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Text Input: Techniques and Research Tools

Text Input: Techniques and Research Tools. Tampere University Computer Human Interaction Group. Poika Isokoski at NIT2003 30.2.2003 Background: A Collage of images scanned from: Albertine Gaur. A history of writing. The British Library, London, UK, 2 edition, 1987. Contents. Introduction

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Text Input: Techniques and Research Tools

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  1. Text Input: Techniques and Research Tools TampereUniversityComputerHumanInteractionGroup Poika Isokoski at NIT2003 30.2.2003 Background: A Collage of images scanned from: Albertine Gaur. A history of writing. The British Library, London, UK, 2 edition, 1987.

  2. Contents • Introduction • Historical Notes • Text Input Methods • Keyboards • Text Recognition • Pointing • Temporal • Measuring Performance • More Info 1 Text Input: Techniques and Research Tools

  3. Introduction • For some time in the past text input was not a very interesting research topic • Desktop keyboard is so good that it cannot be easily beaten • Additional Inferior text input methods have not been needed • Mobile computing has changed the situation • Keyboards are difficult to fit in a mobile phone or a PDA. • Handwriting recognition is difficult and writing is slow • Speech recognition is even more difficult • => There is no obvious solution. • Is this there a real and lasting need for a new writing system(s)? 2 Text Input: Techniques and Research Tools

  4. Historical Notes • Interplay of culture and writing • Culture chooses a writing system that best suits it • need to communicate • need for information storage • available technology and materials • needs of the individuals in power • Good inventions are meaningless if there is no need for them 3 Text Input: Techniques and Research Tools

  5. Historical Notes 4 Text Input: Techniques and Research Tools

  6. Historical Notes • Separation of interfaces • For a long time there was only one interface • Written on paper (or whatever material the culture preferred) • Stored on paper • Read from paper • Pen movement was connected to the form of the written character which again was tightly coupled with the form of the character to be read. 5 Text Input: Techniques and Research Tools

  7. Historical Notes • After Gutenberg • Written in printing press (or with a typewriter) • Stored on paper • Read from paper • Writing motion is not necessarily the same as the form of the characters 6 Text Input: Techniques and Research Tools

  8. Historical Notes • Today • Written with text input methods • Stored as bits (magnetic fields, dots on glass, etc.) • Read from text output system. • None of the tasks are mechanically connected. There is software in between. • Having separate system for each phase: • Gives more freedom for optimization of each task • Requires more skills from the user of texts 7 Text Input: Techniques and Research Tools

  9. Historical Notes 8 Text Input: Techniques and Research Tools

  10. Text Input Methods 9 Text Input: Techniques and Research Tools

  11. Keyboards • Context free • QWERTY • 12-key multi-press • Chord – GKOS as an example( http://gkos.com ) • Contextual • Instant Text • Microsoft Excel 12 Text Input: Techniques and Research Tools

  12. Keyboards • How to measure performance • Speed and error rate (more on these later) • In desktop use: physical stress (dvorak-QWERTY-debate) • How to model/predict performance • No good solution for multi-finger operation • For one-finger typing use same stuff as with soft-keyboards (discussed later) • With multi-press/contextual methods consider the number of key presses, finger travel, and the need for visual feedback. 13 Text Input: Techniques and Research Tools

  13. Text Recognition • Machine readable • Bar-codes • Human Readable • OCR • On-line handwriting recognition • Off-line recognition with information on writing dynamics images from: http://www.adams1.com/pub/russadam/upccode.html http://www.adams1.com/pub/russadam/stack.html 14 Text Input: Techniques and Research Tools

  14. Text Recognition (2) • Unistrokes • Explicit segmentation by lifting the pen • Character level: Unistrokes, Graffiti • Word level: octave • ( http://www.e-acute.fr/English/manual/manualV1.html (not available since 2002 )) 15 Text Input: Techniques and Research Tools

  15. Text Recognition • How to measure performance • Speed • Human error rate • Recognition error rate • Need for training (user or algorithms) • How to model (handwriting) • Models are complicated • Steering law • Models for post-mortem analysis/synthesis (non-predictive) • Model for unistroke writing (simple, but not very accurate) • All these models require some empirical data on the task, therefore they cannot be used in pure prediction. 16 Text Input: Techniques and Research Tools

  16. Pointing • Continuous gesturing (session level unistrokes) • Dasher (web demo) ( http://wol.ra.phy.cam.ac.uk/djw30/dasher/) • Quikwriting (web demo) ( http://mrl.nyu.edu/~perlin/demos/quikwriting.html ) 17 Text Input: Techniques and Research Tools

  17. Pointing • Direct • Soft-keyboards:qwerty, fitaly, OPTI (http://www.yorku.ca/mack/CHI99a.html ) • Menu hybrids • MessageEase ( http://www.exideas.com/ ) • Indirect • FOCL (http://www.yorku.ca/mack/GI98.html ) Q F U M C K Z space O T H space B S R E A W X space I N D space J P V G L Y F1 T A S B O D G I V space W H M L R Y K J Z F C P N E U Q X 18 Text Input: Techniques and Research Tools

  18. Pointing • How to measure performance • Speed and error rate • How to model • Direct: Fitts’ law + statistics on the text to be written • Indirect: number of keypresses (independent KSPC). 19 Text Input: Techniques and Research Tools

  19. Temporal input • Morse code • How to measure performance • Speed and accuracy • How to model • KSPC 20 Text Input: Techniques and Research Tools

  20. Fitts’ Law • Fitts’ law • T Time for pointing task • a,b determined empirically • A distance to target • W width of the target More on Fitts’ law at: http://www.yorku.ca/mack/phd.html W A 21 Text Input: Techniques and Research Tools

  21. Fitts’ Law • Steering Law • TC Time for steering task C • a,b empirically determined constants • W(s) width of the steering tunnel at point s • s trajectory being modeled • Straight tube: • Circle: A W W R More on Steering law: Johnny Accott and Shumin Zhai, Performance evaluation of Input Devices inTrajectory-based Tasks: An Application of The Steering Law, Proceedings of CHI’99, ACM. 22 Text Input: Techniques and Research Tools

  22. Measuring Performance • Measuring speed • What speed? • Walk-up or expert or something in between? • Error free or errors included and corrections included? • Pure writing or in task context? • The users, are they young, old, blind, one-handed? • The list is endless. Measure under conditions that represent actual use or are comparable with other studies. 23 Text Input: Techniques and Research Tools

  23. Measuring Performance • Measuring error rate • What is an error? • A character in wrong position? abba abba abbba abbba • How about corrections and corrections withing corrections? • The best practice: • Compute string distance (levenshtein’s algorithm) • Compute input/character (dependent KSPC) • Edit distance gives the number of errors • KSPC is a measure of the efficiency of the writing method including the effort needed for corrections to achieve the measured error rate. More at: http://www.yorku.ca/mack/CHI01a.htm (CHI2001 Extended Abstracts)http://www.yorku.ca/mack/nordichi2002-shortpaper.html (NordiCHI) 24 Text Input: Techniques and Research Tools

  24. Tradeoffs 25 Text Input: Techniques and Research Tools

  25. More Info • My text input research page:http://www.cs.uta.fi/research/hci/interact/textinput/ • Links to other sites • Bibliography • Papers 26 Text Input: Techniques and Research Tools

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