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This paper proposes a method for incrementally understanding user utterances whose semantic boundaries are not known and responding in real time even before boundaries are determined. It is an integrated parsing and discourse processing method that updates the partial result of understanding word by word, enabling responses based on the partial result. This(More)
This paper concerns the discourse understanding process in spoken dialogue systems. This process enables the system to understand user utterances based on the context of a dialogue. Since multiple candidates for the understanding result can be obtained for a user utterance due to the ambiguity of speech understanding, it is not appropriate to decide on a(More)
This paper proposes a robot that acquires multimodal information, i.e. auditory, visual, and haptic information, fully autonomous way using its embodiment. We also propose an online algorithm of multimodal categorization based on the acquired multimodal information and words, which are partially given by human users. The proposed framework makes it possible(More)
When designing a spoken dialogue system, in particular a real-time one, not only what the system responds but also when it responds need to be considered. This paper focuses on when the system should appropriately respond with backchannels, and reports an experiment that compared two response-time conditions: the immediate response and the orderly response.(More)
This paper describes new feature parameters for detecting misunderstandings in a spoken dialogue system. Although recognition errors cannot be completely avoided with current speech recognition techniques, a spoken dialogue system could be a good human-machine interface if it could automatically detect and recover from its own misunderstandings during(More)
In spoken communications, correction utterances , which are utterances correcting other participants utterances and behaviors , play crucial roles, and detecting them is one of the key issues. Previously , much work has been done on automatic detection of correction utterances in human-human and human-computer dialogs , but they mostly dealt with the(More)
This paper proposes a probabilistic approach to the resolution of referring expressions for task-oriented dialogue systems. The approach resolves descriptions, anaphora, and deixis in a unified manner. In this approach, the notion of reference domains serves an important role to handle context-dependent attributes of entities and references to sets. The(More)
Ideally, the users of spoken dialogue systems should be able to speak at their own tempo. The systems thus need to correctly interpret utterances from various users, even when these utterances contain disflu-ency. In response to this issue, we propose an approach based on a posteriori restoration for incorrectly segmented utterances. A crucial part of this(More)
This paper presents a robot audition system that recognizes simultaneous speech in the real world by using robot-embedded microphones. We have previously reported missing feature theory (MFT) based integration of sound source separation (SSS) and automatic speech recognition (ASR) for building robust robot audition. We demonstrated that a MFT-based(More)