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:
- 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)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2023.inlg-genchal.15.pdf