Publication detail

From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization

LANDINI, F. LOZANO DÍEZ, A. DIEZ SÁNCHEZ, M. BURGET, L.

Original Title

From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization

Type

conference paper

Language

English

Original Abstract

End-to-end neural diarization (EEND) is nowadays one of the most prominent research topics in speaker diarization. EEND presents an attractive alternative to standard cascaded diarization systems since a single system is trained at once to deal with the whole diarization problem. Several EEND variants and approaches are being proposed, however, all these models require large amounts of annotated data for training but available annotated data are scarce. Thus, EEND works have used mostly simulated mixtures for training. However, simulated mixtures do not resemble real conversations in many aspects. In this work we present an alternative method for creating synthetic conversations that resemble real ones by using statistics about distributions of pauses and overlaps estimated on genuine conversations. Furthermore, we analyze the effect of the source of the statistics, different augmentations and amounts of data. We demonstrate that our approach performs substantially better than the original one, while reducing the dependence on the fine-tuning stage. Experiments are carried out on 2-speaker telephone conversations of Callhome and DIHARD 3. Together with this publication, we release our implementations of EEND and the method for creating simulated conversations.

Keywords

peaker diarization, end-to-end neural diariza- tion, simulated conversations

Authors

LANDINI, F.; LOZANO DÍEZ, A.; DIEZ SÁNCHEZ, M.; 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

5095

Pages to

5099

Pages count

5

URL

https://www.isca-speech.org/archive/pdfs/interspeech_2022/landini22_interspeech.pdf

BibTex

@inproceedings{BUT179780,
  author="Federico Nicolás {Landini} and Alicia {Lozano Díez} and Mireia {Diez Sánchez} and Lukáš {Burget}",
  title="From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization",
  booktitle="Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",
  year="2022",
  journal="Proceedings of Interspeech",
  volume="2022",
  number="9",
  pages="5095--5099",
  publisher="International Speech Communication Association",
  address="Incheon",
  doi="10.21437/Interspeech.2022-10451",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/pdfs/interspeech_2022/landini22_interspeech.pdf"
}