Publication detail

Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings

BRUMMER, J. SWART, A. MOŠNER, L. SILNOVA, A. PLCHOT, O. STAFYLAKIS, T. BURGET, L.

Original Title

Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings

Type

conference paper

Language

English

Original Abstract

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 advantages and disadvantages, depending on the context. Cosine scoring follows naturally from the spherical geometry, but for PLDA the blessing is mixedlength normalization Gaussianizes the between-speaker distribution, but violates the assumption of a speaker-independent within-speaker distribution. We propose PSDA, an analogue to PLDA that uses Von Mises- Fisher distributions on the hypersphere for both within and between-class distributions. We show how the self-conjugacy of this distribution gives closed-form likelihood-ratio scores, making it a drop-in replacement for PLDA at scoring time. All kinds of trials can be scored, including single-enroll and multienroll verification, as well as more complex likelihood-ratios that could be used in clustering and diarization. Learning is done via an EM-algorithm with closed-form updates. We explain the model and present some first experiments.

Keywords

speaker recognition, PSDA, Von Mises-Fisher

Authors

BRUMMER, J.; SWART, A.; MOŠNER, L.; SILNOVA, A.; PLCHOT, O.; STAFYLAKIS, T.; BURGET, L.

Released

18. 9. 2022

Publisher

International Speech Communication Association

Location

Incheon

ISBN

1990-9772

Periodical

Proceedings of Interspeech

Year of study

2022

Number

9

State

French Republic

Pages from

1446

Pages to

1450

Pages count

5

URL

https://www.isca-speech.org/archive/pdfs/interspeech_2022/brummer22_interspeech.pdf

BibTex

@inproceedings{BUT179687,
  author="Johan Nikolaas Langenhoven {Brummer} and Albert du Preez {Swart} and Ladislav {Mošner} and Anna {Silnova} and Oldřich {Plchot} and Themos {Stafylakis} and Lukáš {Burget}",
  title="Probabilistic Spherical Discriminant Analysis: An Alternative to PLDA for length-normalized embeddings",
  booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",
  year="2022",
  journal="Proceedings of Interspeech",
  volume="2022",
  number="9",
  pages="1446--1450",
  publisher="International Speech Communication Association",
  address="Incheon",
  doi="10.21437/Interspeech.2022-731",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/pdfs/interspeech_2022/brummer22_interspeech.pdf"
}