On task effects in nlg corpus elicitation: A replication study using mixed effects modeling

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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.

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APA

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 INLG 2019 - 12th International Conference on Natural Language Generation, Proceedings of the Conference (pp. 403–408). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w19-8649

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