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We present a framework that couples computer algorithms with human intelligence in order to automatically sense and interpret nonverbal behavior. The framework is cloud-enabled and ubiquitously available via a web browser, and has been validated in the context of public speaking. The system automatically captures audio and video data in-browser through the(More)
We present a framework to identify whether a public speaker’s body movements are meaningful or non-meaningful (“Mannerisms”) in the context of their speeches. In a dataset of 84 public speaking videos from 28 individuals, we extract 314 unique body movement patterns (e.g. pacing, gesturing, shifting body weights, etc.). Online workers and the speakers(More)
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