Deep learning speaker compensation
Abstract:
A recurrent neural network is employed in a loudspeaker system to compensate the distortion of the system based upon a source signal (content) and the sensing output of a sensing circuit (context). A frequency domain transform is selected to provide mapping between the source signal and a recorded signal; and enable reconstruction of desirable playback. Various sensing-related features and source-related features are derived to serve as the auxiliary information. A desirable content is therefore generated based upon the original content and the context.
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