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arXiv · 2301.06544

Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants

Cheng Qian·Haode Qi·Gengyu Wang·Ladislav Kunc·Saloni Potdar
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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.

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Cheng Qian, Haode Qi, Gengyu Wang, Ladislav Kunc, Saloni Potdar. 2023-01-16. Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants. https://arxiv.org/abs/2301.06544

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