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- W2965445708 abstract "In collaborative tasks, people rely both on verbal and non-verbal cues simultaneously to communicate with each other. For human-robot interaction to run smoothly and naturally, a robot should be equipped with the ability to robustly disambiguate referring expressions. In this work, we propose a model that can disambiguate multimodal fetching requests using modalities such as head movements, hand gestures, and speech. We analysed the acquired data from mixed reality experiments and formulated a hypothesis that modelling temporal dependencies of events in these three modalities increases the model’s predictive power. We evaluated our model on a Bayesian framework to interpret referring expressions with and without exploiting the temporal prior." @default.
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- W2965445708 date "2019-01-01" @default.
- W2965445708 modified "2023-10-18" @default.
- W2965445708 title "Exploring Temporal Dependencies in Multimodal Referring Expressions with Mixed Reality" @default.
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- W2965445708 doi "https://doi.org/10.1007/978-3-030-21565-1_8" @default.
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