JustCorrect: Intelligent Post Hoc Text Correction Techniques on Smartphones
Open accessAbstract
Correcting errors in entered text is a common task but usually diffcult to perform on mobile devices due to tedious cursor navigation steps. In this paper, we present JustCorrect, an intelligent post hoc text correction technique for smartphones. To make a correction, the user simply types the correct text at the end of their current input, and JustCorrect will automatically detect the error and apply the correction in the form of an insertion or a substitution. In this way, manual navigation steps are bypassed, and the correction can be committed with a single tap. We solved two critical problems to support JustCorrect: (1) Correction Algorithm: we propose an algorithm that infers the user's correction intention from the last typed word. (2) Input Modalities: our study revealed that both tap and gesture were suitable input modalities for performing JustCorrect. Based on our fndings, we integrated JustCorrect into a soft keyboard. Our user studies show that using JustCorrect reduces the text correction time by 12.8% over the stock Android keyboard and by 9.7% over the "Type, then Correct" text correction technique by Zhang et al. (2019). Overall, JustCorrect complements existing post hoc text correction techniques, making error correction more automatic and intelligent.
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One study utilized the characters per minute (CPM) metric, while two other studies in the same paper did not report entry speed because the emphasis was on time required to correct errors already present in pre-entered text.
“One study utilized the characters per minute (CPM) metric [85], while two other studies in the same paper [80] did not report on the entry speed, since the emphasis was on the time required to correct errors already present in the pre-entered text.”
From A Review of Design and Evaluation Practices in Mobile Text Entry for Visually Impaired and Blind Persons (2023) · cites this paper as [80]
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Cites
Efficient Estimation of Word Representations in Vector Space
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1301.3781 · Cited by 26,568 · see citing works
Binary Codes capable of currecting deletions, insertions, and reversals
Levenshtein, V. I. (1965) · Soviet physics. Doklady · Cited by 10,387 · see citing works
The String-to-String Correction Problem
Wagner, R. A., & Fischer, M. J. (1974) · Journal of the ACM · doi:10.1145/321796.321811 · Cited by 3,079 · see citing works
Corpus of Contemporary American English (COCA)
Davies, M. G. (2015) · Harvard Dataverse · doi:10.7910/dvn/amuduw · Cited by 589 · see citing works
Proceedings of the International Conference on Spoken Language Processing.
Lickley, R. J., & Bard, E. G. (1992) · Cited by 558 · see citing works
On structuring probabilistic dependences in stochastic language modelling
Ney, H., Essen, U., & Kneser, R. (1994) · Computer Speech & Language · doi:10.1006/csla.1994.1001 · Cited by 517 · see citing works
Shift: a technique for operating pen- based interfaces using touch
Vogel, D., & Baudisch, P. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240727 · Cited by 486 · see citing works
Kristensson, P.-O., & Zhai, S. (2004) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/1029632.1029640 · Cited by 419 · see citing works
Shorthand writing on stylus keyboard
Zhai, S., & Kristensson, P.-O. (2003) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/642611.642630 · Cited by 371 · see citing works
Vector Space Models of Word Meaning and Phrase Meaning: A Survey
Erk, K. (2012) · Language and Linguistics Compass · doi:10.1002/lnco.362 · Cited by 321 · see citing works
Holz, C., & Baudisch, P. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979308 · Cited by 278 · see citing works
Measuring errors in text entry tasks
Soukoreff, R. W., & MacKenzie, I. S. (2001) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/634067.634256 · Cited by 242 · see citing works
Bi, X., Li, Y., & Zhai, S. (2013) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2466180 · Cited by 236 · see citing works
Self-citationComparing Speech and Keyboard Text Entry for Short Messages in Two Languages on Touchscreen Phones
Ruan, S., Wobbrock, J. O., Liou, K., Ng, A. Y., & Landay, J. A. (2018) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3161187 · Cited by 223 · see citing works
Self-citationPhysically large displays improve performance on spatial tasks
Tan, D. S., Gergle, D., Scupelli, P. G., & Pausch, R. F. (2006) · ACM Transactions on Computer-Human Interaction · doi:10.1145/1143518.1143521 · Cited by 199 · see citing works
How do People Type on Mobile Devices?
Palin, K., Feit, A. M., Kim, S., Kristensson, P. O., & Oulasvirta, A. (2019) · International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) · doi:10.1145/3338286.3340120 · Cited by 191 · see citing works
Zhai, S., & Kristensson, P. O. (2012) · Communications of the ACM · doi:10.1145/2330667.2330689 · Cited by 169 · see citing works
Strategies for accelerating on-line learning of hotkeys
Grossman, T., Dragicevic, P., & Balakrishnan, R. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240865 · Cited by 163 · see citing works
Language modeling for soft keyboards
Goodman, J., Venolia, G. D., Steury, K. R., & Parker, C. R. (2002) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/502716.502753 · Cited by 162 · see citing works
Vertanen, K., Memmi, H., Emge, J., Reyal, S., & Kristensson, P. O. (2015) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702135 · Cited by 134 · see citing works
Li, F. C. Y., Guy, R. T., Yatani, K., & Truong, K. N. (2011) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/2047196.2047257 · Cited by 109 · see citing works
Zhang, M. R., Wen, H., & Wobbrock, J. O. (2019) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3332165.3347924 · Cited by 86 · see citing works
Self-citationCommand strokes with and without preview
Kristensson, P. O., & Zhai, S. (2007) · ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) · doi:10.1145/1240624.1240797 · Cited by 62 · see citing works
Bi, X., Ouyang, T. Y., & Zhai, S. (2014) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2556288.2557414 · Cited by 59 · see citing works
Self-citationFuccella, V., Isokoski, P., & Martin, B. (2013) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2481385 · Cited by 57 · see citing works
Evaluation of a Smart-Restorable Backspace Technique to Facilitate Text Entry Error Correction
Arif, A. S., Kim, S., Stuerzlinger, W., Lee, G., & Mazalek, A. (2016) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858407 · Cited by 30 · see citing works
Alvina, J., Griggio, C. F., Bi, X., & Mackay, W. E. (2017) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3126594.3126639 · Cited by 25 · see citing works
Self-citationA glimpse of mobile text entry errors and corrective behaviour in the wild
Komninos, A., Dunlop, M. D., Katsaris, K., & Garofalakis, J. D. (2018) · International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (MobileHCI Adjunct) · doi:10.1145/3236112.3236143 · Cited by 25 · see citing works
Sindhwani, S., Lutteroth, C., & Weber, G. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300433 · Cited by 24 · see citing works
Cui, W., Zheng, J., Lewis, B., Vogel, D., & Bi, X. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300395 · Cited by 20 · see citing works
Self-citationCapacity of the Medium and Behavior of Automata
Barzdin, Y. M. (1965) · Soviet physics. Doklady · Cited by 18 · see citing works
Sim, K. C. (2012) · ACM International Conference on Multimodal Interaction (ICMI) · doi:10.1145/2388676.2388793 · Cited by 16 · see citing works
Sim, K. C. (2010) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt.2010.5700825 · Cited by 16 · see citing works
Motor efficiency of text entry in a combination of a soft keyboard and unistrokes
Isokoski, P., Martin, B., Gandouly, P., & Stephanov, T. (2010) · Nordic Conference on Human-Computer Interaction · doi:10.1145/1868914.1869004 · Cited by 13 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- [1]Agirre Eneko, Cer Daniel, Diab Mona, Gonzalez-Agirre Aitor, and Guo Weiwei. 2013. *SEM 2013 shared task: Semantic Textual Similarity. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity. Association for Computational Linguistics, Atlanta, Georgia, USA, 32– 43. https://www.aclweb.org/anthology/S13-1004
- [14]Heafeld Kenneth. 2011. KenLM: Faster and Smaller Language Model Queries. In Proceedings of the EMNLP 2011 Sixth Workshop on Statistical Machine Translation. Edinburgh, Scotland, United Kingdom, 187– 197. https://kheafield.com/papers/avenue/kenlm.pdf
- [43]Mingrui Ray Zhang and O. Jacob Wobbrock. 2020. Gedit: Keyboard gestures for mobile text editing. In Proceedings of Graphics Interface (GI ‘20) (GI ‘20). Canadian Information Processing Society, Toronto, Ontario, 97– 104.
Cited by
Sorted by citations
Co-Writing with Opinionated Language Models Affects Users’ Views
Jakesch, M., Bhat, A., Buschek, D., Zalmanson, L., & Naaman, M. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581196 · Cited by 265 · see citing works
Lehmann, F., Markert, N., Dang, H., & Buschek, D. (2022) · Mensch und Computer 2022 · doi:10.1145/3543758.3543947 · Cited by 25 · see citing works
Komninos, A., Stefanis, V., & Garofalakis, J. (2023) · Multimodal Technologies and Interaction · doi:10.3390/mti7020022 · Cited by 16 · see citing works
- Authors
- Cui, W., Zhu, S., Zhang, M. R., Schwartz, H. A., Wobbrock, J. O., & Bi, X.
- Affiliations
- Stony Brook University (US)
- University of Washington (US)
- Venue
- Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology
- Publisher
- ACM
- Published
- 2020-10-20
- Volume
- 2020
- Pages
- 487-499
- PMC
- PMC12714354
- OpenAlex
- W3093820610
- Cited by
- 24
- References
- 35
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 1 · 2023: 2 · 2022: 6 · 2021: 3
- FWCI
- 2.01
- Type
- conference paper
- Language
- en
- Open access
- green
- pmc.ncbi.nlm.nih.gov
- Locations
- ACM Symposium on User Interface Software and Technology (UIST) (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion)
- Funders
- NIH (R01EY030085)
- NSF (CHS-1815514)
- 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 › Information Systems › User Authentication and Security Systems
- Keywords
- mobile text entry, error correction, virtual keyboard
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