Supplementary materials for CHI 2019 paper: "VelociWatch: Designing and Evaluating a Virtual Keyboard for the Input of Challenging Text" [1]

Files
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exp1-4.xlsx     - Spreadsheet with participant data from all experiments
exp3.mp4        - Video shown to participants before Experiment 3
exp4.mp4        - Video shown to participants before Experiment 4

twitter-iv.txt  - Mobile twitter phrase set, 194 in-vocabulary phrases
twitter-oov.txt - Mobile twitter phrase set, 213 phrases with one OOV word
watch-iv.txt    - 81 in-vocabulary phrases used in our experiments
watch-oov.txt   - 43 OOV phrases used in our experiments
vocab-100k.txt  - Word list used to determine whether a word was OOV

References
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[1] Vertanen, K., Gaines, D., Fletcher, C., Stanage, A. M., Watling, R., and Kristensson, P. O. VelociWatch: Designing and Evaluating a Virtual Keyboard for the Input of Challenging Text. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '19, ACM (New York, NY, USA, 2019). https://doi.org/10.1145/3290605.3300821

[2] Vertanen, K., Memmi, H., Emge, J., Reyal, S., and Kristensson, P. O. VelociTap: Investigating fast mobile text entry using sentence-based decoding of touchscreen keyboard input. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '15, ACM (New York, NY, USA, 2015), 659–668. http://doi.acm.org/10.1145/2702123.2702135

[3] Vertanen, K., Fletcher, C., Gaines, D., Gould, J., and Kristensson, P. O. The impact of word, multiple word, and sentence input on virtual keyboard decoding performance. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '18, ACM (New York, NY, USA, 2018), 626:1–626:12. http://doi.acm.org/10.1145/3173574.3174200
