Open Mind Common Sense: Knowledge Acquisition from the General Public
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluation of Justina: A Virtual Patient with PTSD
IVA '08 Proceedings of the 8th international conference on Intelligent Virtual Agents
Acquiring correct knowledge for natural language generation
Journal of Artificial Intelligence Research
Building effective question answering characters
SigDIAL '06 Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue
Using virtual humans to bootstrap the creation of other virtual humans
IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
High score!: motivation strategies for user participation in virtual human development
IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
Constructionism of virtual humans to improve perceptions of conversational partners
CHI '12 Extended Abstracts on Human Factors in Computing Systems
IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
Using critical-cue inventories to advance virtual patient technologies in psychological assessment
Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration
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Currently, applications that focus on providing conversations with virtual humans require extensive work to create robust conversational models. We present a new approach called Human-centered Distributed Conversational Modeling. Using this approach, users create conversational models in a distributed manner. To do this, end-users interact with virtual humans to provide new stimuli (questions and statements), and domain-specific experts (e.g. medical/psychology educators) provide new virtual human responses. Using this process, users become the primary developers of conversational models. We tested our approach by creating an example application, Virtual People Factory. Using Virtual People Factory, a pharmacy instructor and 186 pharmacy students were able to create a robust conversational model in 15 hours. This is approximately 10% of the time typical in current approaches and results in more comprehensive coverage of the conversational space. In addition, surveys demonstrate the acceptability of this approach by both educators and students.