Attention, intentions, and the structure of discourse
Computational Linguistics
Training Personal Robots Using Natural Language Instruction
IEEE Intelligent Systems
Elvis: situated speech and gesture understanding for a robotic chandelier
Proceedings of the 6th international conference on Multimodal interfaces
Distributing representation for robust interpretation of dialogue utterances
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Probabilistic grounding of situated speech using plan recognition and reference resolution
ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
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ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
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IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Robust spoken instruction understanding for HRI
Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction
Towards mediating shared perceptual basis in situated dialogue
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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This paper presents a speech understanding component for enabling robust situated human-robot communication. The aim is to gain semantic interpretations of utterances that serve as a basis for multi-modal dialog management also in cases where the recognized word-stream is not grammatically correct. For the understanding process, we designed semantic processable units, which are adapted to the domain of situated communication. Our framework supports the specific characteristics of spontaneous speech used in combination with gestures in a real world scenario. It also provides information about the dialog acts. Finally, we present a processing mechanism using these concept structures to generate the most likely semantic interpretation of the utterances and to evaluate the interpretation with respect to semantic coherence.