Predicting text entry speed on mobile phones

By Miika Silfverberg, I. Mackenzie, Panu Korhonen. International Conference on Human Factors in Computing Systems, 2000

372 citations recorded by the source corpus.

We present a model for predicting expert text entry rates for several input methods on a 12-key mobile phone keypad. The model includes a movement component based on Fitts' law and a linguistic component based on digraph, or letter-pair, probabilities. Predictions are provided for one-handed thumb and two-handed index finger input. For the traditional multi-press method or the lesser-used two-key method, predicted expert rates vary from about 21 to 27 words per minute (wpm). The relatively new T9 method works with a disambiguating algorithm and inputs each character with a single key press. Predicted expert rates vary from 41 wpm for one-handed thumb input to 46 wpm for two-handed index finger input. These figures are degraded somewhat depending on the user's strategy in coping with less-than-perfect disambiguation. Analyses of these strategies are presented.

Subfields: Cognitive Neuroscience, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/2927b1579e60075caceac5d3e60143ff2ebeb28c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

  1. I. Mackenzie
  2. R. William Soukoreff
  3. David John Cameron MacKay
  4. David J. Ward
  5. Chi Zhang
  6. Rui Yao
  7. Alan F. Blackwell
  8. Jinpeng Cai

In Human-Computer Interaction

  1. I. Mackenzie
  2. R. William Soukoreff
  3. David John Cameron MacKay
  4. Chi Zhang
  5. Rui Yao
  6. Jinpeng Cai
  7. David J. Ward
  8. Alan F. Blackwell

Citations in the corpus