Transformer-Capsule Model for Intent Detection (Student Abstract)

Authors

  • Aleksander Obuchowski Gdańsk University of Technology
  • Michał Lew SentiOne Research

DOI:

https://doi.org/10.1609/aaai.v34i10.7215

Abstract

Intent recognition is one of the most crucial tasks in NLU systems, which are nowadays especially important for designing intelligent conversation. We propose a novel approach to intent recognition which involves combining transformer architecture with capsule networks. Our results show that such architecture performs better than original capsule-NLU network implementations and achieves state-of-the-art results on datasets such as ATIS, AskUbuntu ,and WebApp.

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Published

2020-04-03

How to Cite

Obuchowski, A., & Lew, M. (2020). Transformer-Capsule Model for Intent Detection (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 34(10), 13885-13886. https://doi.org/10.1609/aaai.v34i10.7215

Issue

Section

Student Abstract Track