Hastie, Helen

Katsakioris, Miltiadis

Konstas, Ioannis

Laskov, Atanas

English

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Corpus of Multimodal Interaction for Collaborative Planning

As autonomous systems become more commonplace, we need a way to easily and naturally communicate to them our goals and collaboratively come up with a plan on how to achieve these goals. To this end, we conducted a Wizard of Oz study to gather data and investigate the way operators would collaboratively make plans via a conversational `planning assistant' for remote autonomous systems. We present here a corpus of 22 dialogs from expert operators, which can be used to train such a system. Data analysis shows that multimodality is key to successful interaction, measured both quantitatively and qualitatively via user feedback

Edinburgh Research Explorer

As autonomous systems become more commonplace, we need a way to easily and naturally communicate to them our goals and collaboratively come up with a plan on how to achieve these goals. To this end, we conducted a Wizard of Oz study to gather data and investigate the way operators would collaboratively make plans via a conversational {`}planning assistant{'} for remote autonomous systems. We present here a corpus of 22 dialogs from expert operators, which can be used to train such a system. Data analysis shows that multimodality is key to successful interaction, measured both quantitatively and qualitatively via user feedback

Heriot Watt Pure

https://pureapps2.hw.ac.uk/ws/files/25278493/W19_1601.pdf

Corpus of Multimodal Interaction for Collaborative Planning

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Edinburgh Research Explorer

Heriot Watt Pure

Heriot Watt Pure