Transformer-Capsule Model for Intent Detection (Student Abstract)
Aleksander Obuchowski, Michał Lew · Proceedings of the AAAI Conference on Artificial Intelligence · 2020
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.