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Task-oriented dialogue systems: Performance vs. quality-optima, a review

Fellows, Ryan; Ihshaish, Hisham; Battle, Steve; Haines, Ciaran; Mayhew, Peter; Deza, J Ignacio

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Authors

Ryan Fellows

Hisham Ihshaish Hisham.Ihshaish@uwe.ac.uk
Senior Lecturer in Information Science

Ciaran Haines

Peter Mayhew

Ignacio Deza Ignacio.Deza@uwe.ac.uk
Associate Lecturer - CATE - CCT - UCCT0001



Abstract

Task-oriented dialogue systems (TODS) are continuing to rise in popularity as various industries find ways to effectively harness their capabilities, saving both time and money. However, even state-of-the-art TODS are not yet reaching their full potential. TODS typically have a primary design focus on completing the task at hand, so the metric of task-resolution should take priority. Other conversational quality attributes that may point to the success, or otherwise, of the dialogue, may be ignored. This can cause interactions between human and dialogue system that leave the user dissatisfied or frustrated. This paper explores the literature on evaluative frameworks of dialogue systems and the role of conversational quality attributes in dialogue systems, looking at if, how, and where they are utilised, and examining their correlation with the performance of the dialogue system.

Presentation Conference Type Conference Paper (published)
Conference Name 3rd International Conference on Natural Language Processing and Computational Linguistics (NLPCL 2022)
Start Date Jul 30, 2022
End Date Jul 31, 2022
Acceptance Date May 18, 2022
Online Publication Date Jul 31, 2022
Publication Date Jul 31, 2022
Deposit Date Jan 7, 2022
Publicly Available Date Sep 5, 2022
Volume 12
Pages 69-87
Series Title 3rd International Conference on Natural Language Processing & Computational Linguistics (NLPCL 2022)
Series ISSN 2231 - 5403
Book Title David C. Wyld et al. (Eds): SIPP, NLPCL, BIGML, SOEN, AISC, NCWMC, CCSIT - 2022 pp. 69-87, 2022. CS & IT - CSCP 2022
ISBN 978-1-925953-72-5
DOI https://doi.org/10.5121/csit.2022.121306
Keywords Dialogue Systems; Chatbot; Conversational Agents; AI; Natural Language Processing; Quality Attributes
Public URL https://uwe-repository.worktribe.com/output/8535323
Publisher URL https://airccse.org/csit/V12N13.html
Related Public URLs https://ccsit2022.org/nlpcl/index

https://aircconline.com/csit/papers/vol12/

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