Recent Advances and Challenges in Task-oriented Dialog System

TL;DR

This survey reviews recent progress and challenges in task-oriented dialog systems, focusing on data efficiency, multi-turn dynamics, domain knowledge integration, and evaluation methods to guide future research.

Contribution

It provides a comprehensive overview of recent advances and identifies key challenges in the development of task-oriented dialog systems.

Findings

Enhanced data efficiency techniques for low-resource settings

Improved dialog policy learning through multi-turn modeling

Integration of domain ontology knowledge into dialog models

Abstract

Due to the significance and value in human-computer interaction and natural language processing, task-oriented dialog systems are attracting more and more attention in both academic and industrial communities. In this paper, we survey recent advances and challenges in task-oriented dialog systems. We also discuss three critical topics for task-oriented dialog systems: (1) improving data efficiency to facilitate dialog modeling in low-resource settings, (2) modeling multi-turn dynamics for dialog policy learning to achieve better task-completion performance, and (3) integrating domain ontology knowledge into the dialog model. Besides, we review the recent progresses in dialog evaluation and some widely-used corpora. We believe that this survey, though incomplete, can shed a light on future research in task-oriented dialog systems.