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There could be a number of approaches for this task, depending on the number of channels (microphones) in your input and structure of available data. Given a labeled data set from a previously known set of rooms, you can train a neural network (NN) to classify in which one of them a new sample was recorded. A second approach would be to estimate the ...


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One problem with an acoustic link is frequency dependent multi-path fading/reinforcement, which can vary widely as the source and mic positions change, or as the room acoustic vary (moving hard objects, etc.) So I might try a "click" that has a wide and known pattern of several non-harmonically related spectra, and check the Hamming distance between the ...


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Discretize Amplitude or Time – that is the (signal processing question) Seeing that you're using a microcontroller running at at leas 8 MHz (probably 16 MHz): It's way easier to measure the time a signal was high than to first average out the PWM cycle in analog domain and then convert that analog voltage to digital. If this was a sigma-delta ADC, which ...


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