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How to Improve the Quality of Audio in Computer Vision?
Audio is basically a composition of amplitude information and face information. Amplitude meaning how high are the peaks of the sign waves and face information, meaning edoes the sign wave start, how much does it shift atright? And then we can add up, potentially infinitely many sign waves. And this is the audio signal that you can hear, essentially a fore decomposition. The l tulos optimizes the amplitudes aggressively in the beginning of the training process of ha nearer network, but completely neglects the face information.