Publication result detail

Analysis of the BUT Diarization System for Voxconverse Challenge

LANDINI, F.; GLEMBEK, O.; MATĚJKA, P.; ROHDIN, J.; BURGET, L.; DIEZ SÁNCHEZ, M.; SILNOVA, A.

Original Title

Analysis of the BUT Diarization System for Voxconverse Challenge

English Title

Analysis of the BUT Diarization System for Voxconverse Challenge

Type

Paper in proceedings (conference paper)

Original Abstract

This paper describes the system developed by the BUT team for thefourth track of the VoxCeleb Speaker Recognition Challenge, focusingon diarization on the VoxConverse dataset. The system consistsof signal pre-processing, voice activity detection, speaker embeddingextraction, an initial agglomerative hierarchical clusteringfollowed by diarization using a Bayesian hidden Markov model, areclustering step based on per-speaker global embeddings and overlappedspeech detection and handling. We provide comparisons foreach of the steps and share the implementation of the most relevantmodules of our system. Our system scored second in the challengein terms of the primary metric (diarization error rate) and first accordingto the secondary metric (Jaccard error rate).

English abstract

This paper describes the system developed by the BUT team for thefourth track of the VoxCeleb Speaker Recognition Challenge, focusingon diarization on the VoxConverse dataset. The system consistsof signal pre-processing, voice activity detection, speaker embeddingextraction, an initial agglomerative hierarchical clusteringfollowed by diarization using a Bayesian hidden Markov model, areclustering step based on per-speaker global embeddings and overlappedspeech detection and handling. We provide comparisons foreach of the steps and share the implementation of the most relevantmodules of our system. Our system scored second in the challengein terms of the primary metric (diarization error rate) and first accordingto the secondary metric (Jaccard error rate).

Keywords

Speaker Diarization, Variational Bayes, HMM,VoxConverse, VoxSRC Challenge

Key words in English

Speaker Diarization, Variational Bayes, HMM,VoxConverse, VoxSRC Challenge

Authors

LANDINI, F.; GLEMBEK, O.; MATĚJKA, P.; ROHDIN, J.; BURGET, L.; DIEZ SÁNCHEZ, M.; SILNOVA, A.

RIV year

2022

Released

06.06.2021

Publisher

IEEE Signal Processing Society

Location

Toronto, Ontario

ISBN

978-1-7281-7605-5

Book

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Pages from

5819

Pages to

5823

Pages count

5

URL

https://ieeexplore.ieee.org/document/9414315

BibTex

@inproceedings{BUT175790,
  author="Federico Nicolás {Landini} and Ondřej {Glembek} and Pavel {Matějka} and Johan Andréas {Rohdin} and Lukáš {Burget} and Mireia {Diez Sánchez} and Anna {Silnova}",
  title="Analysis of the BUT Diarization System for Voxconverse Challenge",
  booktitle="ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
  year="2021",
  pages="5819--5823",
  publisher="IEEE Signal Processing Society",
  address="Toronto, Ontario",
  doi="10.1109/ICASSP39728.2021.9414315",
  isbn="978-1-7281-7605-5",
  url="https://ieeexplore.ieee.org/document/9414315"
}

Documents

landini_icassp2021_09414315