Intent Detection and Slot Filling for Vietnamese

Intent Detection and Slot Filling for Vietnamese

Authors: Mai Hoang Dao*, Thinh Hung Truong*, Dat Quoc Nguyen

INTERSPEECH 2021 - to appear


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 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

title = {{Intent Detection and Slot Filling for Vietnamese}},
author = {Mai Hoang Dao and Thinh Hung Truong and Dat Quoc Nguyen},
booktitle = {Proceedings of the 22nd Annual Conference of the International Speech Communication Association},
year = {2021},
pages = {to appear}