We designed an augmented reality interface for dialog that enables the control of multimodal behaviors in telepresence robot applications.
This paper introduces an embodied agent that self-authors its own dialog for social chat.
To our best knowledge, this is the first large-scale study for automatic evaluation of narrative quality.
We study a mini-batch diversification scheme for stochastic gradient descent (SGD).
We present a probabilistic language model for time-stamped text data which tracks the semantic evolution of individual words over time.
We propose a joint approach that simultaneously learns a latent coordination model along with the individual policies.
We introduce a simple and effective deep learning approach to automatically generate natural looking speech animation that synchronizes to input speech.
We introduce a deep learning approach for denoising Monte Carlo-rendered images that produces high-quality results suitable for production.
In this paper, we envision a robot that collaborates with a child to create oral stories in a highly interactive manner.
We performed three studies to examine the effects of accurate program response times, repeating unanswered questions, and providing feedback on the children’s likelihood of response.
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