Publication Details

Toroidal Probabilistic Spherical Discriminant Analysis

SILNOVA, A.; BRUMMER, J.; SWART, A.; BURGET, L. Toroidal Probabilistic Spherical Discriminant Analysis. In Proceedings of ICASSP 2023. Rhodes Island: IEEE Signal Processing Society, 2023. p. 1-5. ISBN: 978-1-7281-6327-7.
Czech title
Toroidální pravděpodobnostní sférická diskriminační analýza
Type
conference paper
Language
English
Authors
Silnova Anna, M.Sc., Ph.D. (DCGM)
Brummer Johan Nikolaas Langenhoven, Dr.
Swart Albert du Preez
Burget Lukáš, doc. Ing., Ph.D. (DCGM)
URL
Keywords

speaker recognition, PSDA, Von Mises-Fishe

Abstract

n speaker recognition, where speech segments are mapped to embeddings on the unit hypersphere, two scoring back-ends are commonly used, namely cosine scoring and PLDA. We have recently proposed PSDA, an analog to PLDA that uses Von Mises-Fisher distributions instead of Gaussians. In this paper, we present toroidal PSDA (T-PSDA). It extends PSDA with the ability to model within and between-speaker variabilities in toroidal submanifolds of the hypersphere. Like PLDA and PSDA, the model allows closed-form scoring and closed-form EM updates for training. On VoxCeleb, we find T-PSDA accu- racy on par with cosine scoring, while PLDA accuracy is infe- rior. On NIST SRE'21 we find that T-PSDA gives large accu- racy gains compared to both cosine scoring and PLDA.

Published
2023
Pages
1–5
Proceedings
Proceedings of ICASSP 2023
ISBN
978-1-7281-6327-7
Publisher
IEEE Signal Processing Society
Place
Rhodes Island
DOI
EID Scopus
BibTeX
@inproceedings{BUT185199,
  author="Anna {Silnova} and Johan Nikolaas Langenhoven {Brummer} and Albert du Preez {Swart} and Lukáš {Burget}",
  title="Toroidal Probabilistic Spherical Discriminant Analysis",
  booktitle="Proceedings of ICASSP 2023",
  year="2023",
  pages="1--5",
  publisher="IEEE Signal Processing Society",
  address="Rhodes Island",
  doi="10.1109/ICASSP49357.2023.10095580",
  isbn="978-1-7281-6327-7",
  url="https://ieeexplore.ieee.org/document/10095580"
}
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