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        <title>On task effects in NLG corpus elicitation: a replication study using mixed effects modeling</title>
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    <name type="personal">
        <namePart type="given">Emiel</namePart>
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    <name type="personal">
        <namePart type="given">Martijn</namePart>
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            <title>Proceedings of the 12th International Conference on Natural Language Generation</title>
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            <namePart type="family">van Deemter</namePart>
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        <name type="personal">
            <namePart type="given">Chenghua</namePart>
            <namePart type="family">Lin</namePart>
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        <name type="personal">
            <namePart type="given">Hiroya</namePart>
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    <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.</abstract>
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        <date>2019-oct–nov</date>
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%0 Conference Proceedings
%T On task effects in NLG corpus elicitation: a replication study using mixed effects modeling
%A van Miltenburg, Emiel
%A van de Kerkhof, Merel
%A Koolen, Ruud
%A Goudbeek, Martijn
%A Krahmer, Emiel
%Y van Deemter, Kees
%Y Lin, Chenghua
%Y Takamura, Hiroya
%S Proceedings of the 12th International Conference on Natural Language Generation
%D 2019
%8 oct–nov
%I Association for Computational Linguistics
%C Tokyo, Japan
%F van-miltenburg-etal-2019-task
%X 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.
%R 10.18653/v1/W19-8649
%U https://aclanthology.org/W19-8649
%U https://doi.org/10.18653/v1/W19-8649
%P 403-408

Markdown (Informal)

[On task effects in NLG corpus elicitation: a replication study using mixed effects modeling](https://aclanthology.org/W19-8649) (van Miltenburg et al., INLG 2019)

• On task effects in NLG corpus elicitation: a replication study using mixed effects modeling (van Miltenburg et al., INLG 2019)

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.