SalesBot: Transitioning from Chit-Chat to Task-Oriented Dialogues
Ssu Chiu, Maolin Li, Yen-Ting R. Lin, Yun-Nung Chen · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2022
Dialogue systems are usually categorized into two types, open-domain and task-oriented.The first one focuses on chatting with users and making them engage in the conversations, where selecting a proper topic to fit the dialogue context is essential for a successful dialogue.The other one focuses on a specific task instead of casual talks, e.g., finding a movie on Friday night, playing a song.These two directions have been studied separately due to their different purposes.However, how to smoothly transition from social chatting to task-oriented dialogues is important for triggering the business opportunities, and there is no any public data focusing on such scenarios.Hence, this paper focuses on investigating the conversations starting from open-domain social chatting and then gradually transitioning to taskoriented purposes, and releases a large-scale dataset with detailed annotations for encouraging this research direction.To achieve this goal, this paper proposes a framework to automatically generate many dialogues without human involvement, in which any powerful opendomain dialogue generation model can be easily leveraged.The human evaluation shows that our generated dialogue data has a natural flow at a reasonable quality, showing that our released data has a great potential of guiding future research directions and commercial activities.Furthermore, the released models allow researchers to automatically generate unlimited dialogues in the target scenarios, which can greatly benefit semi-supervised and unsupervised approaches. 1