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Timbre analysis of music audio signals with convolutional neural networks

Timbre analysis of music audio signals with convolutional neural networks

The focus of this work is to study how to efficiently tailor Convolutional Neural Networks (CNNs) towards learning timbre representations from log-mel magnitude spectrograms. We first review the trends when designing CNN architectures. Through this literature overview we discuss which are the crucial points to consider for efficiently learning timbre …