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electronic visualization laboratory, university of illinois a Towards Lifelike Interfaces That Learn Jason Leigh, Andrew Johnson, Luc Renambot, Steve Jones, Maxine Brown

Towards Lifelike Interfaces That Learn

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Towards Lifelike Interfaces That Learn. Jason Leigh, Andrew Johnson, Luc Renambot, Steve Jones, Maxine Brown. The Electronic Visualization Laboratory. Established in 1973 Jason Leigh, Director; Tom DeFanti, Co-Director; Dan Sandin, Director Emeritus 10 full time staff - PowerPoint PPT Presentation

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Page 1: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

Towards Lifelike Interfaces That Learn

Jason Leigh, Andrew Johnson, Luc Renambot, Steve Jones,

Maxine Brown

Page 2: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

The Electronic Visualization Laboratory

• Established in 1973• Jason Leigh, Director; Tom DeFanti, Co-

Director; Dan Sandin, Director Emeritus• 10 full time staff• Interdisciplinary Computer Science, Art &

Communication• 30 students, 15 funded students,• Research in:

– Advanced display systems– Visualization and virtual reality– High speed networking– Collaboration & human computer interaction

• 34 years of collaboration with Science, Industry & Arts to apply new computer science techniques to these disciplines.

• Major support by NSF and ONR.

Page 3: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

Goal in 3 Years

• Life-sized Avatar capable of reacting to speech input with naturalistic facial and gestural responses.

• A methodology of how to capture and translate human verbal and non-verbal communication into an interactive digital representation.

• Deeper understanding of how to create believable/credible avatars.

Page 4: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

System Components

AlexDSSSpeech Recognition

Natural Language Processing

ResponsiveAvatar

Facial Expression Recognition Responsive

Avatar EngineEye-tracking

Speech SynthesisLip SynchGestural ArticulationFacial Articulation

Knowledge

Processing

Facial & Body Motion / Performance Capture

Phonetic Speech Sampling

Knowledge Capture

Textual & Contextual Information

Page 5: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

EVL Year 1

• Digitize facial images and audio of Alex• Shadow Alex to capture information

about his mannerisms• Create 3D Alex focusing largely on

facial features• Prototype initial RAE & merge initial

avatar, speech recognition, AlexDSS, pre-recorded voices

• Validate provision of non-verbal avatar cues, evaluate efficacy of cues

Page 6: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

EVL Year 2

• Full-scale Motion & performance capture to create gestural responses to AlexDSS

• Speech synthesis using Alex’s voice patterns to create verbal responses to AlexDSS

• Use eye-tracking to begin to experiment with aspects of non-verbal communication

• Evaluate merging of verbal and non-verbal information in users’ understandings of– avatar believability and credibility

(ethos)– information retrieved– avatar emotional appeals (pathos)

Page 7: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

EVL Year 3

• Utilize camera-based recognition of facial expressions as additional non-verbal input

• Conduct user studies:– relative to a believability and

credibility (ethos)– to correlate attention to non-

verbal communication relative to comprehension and retention

– to assess value of avatar emotional appeals (pathos)

– to address formation of longer-term relationship formation between avatar and user.

CameraMicrophone

Life-sized projection

Page 8: Towards Lifelike Interfaces That Learn

electronic visualization laboratory, university of illinois at chicago

Thanks!

• This project was supported by grants from the National Science Foundation

• Award CNS 0703916 and CNS 0420477