Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs

Jiaao Chen, Diyi Yang


Abstract
Abstractive conversation summarization has received much attention recently. However, these generated summaries often suffer from insufficient, redundant, or incorrect content, largely due to the unstructured and complex characteristics of human-human interactions. To this end, we propose to explicitly model the rich structures in conversations for more precise and accurate conversation summarization, by first incorporating discourse relations between utterances and action triples (“who-doing-what”) in utterances through structured graphs to better encode conversations, and then designing a multi-granularity decoder to generate summaries by combining all levels of information. Experiments show that our proposed models outperform state-of-the-art methods and generalize well in other domains in terms of both automatic evaluations and human judgments. We have publicly released our code at https://github.com/GT-SALT/Structure-Aware-BART.
Anthology ID:
2021.naacl-main.109
Volume:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
June
Year:
2021
Address:
Online
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1380–1391
Language:
URL:
https://aclanthology.org/2021.naacl-main.109
DOI:
10.18653/v1/2021.naacl-main.109
Bibkey:
Cite (ACL):
Jiaao Chen and Diyi Yang. 2021. Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1380–1391, Online. Association for Computational Linguistics.
Cite (Informal):
Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs (Chen & Yang, NAACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.naacl-main.109.pdf
Video:
 https://aclanthology.org/2021.naacl-main.109.mp4
Code
 GT-SALT/Structure-Aware-BART
Data
SAMSum Corpus