Thesis linked to the implementation of the María de Maeztu Strategic Research Program.

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Back Slizovskaia O, Gómez E, Haro G. A Case Study of Deep-Learned Activations via Hand-Crafted Audio Features. The 2018 Joint Workshop on Machine Learning for Music. Joint workshop program of ICML, IJCAI/ECAI, and AAMAS

Slizovskaia O, Gómez E, Haro G. A Case Study of Deep-Learned Activations via Hand-Crafted Audio Features. The 2018 Joint Workshop on Machine Learning for Music. Joint workshop program of ICML, IJCAI/ECAI, and AAMAS

This work presents a method for analysis of the activations of audio convolutional neural networks by use of hand-crafted audio features. We analyse activations from three CNN architectures trained on different datasets and compare shallow-level activation maps with harmonic-percussive source separation and chromagrams, and deep-level activations with loudness and onset rate

arXiv postprint: https://arxiv.org/abs/1907.01813

https://sites.google.com/site/faimmusic2018/home

Link: https://arxiv.org/abs/1907.01813

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