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OK, I get it. I’m not sure if that’s a problem because it’s a pretty low-level change, but the issue you are seeing probably relates to something else. Note to anyone finding this thread via search: it isn’t necessary to make any code-level changes to OpenEars to support headphone output; the change discussed here is for duplexing of the mic stream, which is something else. If you are having an issue with headphone output with OpenEars, that is not expected and you should suspect the headphones’ connection or volume level of the device. Public service announcement over :) .
So, the recalibration you are seeing that spins up the CPU happens when there is an utterance that is so long that it requires that the buffer containing the search space has to be resized. Typically this only happens for OpenEars developers in the case that the calibration has gotten confused and the end of an utterance is not successfully being detected, so an extra-long utterance is being searched. Starting with 1.65, this will result in a quick recalibration before getting the hypothesis so that the next utterance is performed with the voice activity detection correctly recalibrated. That is the CPU usage. It means that if the user goes into an environment in which the background noise level is much higher, the voice activity detection won’t get stuck in the “nonstop speech” position.
That it is happening for you suggests that the case in which you are seeing it is a very long uninterrupted utterance with no pauses, something like 30 seconds or so. Is that correct? Is this a test case that you’ve thought of as an extreme condition, or is it a real-world thing that happens under a normal use case?