Open-domain Dialogue Generation: What We Can Do, Cannot Do, And Should Do Next

Katharina Kann, Abteen Ebrahimi, Joewie Koh, Shiran Dudy, Alessandro Roncone


Abstract
Human–computer conversation has long been an interest of artificial intelligence and natural language processing research. Recent years have seen a dramatic improvement in quality for both task-oriented and open-domain dialogue systems, and an increasing amount of research in the area. The goal of this work is threefold: (1) to provide an overview of recent advances in the field of open-domain dialogue, (2) to summarize issues related to ethics, bias, and fairness that the field has identified as well as typical errors of dialogue systems, and (3) to outline important future challenges. We hope that this work will be of interest to both new and experienced researchers in the area.
Anthology ID:
2022.nlp4convai-1.13
Volume:
Proceedings of the 4th Workshop on NLP for Conversational AI
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Bing Liu, Alexandros Papangelis, Stefan Ultes, Abhinav Rastogi, Yun-Nung Chen, Georgios Spithourakis, Elnaz Nouri, Weiyan Shi
Venue:
NLP4ConvAI
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
148–165
Language:
URL:
https://aclanthology.org/2022.nlp4convai-1.13
DOI:
10.18653/v1/2022.nlp4convai-1.13
Bibkey:
Cite (ACL):
Katharina Kann, Abteen Ebrahimi, Joewie Koh, Shiran Dudy, and Alessandro Roncone. 2022. Open-domain Dialogue Generation: What We Can Do, Cannot Do, And Should Do Next. In Proceedings of the 4th Workshop on NLP for Conversational AI, pages 148–165, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Open-domain Dialogue Generation: What We Can Do, Cannot Do, And Should Do Next (Kann et al., NLP4ConvAI 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.nlp4convai-1.13.pdf
Data
Wizard of Wikipedia