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TiltText : Using Tilt for Text Input to Mobile Phones

TiltText : Using Tilt for Text Input to Mobile Phones. Daniel Wigdor & Ravin Balakrishnan. Text Messaging. Estimated 500,000,000,000 text messages in 2003 worldwide More popular outside North America. Ambiguity. Pressing “2” : {2,a,b,c,A,B,C}. Solutions. MultiTap

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TiltText : Using Tilt for Text Input to Mobile Phones

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  1. TiltText: Using Tilt for Text Input to Mobile Phones Daniel Wigdor & Ravin Balakrishnan

  2. Text Messaging • Estimated 500,000,000,000 text messages in 2003 worldwide • More popular outside North America

  3. Ambiguity • Pressing “2” : {2,a,b,c,A,B,C}

  4. Solutions • MultiTap • Language-based disambiguation • T9 • Letterwise • Wordwise • Alternate Layouts:

  5. MultiTap: ~2.1 KSPC e.g.: {6,6,6,>,6,6} = “on”

  6. e.g.: {6,6} = “on”, “no”, “mo”,… T9: ~1.2 KSPC

  7. T9: Problems • Ambiguity persists • Inconsistent • Eyes-free operation impossible • Only English-Like text • No numerals • Real “texting” impossible(“b4”,”btw”,”lol”,”rotflmao”…)

  8. What’s best? • Low KSPC • Eyes-free • Non-language specific

  9. Tilt as input • Add a tilt sensor to device • inexpensive accelerometers • Hinckley et al.UIST’00 • Tilt for text input: • Sazawal et al. Unigesture MobileHCI ‘02 • Partridge et al. TiltType UIST’02 • No formal evaluations

  10. TiltText: 1 KSPC + Tilt Action Q eg: {7} = … P R S

  11. Tilt Detection: Key Tilt • Difference between press & release • Slow: 3 consecutive actions • keypress, tilt, key-release • Pilot study: poor performance

  12. Tilt Detection: Absolute • Relative to a fixed origin • Keypress & tilt actions concurrent • Consecutive same-tilt: savings • Consecutive opposite-tilt: extra cost • High error-rate: “creeping posture”

  13. Tilt Detection: Relative • Most recent tilting gesture • floating origin • Maintains advantages of Absolute tilt • Saves work on consecutive same tilts & consecutive opposite tilts • No “creeping posture”

  14. Our Prototype • Uses Absolute tilt • Tilts from board via serial port

  15. The Study • Repeated-measures design 10 participants 2 techniques (MultiTap & TiltText) 16 blocks of 20 phrases each in 2 sessions • Same phrases for both techniques • Technique order between participant • Measured time & accuracy • Participants told to correct mistakes

  16. Results: Overall Speed • Overall, TiltText 16% faster (including error correction) WPM Block

  17. Power-law extrapolation WPM Block

  18. Results: Between Participant • Data from 1st technique seen by each participant • TiltText still faster WPM Block

  19. Results: Error Rate • TiltText error rate higher than MultiTap Error Rate Percentage Block

  20. Error Rate: By Letter • Error rates much higher for some letters Error Rate Percentage Correct Letter

  21. Error Rate: Tilt Direction • Direction significantly effects error rate • Creeping posture Error Rate Percentage Correct Tilt Direction

  22. Conclusions • Implemented TiltText • Three distinct approaches for tilt • Formal study conducted • TiltText faster despite errors

  23. Future Work • Theoretical TiltText speed • KSPC is not the whole story • Implement relative-tilt system • Deeper analysis of error causes • Longer study • Optimizing letter/key assignments

  24. Acknowledgements • Michael McGuffin • Richard Watson • DGP Lab members • Study participants • Microsoft Research

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