TY  - GEN
EP  - 126
AV  - public
N2  - Dialogue State Tracking (DST) aims to keep track of users? intentions during the course of a conversation. In DST, modelling the relations among domains and slots is still an under-studied problem. Existing approaches that have considered such relations generally fall short in: (1) fusing prior slot-domain membership relations and dialogue-aware dynamic slot relations explicitly, and (2) generalizing to unseen domains. To address these issues, we propose a novel Dynamic Schema Graph Fusion Network (DSGFNet), which generates a dynamic schema graph to explicitly fuse the prior slot-domain membership relations and dialogue-aware dynamic slot relations. It also uses the schemata to facilitate knowledge transfer to new domains. DSGFNet consists of a dialogue utterance encoder, a schema graph encoder, a dialogue-aware schema graph evolving network, and a schema graph enhanced dialogue state decoder. Empirical results on benchmark datasets (i.e., SGD, MultiWOZ2.1, and MultiWOZ2.2), show that DSGFNet outperforms existing methods.
UR  - http://dx.doi.org/10.18653/v1/2022.acl-long.10
A1  - Feng, Yue
A1  - Lipani, Aldo
A1  - Ye, Fanghua
A1  - Zhang, Qiang
A1  - Yilmaz, Emine
CY  - Dublin, Ireland
ID  - discovery10146908
PB  - ACL Anthology
N1  - ACL materials are Copyright © 1963?2022 ACL; other materials are copyrighted by their respective copyright holders. Materials prior to 2016 here are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International License. Permission is granted to make copies for the purposes of teaching and research. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License.
SP  - 115
Y1  - 2022/05//
TI  - Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Tracking
ER  -