Abstract
Conversational interfaces provide a flexible and easy way for users to seek information that may otherwise be difficult or inconvenient to obtain. However, existing interfaces generally fall into one of two categories: FAQs, where users must have a concrete question in order to retrieve a general answer, or dialogs, where users must follow a pre-defined path but may receive a personalized answer. In this paper, we introduce Conversational Tree Search (CTS) as a new task that bridges the gap between FAQ-style information retrieval and task-oriented dialog, allowing domain-experts to define dialog trees which can then be converted to an efficient dialog policy that learns only to ask the questions necessary to navigate a user to their goal. We collect a dataset for the travel reimbursement domain and demonstrate a baseline as well as a novel deep Reinforcement Learning architecture for this task. Our results show that the new architecture combines the positive aspects of both the FAQ and dialog system used in the baseline and achieves higher goal completion while skipping unnecessary questions.- Anthology ID:
- 2023.eacl-main.91
- Volume:
- Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Editors:
- Andreas Vlachos, Isabelle Augenstein
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1264–1280
- Language:
- URL:
- https://aclanthology.org/2023.eacl-main.91
- DOI:
- 10.18653/v1/2023.eacl-main.91
- Cite (ACL):
- Dirk Väth, Lindsey Vanderlyn, and Ngoc Thang Vu. 2023. Conversational Tree Search: A New Hybrid Dialog Task. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 1264–1280, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- Conversational Tree Search: A New Hybrid Dialog Task (Väth et al., EACL 2023)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/2023.eacl-main.91.pdf