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Task-Oriented Dialogue Systems: Performance vs Quality-Optima, A Review

Authors

Ryan Fellows1*, Hisham Ihshaish1, Steve Battle1, Ciaran Haines1, Peter Mayhew1,2, J.Ignacio Deza1, 3, 1University of the West of England (UWE), United Kingdom, 2GE Aviation, Cheltenham, United Kingdom, 3Universidad Atlántida Argentina, Argentina

Abstract

Task-oriented dialogue systems (TODS) – designed to assist users to achieve a goal – 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 have not yet reached 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, are usually ignored. This can harm the interactions between the human and the dialogue system leaving the user dissatisfied or frustrated. This paper explores the role of conversational quality attributes within dialogue systems, looking at if, how, and where they are utilised, and examining their correlation with the performance of the dialogue system.

Keywords

Dialogue Systems, Chatbot, Conversational Agents, AI, Natural Language Processing, Quality Attributes.

Full Text  Volume 12, Number 13