Intent Detection and Slot Filling for Vietnamese

Autor:	Dao, Mai Hoang, Truong, Thinh Hung, Nguyen, Dat Quoc
Rok vydání:	2021
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	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: https://github.com/VinAIResearch/JointIDSF Comment: To appear in Proceedings of INTERSPEECH 2021; The first two authors contributed equally to this work
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2104.02021 Zobrazit plný text záznamu View this record from Arxiv