Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion

• URL: http://arxiv.org/abs/2205.13108v1
• Date: Thu, 26 May 2022 02:18:12 GMT
• Title: Unsupervised Abstractive Dialogue Summarization with Word Graphs and POV Conversion
• Authors: Seongmin Park, Jihwa Lee
• Abstract summary: We present state-of-the-art in unsupervised abstractive dialogue summarization by utilizing multi-sentence compression graphs. Our method is demonstrated on datasets across multiple domains, including meetings, interviews, movie scripts, and day-to-day conversations.
• Score: 1.2691047660244335
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We advance the state-of-the-art in unsupervised abstractive dialogue summarization by utilizing multi-sentence compression graphs. Starting from well-founded assumptions about word graphs, we present simple but reliable path-reranking and topic segmentation schemes. Robustness of our method is demonstrated on datasets across multiple domains, including meetings, interviews, movie scripts, and day-to-day conversations. We also identify possible avenues to augment our heuristic-based system with deep learning. We open-source our code, to provide a strong, reproducible baseline for future research into unsupervised dialogue summarization.

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