Finding the “right” answers for customers

Frank Schilder


Abstract
This talk will present a few NLG systems developed within Thomson Reuters providing information to professionals such as lawyers, accountants or traders. Based on the experience developing these system, I will discuss the usefulness of automatic metrics, crowd-sourced evaluation, corpora studies and expert reviews. I will conclude with exploring the question of whether developers of NLG systems need to follow ethical guidelines and how those guidelines could be established.
Anthology ID:
W17-3510
Volume:
Proceedings of the 10th International Conference on Natural Language Generation
Month:
September
Year:
2017
Address:
Santiago de Compostela, Spain
Venues:
INLG | WS
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
74
Language:
URL:
https://www.aclweb.org/anthology/W17-3510
DOI:
10.18653/v1/W17-3510
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-3510.pdf