R. William Soukoreff
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
R. William Soukoreff has a total of 1 co-authors. Here are the top co-authors by number of shared publications:
I. Scott Mackenzie
Department of Computing and Information Science , University of Guelph , Guelph, Ontario, NIG 2WI, Canada
1 shared publication
Latest Publications
- 1 November 1995
- Published by Taylor & Francis in Behaviour & Information Technology
- Vol. 14 (6) , 370-379
Theoretical upper and lower bounds on typing speed using a stylus and a soft keyboard
A theoretical model is presented to predict upper-and lower-bound text-entry rates using a stylus to tap on a soft QWERTY keyboard. The model is based on the Hick-Hyman law for choice reaction time, Fitts law for rapid aimed movements, and linguistic tables for the relative frequencies of letter-pairs, or digrams, in common English. The model's importance lies not only in the predictions provided, but in its characterization of text-entry tasks using keyboards. Whereas previous studies only use frequency probabilities of the 26 × 26 digrams in the Roman alphabet, our model accommodates the space har—the most common character in typing tasks. Using a very large linguistic table that decomposes digrams by position-within-words, we established start-of-word (space-letter) and end-of-word (letter-space) probabilities and worked from a 27 × 27 digram table. The model predicts a typing rate of 8.9wpm for novices unfamiliar with the QWERTY keyboard, and 30.1wpm for experts. Comparisons are drawn with empirical studies using a stylus and other forms of text entry.
- 1 November 1995
- Published by Taylor & Francis in Behaviour & Information Technology
- Vol. 14 (6) , 370-379
Theoretical upper and lower bounds on typing speed using a stylus and a soft keyboard
A theoretical model is presented to predict upper-and lower-bound text-entry rates using a stylus to tap on a soft QWERTY keyboard. The model is based on the Hick-Hyman law for choice reaction time, Fitts law for rapid aimed movements, and linguistic tables for the relative frequencies of letter-pairs, or digrams, in common English. The model's importance lies not only in the predictions provided, but in its characterization of text-entry tasks using keyboards. Whereas previous studies only use frequency probabilities of the 26 × 26 digrams in the Roman alphabet, our model accommodates the space har—the most common character in typing tasks. Using a very large linguistic table that decomposes digrams by position-within-words, we established start-of-word (space-letter) and end-of-word (letter-space) probabilities and worked from a 27 × 27 digram table. The model predicts a typing rate of 8.9wpm for novices unfamiliar with the QWERTY keyboard, and 30.1wpm for experts. Comparisons are drawn with empirical studies using a stylus and other forms of text entry.