A Comparison on Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging
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Deep neural networks (DNN) have been successfully applied for music classification tasks including music tagging. In this paper, we investigate the effect of audio preprocessing on music tagging with neural networks. We perform comprehensive experiments involving audio preprocessing using different time-frequency representations, logarithmic magnitude compression, frequency weighting and scaling. We show that many commonly used input preprocessing techniques are redundant except magnitude compression.
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