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Evolution of Text Input Techniques in Communication Technology

This collage of historical notes delves into the evolution of text input methods, keyboards, recognition systems, and pointing techniques. Explore how cultural needs, technological advancements, and individual preferences have shaped text input systems.

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Evolution of Text Input Techniques in Communication Technology

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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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