ISCA Archive Interspeech 2014
ISCA Archive Interspeech 2014

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 work within the Bayesian paradigm of evidence reporting and develop a principled probabilistic treatment of the problem, which results in a Bayesian likelihood-ratio as the vehicle for reporting weight of evidence. We show in contrast, that reporting a likelihood-ratio distribution does not solve this problem. Our solution is experimentally exercised on a simulated forensic scenario, using NIST SRE'12 scores, which demonstrates a clear advantage for the proposed method compared to the traditional plugin calibration recipe.

doi: 10.21437/Interspeech.2014-90

Cite as: Brümmer, N., Swart, A. (2014) Bayesian calibration for forensic evidence reporting. Proc. Interspeech 2014, 388-392, doi: 10.21437/Interspeech.2014-90

  author={Niko Brümmer and Albert Swart},
  title={{Bayesian calibration for forensic evidence reporting}},
  booktitle={Proc. Interspeech 2014},