On Suggesting Phrases vs. Predicting Words for Mobile Text Composition
Open accessAbstract
A system capable of suggesting multi-word phrases while someone is writing could supply ideas about content and phrasing and allow those ideas to be inserted efficiently. Meanwhile, statistical language modeling has provided various approaches to predicting phrases that users type. We introduce a simple extension to the familiar mobile keyboard suggestion interface that presents phrase suggestions that can be accepted by a repeated-tap gesture. In an extended composition task, we found that phrases were interpreted as suggestions that affected the content of what participants wrote more than conventional single-word suggestions, which were interpreted as predictions. We highlight a design challenge: how can a phrase suggestion system make valuable suggestions rather than just accurate predictions'
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A system that suggests phrases rather than words is more likely to be perceived as a collaborator and content contributor by users.
“There is evidence that a system that suggests phrases rather than words [5] is more likely to be perceived as a collaborator and content contributor by users.”
From Co-Writing with Opinionated Language Models Affects Users’ Views (2023) · cites this paper as [5]
Arnold et al. (2016) found that suggesting phrases aided writers more with ideas and language than suggesting words, and writers reported phrases provided more ideas than single-word suggestions.
“They found that phrases aided writers more with ideas (what to say) and language (how to say it).Writers also reported that phrases provided them with more ideas than single-word suggestions.”
From Interacting with Next-Phrase Suggestions: How Suggestion Systems Aid and Influence the Cognitive Processes of Writing (2023) · cites this paper as [20]
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Liu, Z. (2025) · International Conference on Federated Learning Technologies and Applications (FLTA) · doi:10.1109/flta67013.2025.11336736
Heuer, H., Goller, S., & Buschek, D. (2026) · i-com · doi:10.1515/icom-2025-0024
Komninos, A., Simou, I., & Garofalakis, J. D. (2026) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3816773
He, W. P., & Fussell, S. R. (2026) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3816046.3816235
Apprentissage, évaluation et rééducation de l’écriture
Véron-Delor, L., Pinto, S., Eusebio, A., et al. (2025) · De Boeck Supérieur eBooks · doi:10.3917/dbu.conna.2025.01.0233
- Authors
- Arnold, K. C., Gajos, K. Z., & Kalai, A. T.
- Affiliations
- Harvard University (US)
- Microsoft Research New England (United States) (US)
- Venue
- Proceedings of the 29th Annual Symposium on User Interface Software and Technology
- Publisher
- ACM
- Published
- 2016-10-16
- Pages
- 603-608
- OpenAlex
- W2539241874
- Cited by
- 69
- References
- 40
- Citations by year
- 2026: 5 · 2025: 12 · 2024: 7 · 2023: 9 · 2022: 6 · 2021: 9 · 2020: 8 · 2019: 7 · 2018: 4 · 2017: 2
- FWCI
- 2.96
- Type
- conference paper
- Language
- en
- Open access
- green
- nrs.harvard.edu
- Locations
- ACM Symposium on User Interface Software and Technology (UIST) (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- word prediction, mobile keyboards, statistical language models, user interface design, text entry
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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