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Kymatio: Deep Learning meets Wavelet Theory for Music Signal Processing

Introduction

Tutorial Structure
Tutorial Scope
Why use wavelets in music information retrieval?

Introduction to Wavelets

What is a wavelet?
1D Morlet Wavelets
Wavelet Filterbanks
2D Morlet Wavelets
Notebook 1 - Introduction to Wavelets

Introduction to Scattering

Intro to Wavelet Transforms
Wavelet Filterbanks
First-order Scattering
Wavelet Scalogram
Second-order Scattering
Time-Frequency Scattering
Notebook 2 - Scattering Transforms with Kymatio

Scattering in MIR

Musical Playing Technique Classification with Hybrid Scattering ConvNets
SOL Playing Techniques Dataset
Evaluation
Extensions
Notebook 3 - Musical Playing Technique Classification

GEAR: Generative Evaluation of Audio Representations

GEAR: Generative Evaluation of Audio Representations
AM/FM Chirp Dataset Generation
Generative Evaluation of Audio Representations
Nearest Neighbors Regression of Synth Parameters
Notebook 4 - GEAR: Generative Evaluation of Audio Representations

Differentiable Time-Frequency Analysis

DTFA: Differentiable Time-Frequency Analysis
Differentiable digital signal processing
From the microscale to the mesoscale
Parameter Estimation by Gradient Descent
Notebook 5 - DTFA: Differentiable Time-Frequency Analysis

Resources

References
Acknowledgements
Authors

Repository
Open issue

.md

Notebook 5 - DTFA: Differentiable Time-Frequency Analysis

Contents

Google Colab

Notebook 5 - DTFA: Differentiable Time-Frequency Analysis#

Google Colab #

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Parameter Estimation by Gradient Descent

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References

Contents

Google Colab

By Cyrus Vahidi, Christopher Mitcheltree, Vincent Lostanlen

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