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A framework for multimodal data collection, visualization, annotation and learning

The development and iterative refinement of inference models for multimodal systems can be challenging and time intensive. We present a framework for multimodal data collection, visualization, annotation, and learning that enables system developers to build models using various machine learning techniques, and quickly iterate through cycles of development, deployment and refinement.