ABSTRACT
The challenge of mobile text entry is exacerbated as mobile devices are used in a number of situations and with a number of hand postures. We introduce ContextType, an adaptive text entry system that leverages information about a user's hand posture (using two thumbs, the left thumb, the right thumb, or the index finger) to improve mobile touch screen text entry. ContextType switches between various keyboard models based on hand posture inference while typing. ContextType combines the user's posture-specific touch pattern information with a language model to classify the user's touch events as pressed keys. To create our models, we collected usage patterns from 16 participants in each of the four postures. In a subsequent study with the same 16 participants comparing ContextType to a control condition, ContextType reduced total text entry error rate by 20.6%.
Supplemental Material
- Azenkot, S. and Zhai, S. (2012). Touch behavior with different postures on soft smartphone keyboards. Proc.. MobileHCI'12. New York: ACM Press, pp. 251--260. Google ScholarDigital Library
- Chen, S.F. and Goodman, J. (1996). An empirical study of smoothing techniques for language modeling. Proc. Assoc. Comp. Ling.,1996. Stroudsberg, pp. 310--318. Google ScholarDigital Library
- Findlater, L. and Wobbrock, J. (2012). Personalized input: Improving ten-finger touchscreen typing through automatic adaptation. Proc. CHI'12. New York: ACM Press, pp. 815--824. Google ScholarDigital Library
- Goel, M., Wobbrock, J.O., and Patel, S.N. (2012). GripSense: Using built-in sensors to detect hand posture and pressure on commodity mobile phones. Proc. UIST'12. New York: ACM Press, pp. 545--554. Google ScholarDigital Library
- Goodman, J., Venolia, G., Steury, K., and Parker, C. (2002). Language modeling for soft keyboards. Proc. IUI'02. New York: ACM Press, pp. 194--195. Google ScholarDigital Library
- Kucera, H. and Francis, W. (1967). Computational Analysis of Present-Day American English.Google Scholar
- MacKenzie, I.S. and Soukoreff, R.W. (2003). Phrase sets for evaluating text entry techniques. Proc. CHI'03 EA. ACM Press. Google ScholarDigital Library
- Sears, A., Lin, M., Jacko, J., and Xiao, Y. (2003). When computers fade pervasive computing and situationally-induced impairments and disabilities. HCI International 2'03, pp. 1298--1302.Google Scholar
- Soukoreff, R.W. and MacKenzie, I.S. (2003). Metrics for text entry research: an evaluation of MSD and KSPC, and a new unified error metric. Proc. CHI'03. New York: ACM Press, pp. 113--120. Google ScholarDigital Library
- Wobbrock, J.O., Findlater, L., Gergle, D., and Higgins, J.J. (2011). The aligned rank transform for nonparametric factorial analyses using only anova procedures. Proc. CHI'11. New York: ACM Press, pp. 143--146. Google ScholarDigital Library
- Wobbrock, J.O., Myers, B.A., and Aung, H.H. (2008). The performance of hand postures in front- and back-of-device interaction for mobile computing. International Journal of Human-Computer Studies 66,12. Duluth, MN: Academic Press, pp. 857--875. 0" 5" 10" 15" Two$thumbs+ Le.+ Index+ Right+ Total+ Mean Total Error Rate (%) Control" ContextType" Google ScholarDigital Library
Index Terms
- ContextType: using hand posture information to improve mobile touch screen text entry
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