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The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers

Titelangaben

Buschek, Daniel ; Zürn, Martin ; Eiband, Malin:
The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers.
2021
Veranstaltung: CHI Conference on Human Factors in Computing Systems , 08.05.-13.05.2021 , Online (Originally: Yokohama, Japan).
(Veranstaltungsbeitrag: Kongress/Konferenz/Symposium/Tagung , Paper )
DOI: https://doi.org/10.1145/3411764.3445372

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AI Tools - Continuous Interaction with Computational Intelligence Tools
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https://osf.io/7q4c8/

Abstract

We present an in-depth analysis of the impact of multi-word suggestion choices from a neural language model on user behaviour regarding input and text composition in email writing. Our study for the first time compares different numbers of parallel suggestions, and use by native and non-native English writers, to explore a trade-off of "efficiency vs ideation", emerging from recent literature. We built a text editor prototype with a neural language model (GPT-2), refined in a prestudy with 30 people. In an online study (N=156), people composed emails in four conditions (0/1/3/6 parallel suggestions). Our results reveal (1) benefits for ideation, and costs for efficiency, when suggesting multiple phrases; (2) that non-native speakers benefit more from more suggestions; and (3) further insights into behaviour patterns. We discuss implications for research, the design of interactive suggestion systems, and the vision of supporting writers with AI instead of replacing them.

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Publikationsform: Veranstaltungsbeitrag (Paper)
Begutachteter Beitrag: Ja
Keywords: Text entry; typing; language model; text suggestions; deep learning; neural network; dataset
Institutionen der Universität: Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik
Fakultäten
Fakultäten > Fakultät für Mathematik, Physik und Informatik
Titel an der UBT entstanden: Ja
Themengebiete aus DDC: 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik
Eingestellt am: 06 Apr 2021 12:02
Letzte Änderung: 31 Mai 2021 11:59
URI: https://eref.uni-bayreuth.de/id/eprint/64579