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    I work on real-time voice/video AI at Tavus and for the past few years, I’ve mostly focused on how machines respond in a conversation. One thing that’s always bothered me is that almost all conversational systems still reduce everything to transcripts, and throw away a ton of signals that need to be used downstream. Some existing emotion understanding models try to analyze and classify into small sets of arbitrary boxes, but they either aren’t fast / rich enough to do this with conviction in real-time. So I built a multimodal perception system which gives us a way to encode visual…

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