DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs

Satwik Kottur, Chinnadhurai Sankar, Zhou Yu, Alborz Geramifard


Abstract
Real-world conversational agents must effectively handle long conversations that span multiple contexts. Such context can be interspersed with chitchat (dialog turns not directly related to the task at hand), and potentially grounded in a multimodal setting. While prior work focused on the above aspects in isolation, there is a lack of a unified framework that studies them together. To overcome this, we propose DialogStitch, a novel framework to seamlessly ‘stitch’ multiple conversations and highlight these desirable traits in a taskoriented dialog. After stitching, our dialogs are provably deeper, contain longer-term dependencies, and span multiple contexts, when compared with the source dialogs—all free of cost without any additional annotations! Though our framework generalizes to a variety of combinations, we demonstrate its benefits in two settings: (a) multimodal, imagegrounded conversations, and, (b) task-oriented dialogs fused with chit-chat conversations. We benchmark state-of-the-art dialog models on our datasets and find accuracy drops of (a) 12% and (b) 45% respectively, indicating the additional challenges in the stitched dialogs. Our code and data are publicly available.
Anthology ID:
2021.sigdial-1.3
Volume:
Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue
Month:
July
Year:
2021
Address:
Singapore and Online
Editors:
Haizhou Li, Gina-Anne Levow, Zhou Yu, Chitralekha Gupta, Berrak Sisman, Siqi Cai, David Vandyke, Nina Dethlefs, Yan Wu, Junyi Jessy Li
Venue:
SIGDIAL
SIG:
SIGDIAL
Publisher:
Association for Computational Linguistics
Note:
Pages:
21–26
Language:
URL:
https://aclanthology.org/2021.sigdial-1.3
DOI:
10.18653/v1/2021.sigdial-1.3
Bibkey:
Cite (ACL):
Satwik Kottur, Chinnadhurai Sankar, Zhou Yu, and Alborz Geramifard. 2021. DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs. In Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 21–26, Singapore and Online. Association for Computational Linguistics.
Cite (Informal):
DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs (Kottur et al., SIGDIAL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.sigdial-1.3.pdf
Video:
 https://www.youtube.com/watch?v=rSgDH9gD_cU
Code
 facebookresearch/dialogstitch
Data
CLEVRCLEVR-DialogDailyDialogVisDialWizard of Wikipedia