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Intent Detection with WikiHow
Conference proceeding   Open access

Intent Detection with WikiHow

Li Zhang, Qing Lyu and Chris Callison-Burch
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, pp 328-333
01 Jan 2020
DOI: https://doi.org/10.18653/v1/2020.aacl-main.35
url
https://doi.org/10.18653/v1/2020.aacl-main.35View
Published, Version of Record (VoR) Open CC BY V3.0

Abstract

Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications Linguistics Science & Technology Artificial Intelligence or Cybernetics Computer Science Social Sciences Technology
Modern task-oriented dialog systems need to reliably understand users’ intents. Intent detection is even more challenging when moving to new domains or new languages, since there is little annotated data. To address this challenge, we present a suite of pretrained intent detection models which can predict a broad range of intended goals from many actions because they are trained on wikiHow, a comprehensive instructional website. Our models achieve state-of-the-art results on the Snips dataset, the Schema-Guided Dialogue dataset, and all 3 languages of the Facebook multilingual dialog datasets. Our models also demonstrate strong zero- and few-shot performance, reaching over 75% accuracy using only 100 training examples in all datasets.

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15 citations in Web of Science

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Web of Science research areas
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
Linguistics
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