Enhanced Speaker-aware Multi-party Multi-turn Dialogue Comprehension

• URL: http://arxiv.org/abs/2109.04066v1
• Date: Thu, 9 Sep 2021 07:12:22 GMT
• Title: Enhanced Speaker-aware Multi-party Multi-turn Dialogue Comprehension
• Authors: Xinbei Ma, Zhuosheng Zhang, Hai Zhao
• Abstract summary: Multi-party multi-turn dialogue comprehension brings unprecedented challenges. Most existing methods deal with dialogue contexts as plain texts. We propose an enhanced speaker-aware model with masking attention and heterogeneous graph networks.
• Score: 43.352833140317486
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multi-party multi-turn dialogue comprehension brings unprecedented challenges on handling the complicated scenarios from multiple speakers and criss-crossed discourse relationship among speaker-aware utterances. Most existing methods deal with dialogue contexts as plain texts and pay insufficient attention to the crucial speaker-aware clues. In this work, we propose an enhanced speaker-aware model with masking attention and heterogeneous graph networks to comprehensively capture discourse clues from both sides of speaker property and speaker-aware relationships. With such comprehensive speaker-aware modeling, experimental results show that our speaker-aware model helps achieves state-of-the-art performance on the benchmark dataset Molweni. Case analysis shows that our model enhances the connections between utterances and their own speakers and captures the speaker-aware discourse relations, which are critical for dialogue modeling.

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