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Programming Support for Natural Interaction

Programming Support for Natural Interaction. Jennifer Mankoff CoC & GVU Center Georgia Tech. Acknowledgements. Gregory Abowd & Scott Hudson FCE Group & GVU NSF & IBM. Natural Interaction. Mouse + Keyboard work great for killer apps of the GUI world Problems Arise…

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Programming Support for Natural Interaction

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  1. Programming Support for Natural Interaction Jennifer Mankoff CoC & GVU Center Georgia Tech

  2. Acknowledgements • Gregory Abowd & Scott Hudson • FCE Group & GVU • NSF & IBM

  3. Natural Interaction • Mouse + Keyboard work great for killer apps of the GUI world • Problems Arise… • Off the desktop (Ubiquitous computing) • People with disabilities • My interest: Providing general support for interaction design in this space of problems

  4. Outline of Talk • Output • Augmenting physical objects and spaces • Input • Recognition in the face of errors • Motivation and Design Space • Contribution: Toolkit-level support • Validation: 2 Toolkits, Problem areas • Low bandwidth, ambiguous input

  5. Output: Augmenting physical objects and spaces • PALplates • User study • Exploration • Domisilica • Dual augmentation • General infrastructure

  6. PALplates (CHI’97) (FX-Pal) • Based on study of paper prototype • Point of need • Dynamic UI • Identity • Location

  7. Domisilica • Dual Augmentation • Augment virtual world with information about real world state • Augment real world with virtual services, info (recipes, notes) • General Infrastructure • Example app: Cyberfridge (CVE’98)

  8. Contents: an Instant Jello Pudding:French Vanilla an Instant Jello Pudding:French Vanilla a 16oz Ferrara Capellini-Angel Hair a Hamburger Helper: Beef Noodle ...

  9. Outline of Talk • Output • Augmenting physical objects and spaces • General support for exploring new domains • Input

  10. Input • Recognition • Motivation and Design Space • Contribution: Toolkit-level support • Validation: 2 Toolkits, Problem areas • Low Bandwidth, Ambiguous Input

  11. Recognition • Recognition is becoming ubiquitous • Recognition is difficult to use • A range of interface problems result • OOPS toolkit helps solve them

  12. Research Method • Evaluators • Study individual problems/solutions • Design space of possible solutions • Builders • Facilitate solutions to sets of problems (Architectural / toolkit solutions) • Design space exploration by a larger community

  13. Input • Recognition • Motivation and Design Space • Contribution: Toolkit-level support • Validation: 2 Toolkits, Problem areas • Low Bandwidth, Ambiguous Input

  14. Definitions • Recognizer • interprets user input • creates ambiguity • Error • mistake from user’s perspective • represented with ambiguity • Mediation • dialogue between user and computer • used for resolving ambiguity

  15. SILK (Landay, 1996)

  16. Burlap

  17. Multimodal Suhm (98) McGee et al (98) Handwriting Huerst, Yang & Waibel (98) Speech Ainsworth & Pratt (92) Baber & Hone (93) IUIs Horvitz (99) Many Others… Design Space of Mediation Techniques

  18. Design Space of Mediation Techniques • Two major classes • Repetition • Choice

  19. Design Space of Mediation Techniques • Two major classes • Repetition • Choice

  20. Input • Motivation: Alternatives to Keyboard/Mouse • Recognition • Motivation and Design Space • Contribution: Toolkit-level support • Validation: 2 Toolkits, Problem areas • Low Bandwidth, Ambiguous Input

  21. OOPS Toolkit (CHI’00) • Toolkit-level support for handling ambiguity in recognition • Library of mediators • Architectural support • Based on subArctic

  22. Architectural Support • INDEPENDENT of any specific toolkit • Separation of mediators, recognizers, and application • Communication by a common internal model (ambiguous hierarchical events) • Maintains ambiguity indefinitely

  23. GUI Garnet/interactors (Myers ‘90) X toolkits (Rosenberg et al. ’90) GUI+Recognition SATIN (Hong et al ’00) Extended Amulet (Landay & Myers ’93) PPSM (Hudson&Newell ’92) Artkit (Henry et al. ’90) Context Context Toolkit (Dey et al ’00) PARCPad, etc (Schilit et al. ’94) Multimodal OAA (Cohen et al ’94/Oviatt ’99) PAC-Amodeus (Nigay& Coutaz ’95) Related Work

  24. Three key pieces • Ambiguous hierarchical events • Mediation subsystem • Changes to event dispatch

  25. down down drag drag up up • • • • • • • • • • • • stroke stroke s c Ambiguous Hierarchical Events Myers & Kosbie ‘96 s

  26. Mediation Subsystem • Ambiguity is identified automatically • Presence of multiple interactor nodes • Hierarchy is passed to mediators • Recognizers, recipients informed of accept/reject decisions • Accept/reject modifies hierarchy • Application selects mediators from library

  27. Event Dispatch • Problem: all recipients must support ambiguity • A sensed event arrives • It is dispatched to all recognizers It is mediated rec1 rec2 Input handler event rec3 rec4 recn med2 med1 med4 med3 medn

  28. Modified Event Dispatch 1. A sensed event arrives 2a. It is dispatched to ambiguity unaware components 2b. It is dispatched to all recognizers • It is mediated • Any accepted leaf nodes are dispatched to ambiguity unaware components

  29. s c stroke stroke s c Comparison 1990’s GUI OOPS recogs mediators application application recognizers meds inter interactors Input handler Input handler

  30. Input • Recognition • Motivation and Design Space • Contribution: Toolkit-level support • Validation: 2 Toolkits, Problem areas • Low Bandwidth, Ambiguous Input

  31. Validation • Doing what’s been done • Burlap (complex app) • ~15 Mediators (based on design space) • Architecture: 2 Toolkits • “direct” hookup in GUI world • Context Toolkit extensions (Dey) • Making new things possible: 4 problem areas

  32. Problem Areas (UIST ’00) • Errors & Ambiguity • rejection errors • target ambiguity • Mediation • adding alternatives • occlusion

  33. Problem: There may be multiple targets of a user action Example: clicking Kabbash (95) Worden (97) Target Ambiguity

  34. Problem: There may be multiple targets of a user action Example: Clicking Solution: Give the user a choice of all of the targets Target Ambiguity

  35. Problem: There may be multiple targets of a user action Example: Clicking Solution: Give the user a choice of all of the targets Analysis: Any interface involving mouse press/release Requires separation of concerns Works with all interactors Target Ambiguity

  36. Problem: The correct choice isn’t always present Adding alternatives

  37. Problem: The correct choice isn’t always present Example: word-prediction Adding alternatives

  38. Problem: The correct choice isn’t always present Example: word-prediction Solution: Allow the user to add choices Adding alternatives

  39. Problem: The correct choice isn’t always present Example: word-prediction Solution: Allow the user to add choices Analysis: Closely related choices (e.g. URL prediction) Requires extensible mediators Benefits from recognizer API Adding alternatives

  40. Contributions (Recognition) • Resolution of ambiguity in recognition through mediation • Architectural support (2 toolkits) • Exploration of domain of mediators

  41. Future Work (Recognition) • Testing • Implicit Input (Current) • Intelligent Mediation • “Lazy” alternative generation • Meta-intelligence • General support for varied inputs

  42. Input • Recognition • Motivation and Design Space • Contribution: Toolkit-level support • Validation: 2 Toolkits, Problem areas • Low Bandwidth, Ambiguous Input

  43. Brain-computer interface (Current) • Locked-in Syndrome • Neural Mouse Control

  44. Low-Bandwidth Input • No alternative modalities available • Need for efficient error handling • Challenge: interpret brain signal in as rich a form as possible

  45. Automatic Conversion for Low Bandwidth Input • Web Browser Example: • Automatic URLextraction • Preview Area • Generalization –Next step for natural interaction

  46. Conclusions • Interaction design for ubiquity, disability • Dual augmentation • Ambiguity in recognition • Low bandwidth or error-prone input • Exploration of new interaction techniques • Four mediation problems • Low Bandwidth input • General, re-usable solutions • Domisilica • OOPS toolkit • Extended Context Toolkit

  47. Further Information http://www.cc.gatech.edu/fce/errata/ jmankoff@cc.gatech.edu

  48. What about Alternative Explosion? • Fairly independent, discrete interactions • Some stuff stays in recognizers • Recognition API helps • Only cache ambiguous events • Work to be done…

  49. How general is “general”? • Two Toolkits • Two complex applications • Library of existing mediators • Explorations of 4 problem areas (UIST 00)

  50. Is subArctic doing the work here? • No, our minimal requirements are common in today’s toolkits: • An event-based toolkit • An input-handling module that delivers events to the appropriate places • A library of interactors/widgets • Access to source code (OOPS is not just a library!)

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