An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking

Puyang Xu, Qi Hu


Abstract
We highlight a practical yet rarely discussed problem in dialogue state tracking (DST), namely handling unknown slot values. Previous approaches generally assume predefined candidate lists and thus are not designed to output unknown values, especially when the spoken language understanding (SLU) module is absent as in many end-to-end (E2E) systems. We describe in this paper an E2E architecture based on the pointer network (PtrNet) that can effectively extract unknown slot values while still obtains state-of-the-art accuracy on the standard DSTC2 benchmark. We also provide extensive empirical evidence to show that tracking unknown values can be challenging and our approach can bring significant improvement with the help of an effective feature dropout technique.
Anthology ID:
P18-1134
Volume:
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1448–1457
Language:
URL:
https://aclanthology.org/P18-1134
DOI:
10.18653/v1/P18-1134
Bibkey:
Cite (ACL):
Puyang Xu and Qi Hu. 2018. An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1448–1457, Melbourne, Australia. Association for Computational Linguistics.
Cite (Informal):
An End-to-end Approach for Handling Unknown Slot Values in Dialogue State Tracking (Xu & Hu, ACL 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/author-url/P18-1134.pdf