The E2E NLG Challenge: A Tale of Two Systems

Charese Smiley, Elnaz Davoodi, Dezhao Song, Frank Schilder

Abstract
This paper presents the two systems we entered into the 2017 E2E NLG Challenge: TemplGen, a templated-based system and SeqGen, a neural network-based system. Through the automatic evaluation, SeqGen achieved competitive results compared to the template-based approach and to other participating systems as well. In addition to the automatic evaluation, in this paper we present and discuss the human evaluation results of our two systems.
Anthology ID:
W18-6558
Volume:
Proceedings of the 11th International Conference on Natural Language Generation
Month:
November
Year:
2018
Address:
Tilburg University, The Netherlands
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
472–477
Language:
URL:
https://aclanthology.org/W18-6558
DOI:
10.18653/v1/W18-6558
Bibkey:
Cite (ACL):
Charese Smiley, Elnaz Davoodi, Dezhao Song, and Frank Schilder. 2018. The E2E NLG Challenge: A Tale of Two Systems. In Proceedings of the 11th International Conference on Natural Language Generation, pages 472–477, Tilburg University, The Netherlands. Association for Computational Linguistics.
Cite (Informal):
The E2E NLG Challenge: A Tale of Two Systems (Smiley et al., INLG 2018)
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PDF:
https://preview.aclanthology.org/paclic-22-ingestion/W18-6558.pdf
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