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Hands-On Music Generation with Magenta

You're reading from   Hands-On Music Generation with Magenta Explore the role of deep learning in music generation and assisted music composition

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Product type Paperback
Published in Jan 2020
Publisher
ISBN-13 9781838824419
Length 360 pages
Edition 1st Edition
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Author (1):
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Alexandre DuBreuil Alexandre DuBreuil
Author Profile Icon Alexandre DuBreuil
Alexandre DuBreuil
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction to Artwork Generation
2. Introduction to Magenta and Generative Art FREE CHAPTER 3. Section 2: Music Generation with Machine Learning
4. Generating Drum Sequences with the Drums RNN 5. Generating Polyphonic Melodies 6. Latent Space Interpolation with MusicVAE 7. Audio Generation with NSynth and GANSynth 8. Section 3: Training, Learning, and Generating a Specific Style
9. Data Preparation for Training 10. Training Magenta Models 11. Section 4: Making Your Models Interact with Other Applications
12. Magenta in the Browser with Magenta.js 13. Making Magenta Interact with Music Applications 14. Assessments 15. Other Books You May Enjoy

Technical requirements

In this chapter, we'll use the following tools:

  • The command line or Bash to launch Magenta from the Terminal
  • Python and its libraries to write music generation code using Magenta
  • Magenta to generate audio clips
  • Audacity to edit audio clips
  • Any media player to listen to the generated WAV files

In Magenta, we'll make the use of the NSynth and GANSynth models. We'll be explaining these models in depth, but if you feel like you need more information, the models' README in Magenta's source code (github.com/tensorflow/magenta/tree/master/magenta/models) is a good place to start. You can also take a look at Magenta's code, which is well documented. We also provide additional content in the Further reading section.

The code for this chapter is in this book's GitHub repository in the Chapter05 folder, located at github.com/PacktPublishing...

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