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Intent detection and slot filling for Vietnamese

2021-04-05 17:19:42
Mai Hoang Dao, Thinh Hung Truong, Dat Quoc Nguyen
arXiv_CL
           
Abstract

Intent detection and slot filling are important tasks in spoken and natural language understanding. However, Vietnamese is a low-resource language in these research topics. In this paper, we present the first public intent detection and slot filling dataset for Vietnamese. In addition, we also propose a joint model for intent detection and slot filling, that extends the recent state-of-the-art JointBERT+CRF model with an intent-slot attention layer in order to explicitly incorporate intent context information into slot filling via "soft" intent label embedding. Experimental results on our Vietnamese dataset show that our proposed model significantly outperforms JointBERT+CRF. We publicly release our dataset and the implementation of our model at: this https URL

Abstract (translated)

URL

https://arxiv.org/abs/2104.02021

PDF

https://arxiv.org/pdf/2104.02021.pdf

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