On task effects in NLG corpus elicitation: a replication study using mixed effects modeling

Emiel van Miltenburg, Merel van de Kerkhof, Ruud Koolen, Martijn Goudbeek, Emiel Krahmer


Abstract
Task effects in NLG corpus elicitation recently started to receive more attention, but are usually not modeled statistically. We present a controlled replication of the study by Van Miltenburg et al. (2018b), contrasting spoken with written descriptions. We collected additional written Dutch descriptions to supplement the spoken data from the DIDEC corpus, and analyzed the descriptions using mixed effects modeling to account for variation between participants and items. Our results show that the effects of modality largely disappear in a controlled setting.
Anthology ID:
W19-8649
Volume:
Proceedings of the 12th International Conference on Natural Language Generation
Month:
October–November
Year:
2019
Address:
Tokyo, Japan
Editors:
Kees van Deemter, Chenghua Lin, Hiroya Takamura
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
403–408
Language:
URL:
https://aclanthology.org/W19-8649
DOI:
10.18653/v1/W19-8649
Bibkey:
Cite (ACL):
Emiel van Miltenburg, Merel van de Kerkhof, Ruud Koolen, Martijn Goudbeek, and Emiel Krahmer. 2019. On task effects in NLG corpus elicitation: a replication study using mixed effects modeling. In Proceedings of the 12th International Conference on Natural Language Generation, pages 403–408, Tokyo, Japan. Association for Computational Linguistics.
Cite (Informal):
On task effects in NLG corpus elicitation: a replication study using mixed effects modeling (van Miltenburg et al., INLG 2019)
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PDF:
https://aclanthology.org/W19-8649.pdf
Supplementary attachment:
 W19-8649.Supplementary_Attachment.pdf