Interview: Large-scale Modeling of Media Dialog with Discourse Patterns and Knowledge Grounding
Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, Julian McAuley
Abstract
In this work, we perform the first large-scale analysis of discourse in media dialog and its impact on generative modeling of dialog turns, with a focus on interrogative patterns and use of external knowledge. Discourse analysis can help us understand modes of persuasion, entertainment, and information elicitation in such settings, but has been limited to manual review of small corpora. We introduce **Interview**—a large-scale (105K conversations) media dialog dataset collected from news interview transcripts—which allows us to investigate such patterns at scale. We present a dialog model that leverages external knowledge as well as dialog acts via auxiliary losses and demonstrate that our model quantitatively and qualitatively outperforms strong discourse-agnostic baselines for dialog modeling—generating more specific and topical responses in interview-style conversations.- Anthology ID:
- 2020.emnlp-main.653
- Volume:
- Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 8129–8141
- Language:
- URL:
- https://aclanthology.org/2020.emnlp-main.653
- DOI:
- 10.18653/v1/2020.emnlp-main.653
- Cite (ACL):
- Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, and Julian McAuley. 2020. Interview: Large-scale Modeling of Media Dialog with Discourse Patterns and Knowledge Grounding. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 8129–8141, Online. Association for Computational Linguistics.
- Cite (Informal):
- Interview: Large-scale Modeling of Media Dialog with Discourse Patterns and Knowledge Grounding (Majumder et al., EMNLP 2020)
- PDF:
- https://preview.aclanthology.org/jeptaln-2024-ingestion/2020.emnlp-main.653.pdf