Abstract
This paper describes our AMRTVSumm system for the SummScreen datasets in the Automatic Summarization for Creative Writing shared task (Creative-Summ 2022). In order to capture the complicated entity interactions and dialogue structures in transcripts of TV series, we introduce a new Abstract Meaning Representation (AMR) (Banarescu et al., 2013), particularly designed to represent individual scenes in an episode. We also propose a new cross-level cross-attention mechanism to incorporate these scene AMRs into a hierarchical encoder-decoder baseline. On both the ForeverDreaming and TVMegaSite datasets of SummScreen, our system consistently outperforms the hierarchical transformer baseline. Compared with the state-of-the-art DialogLM (Zhong et al., 2021), our system still has a lower performance primarily because it is pretrained only on out-of-domain news data, unlike DialogLM, which uses extensive in-domain pretraining on dialogue and TV show data. Overall, our work suggests a promising direction to capture complicated long dialogue structures through graph representations and the need to combine graph representations with powerful pretrained language models.- Anthology ID:
- 2022.creativesumm-1.6
- Volume:
- Proceedings of The Workshop on Automatic Summarization for Creative Writing
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Venue:
- CreativeSumm
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 36–43
- Language:
- URL:
- https://aclanthology.org/2022.creativesumm-1.6
- DOI:
- Cite (ACL):
- Yilun Hua, Zhaoyuan Deng, and Zhijie Xu. 2022. AMRTVSumm: AMR-augmented Hierarchical Network for TV Transcript Summarization. In Proceedings of The Workshop on Automatic Summarization for Creative Writing, pages 36–43, Gyeongju, Republic of Korea. Association for Computational Linguistics.
- Cite (Informal):
- AMRTVSumm: AMR-augmented Hierarchical Network for TV Transcript Summarization (Hua et al., CreativeSumm 2022)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/2022.creativesumm-1.6.pdf