The Architecture of Why2-Atlas: A Coach for Qualitative Physics Essay Writing
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
CobotDS: a spoken dialogue system for chat
Eighteenth national conference on Artificial intelligence
Towards developing general models of usability with PARADISE
Natural Language Engineering
Quantitative and qualitative evaluation of Darpa Communicator spoken dialogue systems
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Exploiting discourse structure for spoken dialogue performance analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Evidence of Misunderstandings in Tutorial Dialogue and their Impact on Learning
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
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Speech recognition problems are a reality in current spoken dialogue systems. In order to better understand these phenomena, we study dependencies between speech recognition problems and several higher level dialogue factors that define our notion of student state: frustration/anger, certainty and correctness. We apply Chi Square (X2) analysis to a corpus of speech-based computer tutoring dialogues to discover these dependencies both within and across turns. Significant dependencies are combined to produce interesting insights regarding speech recognition problems and to propose new strategies for handling these problems. We also find that tutoring, as a new domain for speech applications, exhibits interesting tradeoffs and new factors to consider for spoken dialogue design.