Memory State Tracker: A Memory Network based Dialogue State Tracker

被引:0
作者
Wang, Di [1 ]
O'Keefe, Simon [1 ]
机构
[1] Univ York, Dept Comp Sci, York, N Yorkshire, England
来源
ICAART: PROCEEDINGS OF THE 13TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE - VOL 1 | 2021年
关键词
Dialogue State Tracker; Memory Network;
D O I
10.5220/0010385705330538
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Dialogue State Tracking (DST) is a core component towards task oriented dialogue system. It fills manually-set slots at each turn of an utterance, which indicate the current topics or user requirement. In this work we propose a memory based state tracker that includes a memory encoder which encodes the dialogue history into a memory vector, and then connects to a pointer network which makes predictions. Our model reached a joint goal accuracy of 49.16% on MultiWOZ 2.0 data set (Budzianowski et al., 2018) and 47.27% on MultiWOZ 2.1 data set (Eric et al., 2019), outperforming the benchmark result.
引用
收藏
页码:533 / 538
页数:6
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