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

Kristýna Klesnilová, Michelle Elizabeth

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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://preview.aclanthology.org/teach-a-man-to-fish/2023.inlg-genchal.15.pdf
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