[Feature] Although machines are getting better at understanding audio signals, the tasks that are being undertaken are still relatively basic. Identifying a solo on a particular instrument, working out who is talking, working out when someone is singing, and so forth—these are tasks we mostly do relatively easily as humans. Coming up with an algorithm that enables a machine to do it reliably is surprisingly challenging. Selected papers from the recent conference on semantic audio are summarized.
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