Computer Science and Engineering

Robust Multimodal Interpretation in Conversation Systems

2/1/2004 - 2010
Supported by National Science Foundation (Career Award)

Multimodal systems allow users to interact with computers through multiple modalities such as speech, gesture, and gaze. These systems are designed to support transparent, efficient, and natural means of human computer interaction. Understanding what the user intends to communicate is one of the most significant challenges for multimodal systems. Despite recent progress in multimodal interpretation, when unexpected inputs (e.g., inputs that are outside of system knowledge) or unreliable inputs (e.g., inputs that are not correctly recognized) are encountered, these systems tend to fail. Variations in vocabulary and multimodal synchronization patterns, disfluencies in speech utterances, and ambiguities in gestures can seriously impair interpretation performance. This project seeks to improve the robustness of multimodal interpretation by adapting system interpretation capability over time through automated knowledge acquisition and optimizing interpretation through probabilistic reasoning. Supported by NSF.
(Picture: Ph.D. student Zahar Prasov interacts with a system using speech and gesture)

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