Result Details

Do End-to-End Neural Diarization Attractors Need to Encode Speaker Characteristic Information?

ZHANG, L.; STAFYLAKIS, T.; LANDINI, F.; DIEZ SÁNCHEZ, M.; SILNOVA, A.; BURGET, L. Do End-to-End Neural Diarization Attractors Need to Encode Speaker Characteristic Information?. Proceedings of Odyssey 2024: The Speaker and Language Recognition Workshop. Québec City: International Speech Communication Association, 2024. p. 123.
Type
conference paper
Language
English
Authors
ZHANG, L.
Stafylakis Themos, Prof.
Landini Federico Nicolás, Ph.D., DCGM (FIT)
DIEZ SÁNCHEZ, M.
Silnova Anna, M.Sc., Ph.D., DCGM (FIT)
Burget Lukáš, doc. Ing., Ph.D., DCGM (FIT)
Abstract

In this paper, we apply the variational information bottleneck
approach to end-to-end neural diarization with encoder-decoder
attractors (EEND-EDA). This allows us to investigate what in-
formation is essential for the model. EEND-EDA utilizes attrac-
tors, vector representations of speakers in a conversation. Our
analysis shows that, attractors do not necessarily have to con-
tain speaker characteristic information. On the other hand, giv-
ing the attractors more freedom to allow them to encode some
extra (possibly speaker-specific) information leads to small but
consistent diarization performance improvements. Despite ar-
chitectural differences in EEND systems, the notion of attrac-
tors and frame embeddings is common to most of them and
not specific to EEND-EDA. We believe that the main conclu-
sions of this work can apply to other variants of EEND. Thus,
we hope this paper will be a valuable contribution to guide the
community to make more informed decisions when designing new systems.

Keywords

End-to-End Neural Diarization, Speaker Characteristic Information

URL
Published
2024
Pages
123–130
Proceedings
Proceedings of Odyssey 2024: The Speaker and Language Recognition Workshop
Conference
Odyssey 2024: The Speaker and Language Recognition Workshop
Publisher
International Speech Communication Association
Place
Québec City
DOI
10.21437/odyssey.2024-18
BibTeX 
@inproceedings{BUT193432,
  author="ZHANG, L. and STAFYLAKIS, T. and LANDINI, F. and DIEZ SÁNCHEZ, M. and SILNOVA, A. and BURGET, L.",
  title="Do End-to-End Neural Diarization Attractors Need to Encode Speaker Characteristic Information?",
  booktitle="Proceedings of Odyssey 2024: The Speaker and Language Recognition Workshop",
  year="2024",
  pages="123--130",
  publisher="International Speech Communication Association",
  address="Québec City",
  doi="10.21437/odyssey.2024-18",
  url="https://www.isca-archive.org/odyssey_2024/zhang24_odyssey.pdf"
}
Files
Projects
Exchanges for SPEech ReseArch aNd TechnOlogies, EU, Horizon 2020, start: 2021-01-01, end: 2025-12-31, completed
Robust processing of recordings for operations and security, MV, PROGRAM STRATEGICKÁ PODPORA ROZVOJE BEZPEČNOSTNÍHO VÝZKUMU ČR 2019-2025 (IMPAKT 1) PODPROGRAMU 1 SPOLEČNÉ VÝZKUMNÉ PROJEKTY (BV IMP1/1VS), VJ01010108, start: 2020-10-01, end: 2025-09-30, completed
Research groups
Speech Data Mining Research Group BUT Speech@FIT (RG SPEECH)
Departments
Department of Computer Graphics and Multimedia (DCGM)
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