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Predicting text entry speed on mobile phones

Predicting text entry speed on mobile phones CHI 2 0 0 0 ¢ 1 - 6 APRIL 2 0 0 0 Papers Predicting Text Entry Speed on Mobile Phones Miika Silfverberg Nokia Research Center P.O. B o x 407 FIN-00045 Nokia Group Finland +358 40 528 7759 miika.silfverberg @nokia.com I. Scott MacKenzie Dept. o f M a t h e m a t i c s & Statistics York University Toronto, Ontario C a n a d a M 3 J 1P3 +1 416 736 2100 smackenzie @ acm.org Panu Korhonen Nokia Research Center P.O. B o x 407 FIN-00045 Nokia Group Finland +358 40 504 7123 panu.korhonen @nokia.com 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 twokey 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 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Predicting text entry speed on mobile phones

Association for Computing Machinery — Apr 1, 2000

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References (21)

Datasource
Association for Computing Machinery
Copyright
Copyright © 2000 by ACM Inc.
ISBN
1-58113-216-6
doi
10.1145/332040.332044
Publisher site
See Article on Publisher Site

Abstract

CHI 2 0 0 0 ¢ 1 - 6 APRIL 2 0 0 0 Papers Predicting Text Entry Speed on Mobile Phones Miika Silfverberg Nokia Research Center P.O. B o x 407 FIN-00045 Nokia Group Finland +358 40 528 7759 miika.silfverberg @nokia.com I. Scott MacKenzie Dept. o f M a t h e m a t i c s & Statistics York University Toronto, Ontario C a n a d a M 3 J 1P3 +1 416 736 2100 smackenzie @ acm.org Panu Korhonen Nokia Research Center P.O. B o x 407 FIN-00045 Nokia Group Finland +358 40 504 7123 panu.korhonen @nokia.com 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 twokey 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

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