vector extraction, which could be important es…
A Generative Model for Score Normalization in Speaker Recognition
Albert Swart, Niko Brummer
We propose a theoretical framework for thinking about score normalization, which confirms that normalization is not needed under (admittedly fragile) ideal conditions. If, however,…
Bayesian calibration for forensic evidence reporting
Niko Brümmer, Albert Swart
We introduce a Bayesian solution for the problem in forensic speaker recognition, where there may be very little background material for estimating score calibration parameters. We…
A comparison of linear and non-linear calibrations for speaker recognition
Niko Brümmer, Albert Swart, David van Leeuwen
In recent work on both generative and discriminative score to log-likelihood-ratio calibration, it was shown that linear transforms give good accuracy only for a limited range of o…