Predicting text entry speed on mobile phones

ABSTRACT

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.

REFERENCES

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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.5 COMPUTER SYSTEM IMPLEMENTATION
      C.5.3 Microcomputers
          Subjects: Portable devices (e.g., laptops, personal digital assistants)

Additional Classification:
  G. Mathematics of Computing
  G.2 DISCRETE MATHEMATICS

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
  I.7 DOCUMENT AND TEXT PROCESSING

General Terms:
Algorithms, Design, Experimentation, Human Factors, Management, Measurement, Performance, Theory

Keywords:
Fitts' law, digraph frequencies, human performance modeling, keypad input, mobile phones, mobile systems, text entry