Team Synapse @ AutoMin 2023: Leveraging BART-Based Models for Automatic Meeting Minuting

Kristýna Klesnilová, Michelle Elizabeth


Abstract
This paper describes the approach we followed for our submission to the Second Run of the Automatic Minuting Shared Task. Our methodology centers around employing BART-based models fine-tuned on diverse summarization corpora. The segmented meeting transcripts are fed into the models, generating summaries that are subsequently combined and formatted into the final meeting minutes.
Anthology ID:
2023.inlg-genchal.15
Volume:
Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges
Month:
September
Year:
2023
Address:
Prague, Czechia
Editor:
Simon Mille
Venues:
INLG | SIGDIAL
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
108–113
Language:
URL:
https://aclanthology.org/2023.inlg-genchal.15
DOI:
Bibkey:
Cite (ACL):
Kristýna Klesnilová and Michelle Elizabeth. 2023. Team Synapse @ AutoMin 2023: Leveraging BART-Based Models for Automatic Meeting Minuting. In Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges, pages 108–113, Prague, Czechia. Association for Computational Linguistics.
Cite (Informal):
Team Synapse @ AutoMin 2023: Leveraging BART-Based Models for Automatic Meeting Minuting (Klesnilová & Elizabeth, INLG-SIGDIAL 2023)
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PDF:
https://aclanthology.org/2023.inlg-genchal.15.pdf