David J. Ward
Alan F. Blackwell
- 1.Project Gutenberg. Fine literature digitally re-published. http://www.promo.net/pg/.Google Scholar
- 2.T.C. Bell, J.G. Cleary, and I.H. Witten. Text Compres-sion. Prentice Hall, NJ, 1990. Google ScholarDigital Library
- 3.R. Bellman. Dynamic Programming. Princeton Uni-versity Press, Boston, 1957. Google ScholarDigital Library
- 4.T. Bellman and I.S. MacKenzie. A probabilistic char-acter layout strategy for mobile text entry. In Proc. Graphics Interface '98, pages 168-176, 1998.Google Scholar
- 5.Jorge Luis Borges. The Library of Babel. David R. Godine, 2000.Google Scholar
- 6.C. G. Drury and E. R. Hoffmann. A model for movement time on data-entry keyboards. Ergonomics, 35(2):129-147, 1992.Google ScholarCross Ref
- 7.G. Gilchrist. Archive Comparison Test. Available at http://www.geocities.com/ SiliconValley/Park/4264/act.html.Google Scholar
- 8.D. Goldberg and C. Richardson. Touch-typing with a stylus. In Proceedings of the INTERCHI '93 Confer-ence on Human Factors in Computing Systems., pages 168-176. ACM, New York, 1993. Google ScholarDigital Library
- 9.M.E. Gordon, H.G. Henry, and D.P. Massengill. Stud-ies in typewriter keyboard modification: I. effects of amount of change, finger load, and copy content on accuracy and speed. Journal of Applied Psychology, 60:220-226, 1975.Google ScholarCross Ref
- 10.M. Hunter, S. Zhai, and B. A. Smith. Physics-based graphical keyboard design. In Proceedings of CHI'2000., volume 2, pages 157-158. Google ScholarDigital Library
- 11.K.H.E. Kroemer. Performance on a prototype key-board with ternary chorded keys. Applied Ergonomics, 23(2):83-90, 1992.Google ScholarCross Ref
- 12.I. S. MacKenzie, S. X. Zhang, and R. W. Soukoreff. Text entry using soft keyboards. Behaviour & Informa-tion Technology., 18:235-244.Google Scholar
- 13.I.S. Mackenzie. Movement time prediction in human-computer interfaces. In Readings in Human-Computer Interaction (2nd ed.), pages 483-493. Kaufmann, Los Altos, CA., 1992. R. M. Baecker, W. A. S. Buxton, J. Grudin and S. Greenberg (Eds.). Google Scholar
- 14.I.S. MacKenzie, B. Nonnecke, C. McQueen, S. Ridder-sma, and M. Meltz. A comparison of three methods of character entry on pen-based computers. In Human Factors and Ergonomics Society 38th Annual Meeting, pages 330-334. Santa Monica, CA. Human Factors So-ciety, 1994.Google ScholarCross Ref
- 15.I.S. MacKenzie and S.X. Zhang. The design and eval-uation of a high-performance soft keyboard. In Pro-ceedings of the ACM Conference on Human Factors in Computing Systems - CHI '99, pages 25-31. New York: ACM. Google ScholarDigital Library
- 16.I.S. MacKenzie and S.X. Zhang. The immediate us-ability of Graffiti. In Proceedings of Graphics Inter-face '97, pages 129-137. Toronto: Canadian Informa-tion Processing Society. Google ScholarDigital Library
- 17.E. Matias, I.S. MacKenzie, and W. Buxton. Half-QWERTY: A one-handed keyboard facilitating skill transfer from QWERTY. In Proceedings of the INTER-CHI '93 Conference on Human Factors in Computing Systems., pages 88-94. ACM, New York. Google ScholarDigital Library
- 18.A. Newell and P.S. Rosenbloom. Mechanisms of skill acquisition and the power law of learning. In Cognitive Skills and Their Acquisition , edited by J. R. Anderson, pages 1-55. L. Erlbaum Associates, NJ, 1981.Google Scholar
- 19.D.A. Norman and D. Fisher. Why alphabetic keyboards are not easy to use: Keyboard layout doesn't much mat-ter. Human Factors, 24:509-519, 1982.Google ScholarCross Ref
- 20.J. K. Ousterhout. Tcl and the Tk toolkit. Addison-Wesley, Reading, Mass., 1994. Google ScholarDigital Library
- 21.K. Perlin. Quikwriting: continuous stylus-based text entry. In ACM Symposium on User Interface Software and Technology, pages 215-216, 1998. Google ScholarDigital Library
- 22.D. D. Salcucci and J. R. Anderson. Intelligent gaze-added interface. In CHI 2000, pages 273-280. Google ScholarDigital Library
- 23.A. Sears, D. Revis, J. Swatski, R. Crittenden, and B. Shneiderman. Investigating touchscreen typing: the effect of keyboard size on typing speed. Behaviour and Information Technology, 12:17-22, 1993.Google ScholarCross Ref
- 24.C. E. Shannon. Collected Papers. IEEE Press, New York, 1993. Edited by N. J. A. Sloane and A. D. Wyner.Google Scholar
- 25.M. Silfverberg, I. S. MacKenzie, and P. Korhonen. Pre-dicting text entry speed on mobile phones. In proceed-ings CHI 2000, pages 9-16. Google ScholarDigital Library
- 26.W.J. Teahan. Probability estima-tion for PPM. In Proceedings NZCSRSC'95. Available from http://www.cs.waikato.ac.nz/~wjt/ papers/NZCSRSC.ps.gz.Google Scholar
- 27.D. Venolia and F. Neiberg. T-Cube: A fast, self-disclosing pen-based alphabet. In Proceedings CHI '94, pages 265-270, 1994. Google ScholarDigital Library
- 28.A. J. Viterbi. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory, IT-13:260-269, 1967.Google ScholarCross Ref
- 29.David Ward. Non-interactive Dasher demon-stration. http://wol.ra.phy.cam.ac.uk/ djw30/dasher/.Google Scholar
Index Terms
- Dasher—a data entry interface using continuous gestures and language models
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