Adversarial domain adaptation for variational neural language generation in dialogue systems

Tran, Van Khanh and Nguyen, Le-Minh 2018, Adversarial domain adaptation for variational neural language generation in dialogue systems, in COLING 2018 : Proceedings of the 27th International Conference on Computational Linguistics, Association for Computational Linguistics, Stroudsburg, Pa., pp. 1205-1217.

Attached Files
Name Description MIMEType Size Downloads

Title Adversarial domain adaptation for variational neural language generation in dialogue systems
Author(s) Tran, Van KhanhORCID iD for Tran, Van Khanh orcid.org/0000-0002-3445-2596
Nguyen, Le-Minh
Conference name Association for Computational Linguistics. Conference (27th : 2018 : Santa Fe, N.M.)
Conference location Santa Fe, N.M.
Conference dates 2018/08/20 - 2018/08/26
Title of proceedings COLING 2018 : Proceedings of the 27th International Conference on Computational Linguistics
Editor(s) [Unknown]
Publication date 2018
Series Association for Computational Linguistics Conference
Start page 1205
End page 1217
Total pages 13
Publisher Association for Computational Linguistics
Place of publication Stroudsburg, Pa.
Keyword(s) Domain Adaptation
Natural Language Generation (NLG)
Spoken Dialogue Systems
ISBN 978-1-948087-50-6
Language eng
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2018, Association for Computational Linguistics
Persistent URL http://hdl.handle.net/10536/DRO/DU:30122163

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 12 Abstract Views, 5 File Downloads  -  Detailed Statistics
Created: Thu, 30 May 2019, 09:20:02 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.