On task effects in NLG corpus elicitation

A replication study using mixed effects modeling

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Abstract

Task effects in NLG corpus elicitation recently started to receive more attention, but are usu- ally not modeled statistically. We present a controlled replication of the study by Van Mil- tenburg et al. (2018b), contrasting spoken with written descriptions. We collected additional written Dutch descriptions to supplement the spoken data from the DIDEC corpus, and an- alyzed the descriptions using mixed effects modeling to account for variation between par- ticipants and items. Our results show that the effects of modality largely disappear in a con- trolled setting.
Original languageEnglish
Title of host publicationProceedings of the 12th International Conference on Natural Language Generation (INLG 2019)
EditorsKees van Deemter, Chenghua Lin, Hiroya Takamura
Publication statusPublished - 2019
Event12th International conference on Natural Language Generation (INLG 2019) - Tokyo, Japan
Duration: 29 Oct 20191 Nov 2019
https://www.inlg2019.com

Conference

Conference12th International conference on Natural Language Generation (INLG 2019)
CountryJapan
CityTokyo
Period29/10/191/11/19
Internet address

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Keywords

  • Natural Language Generation
  • Image Description
  • Modality

Cite this

van Miltenburg, E., van de Kerkhof, M., Koolen, R., Goudbeek, M., & Krahmer, E. (2019). On task effects in NLG corpus elicitation: A replication study using mixed effects modeling. In K. van Deemter, C. Lin, & H. Takamura (Eds.), Proceedings of the 12th International Conference on Natural Language Generation (INLG 2019)
van Miltenburg, Emiel ; van de Kerkhof, Merel ; Koolen, Ruud ; Goudbeek, Martijn ; Krahmer, Emiel. / On task effects in NLG corpus elicitation : A replication study using mixed effects modeling. Proceedings of the 12th International Conference on Natural Language Generation (INLG 2019). editor / Kees van Deemter ; Chenghua Lin ; Hiroya Takamura. 2019.
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title = "On task effects in NLG corpus elicitation: A replication study using mixed effects modeling",
abstract = "Task effects in NLG corpus elicitation recently started to receive more attention, but are usu- ally not modeled statistically. We present a controlled replication of the study by Van Mil- tenburg et al. (2018b), contrasting spoken with written descriptions. We collected additional written Dutch descriptions to supplement the spoken data from the DIDEC corpus, and an- alyzed the descriptions using mixed effects modeling to account for variation between par- ticipants and items. Our results show that the effects of modality largely disappear in a con- trolled setting.",
keywords = "Natural Language Generation, Image Description, Modality",
author = "{van Miltenburg}, Emiel and {van de Kerkhof}, Merel and Ruud Koolen and Martijn Goudbeek and Emiel Krahmer",
year = "2019",
language = "English",
editor = "{van Deemter}, Kees and Chenghua Lin and Hiroya Takamura",
booktitle = "Proceedings of the 12th International Conference on Natural Language Generation (INLG 2019)",

}

van Miltenburg, E, van de Kerkhof, M, Koolen, R, Goudbeek, M & Krahmer, E 2019, On task effects in NLG corpus elicitation: A replication study using mixed effects modeling. in K van Deemter, C Lin & H Takamura (eds), Proceedings of the 12th International Conference on Natural Language Generation (INLG 2019). 12th International conference on Natural Language Generation (INLG 2019), Tokyo, Japan, 29/10/19.

On task effects in NLG corpus elicitation : A replication study using mixed effects modeling. / van Miltenburg, Emiel; van de Kerkhof, Merel; Koolen, Ruud; Goudbeek, Martijn; Krahmer, Emiel.

Proceedings of the 12th International Conference on Natural Language Generation (INLG 2019). ed. / Kees van Deemter; Chenghua Lin; Hiroya Takamura. 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

TY - GEN

T1 - On task effects in NLG corpus elicitation

T2 - A replication study using mixed effects modeling

AU - van Miltenburg, Emiel

AU - van de Kerkhof, Merel

AU - Koolen, Ruud

AU - Goudbeek, Martijn

AU - Krahmer, Emiel

PY - 2019

Y1 - 2019

N2 - Task effects in NLG corpus elicitation recently started to receive more attention, but are usu- ally not modeled statistically. We present a controlled replication of the study by Van Mil- tenburg et al. (2018b), contrasting spoken with written descriptions. We collected additional written Dutch descriptions to supplement the spoken data from the DIDEC corpus, and an- alyzed the descriptions using mixed effects modeling to account for variation between par- ticipants and items. Our results show that the effects of modality largely disappear in a con- trolled setting.

AB - Task effects in NLG corpus elicitation recently started to receive more attention, but are usu- ally not modeled statistically. We present a controlled replication of the study by Van Mil- tenburg et al. (2018b), contrasting spoken with written descriptions. We collected additional written Dutch descriptions to supplement the spoken data from the DIDEC corpus, and an- alyzed the descriptions using mixed effects modeling to account for variation between par- ticipants and items. Our results show that the effects of modality largely disappear in a con- trolled setting.

KW - Natural Language Generation

KW - Image Description

KW - Modality

M3 - Conference contribution

BT - Proceedings of the 12th International Conference on Natural Language Generation (INLG 2019)

A2 - van Deemter, Kees

A2 - Lin, Chenghua

A2 - Takamura, Hiroya

ER -

van Miltenburg E, van de Kerkhof M, Koolen R, Goudbeek M, Krahmer E. On task effects in NLG corpus elicitation: A replication study using mixed effects modeling. In van Deemter K, Lin C, Takamura H, editors, Proceedings of the 12th International Conference on Natural Language Generation (INLG 2019). 2019