Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants
Cheng Qian, Haode Qi, Gengyu Wang, Ladislav Kunc, Saloni Potdar
Abstract
Out of Scope (OOS) detection in Conversational AI solutions enables a chatbot to handle a conversation gracefully when it is unable to make sense of the end-user query. Accurately tagging a query as out-of-domain is particularly hard in scenarios when the chatbot is not equipped to handle a topic which has semantic overlap with an existing topic it is trained on. We propose a simple yet effective OOS detection method that outperforms standard OOS detection methods in a real-world deployment of virtual assistants. We discuss the various design and deployment considerations for a cloud platform solution to train virtual assistants and deploy them at scale. Additionally, we propose a collection of datasets that replicates real-world scenarios and show comprehensive results in various settings using both offline and online evaluation metrics.- Anthology ID:
- 2022.emnlp-industry.51
- Volume:
- Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, UAE
- Editors:
- Yunyao Li, Angeliki Lazaridou
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 502–511
- Language:
- URL:
- https://aclanthology.org/2022.emnlp-industry.51
- DOI:
- 10.18653/v1/2022.emnlp-industry.51
- Cite (ACL):
- Cheng Qian, Haode Qi, Gengyu Wang, Ladislav Kunc, and Saloni Potdar. 2022. Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 502–511, Abu Dhabi, UAE. Association for Computational Linguistics.
- Cite (Informal):
- Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants (Qian et al., EMNLP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2022.emnlp-industry.51.pdf