Relaxing stylus typing precision by geometric pattern matching

Fitts' law models the inherent speed-accuracy trade-off constraint in stylus typing. Users attempting to go beyond the Fitts' law speed ceiling will tend to land the stylus outside the targeted key, resulting in erroneous words and increasing users' frustration. We propose a geometric pattern matching technique to overcome this problem. Our solution can be used either as an enhanced spell checker or as a way to enable users to escape the Fitts' law constraint in stylus typing, potentially resulting in higher text entry speeds than what is currently theoretically modeled. We view the hit points on a stylus keyboard as a high resolution geometric pattern. This pattern can be matched against patterns formed by the letter key center positions of legitimate words in a lexicon. We present the development and evaluation of an "elastic" stylus keyboard capable of correcting words even if the user misses all the intended keys, as long as the user's tapping pattern is close enough to the intended word.

[1]  T. Landauer,et al.  Handbook of Human-Computer Interaction , 1997 .

[2]  Dennis E. Egan,et al.  Handbook of Human Computer Interaction , 1988 .

[3]  Poulton Ec,et al.  Unwanted asymmetrical transfer effects with balanced experimental designs. , 1966 .

[4]  L. Kaufman,et al.  Handbook of perception and human performance , 1986 .

[5]  Ronald Fagin,et al.  Relaxing the Triangle Inequality in Pattern Matching , 2004, International Journal of Computer Vision.

[6]  Shumin Zhai,et al.  SHARK2: a large vocabulary shorthand writing system for pen-based computers , 2004, UIST '04.

[7]  David G. Stork,et al.  Pattern Classification (2nd ed.) , 1999 .

[8]  Alan F. Blackwell,et al.  Dasher—a data entry interface using continuous gestures and language models , 2000, UIST '00.

[9]  Stuart M. Shieber,et al.  Abbreviated text input , 2003, IUI '03.

[10]  Theodosios Pavlidis,et al.  Optimal Correspondence of String Subsequences , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Henry Lieberman,et al.  A commonsense approach to predictive text entry , 2004, CHI EA '04.

[12]  Shumin Zhai,et al.  Movement model, hits distribution and learning in virtual keyboarding , 2002, CHI.

[13]  I. Scott MacKenzie,et al.  The design and evaluation of a high-performance soft keyboard , 1999, CHI '99.

[14]  Toshiyuki Masui,et al.  An efficient text input method for pen-based computers , 1998, CHI.

[15]  Shumin Zhai,et al.  Performance Optimization of Virtual Keyboards , 2002, Hum. Comput. Interact..

[16]  James R. Lewis,et al.  Keys and Keyboards , 1997 .

[17]  Shumin Zhai,et al.  Shorthand writing on stylus keyboard , 2003, CHI '03.

[18]  Joshua Goodman,et al.  Language modeling for soft keyboards , 2002, IUI '02.

[19]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[20]  Enrique Vidal,et al.  Computation of Normalized Edit Distance and Applications , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Amit Roy,et al.  Creating word-level language models for handwriting recognition , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[22]  Shigeo Abe DrEng Pattern Classification , 2001, Springer London.

[23]  E C Poulton,et al.  Unwanted asymmetrical transfer effects with balanced experimental designs. , 1966, Psychological bulletin.

[24]  Ian H. Witten,et al.  Adaptive Predictive Text Generation and the Reactive Keyboard , 1991, Interact. Comput..

[25]  Jan Krüger,et al.  A reduced QWERTY keyboard for mobile text entry , 2004, CHI EA '04.