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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" }