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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

Chapter 9: Making Magenta Interact with Music Applications

  1. A DAW will have more functions geared towards music production such as recording, audio, MIDI editing, effects and mastering, and song composition. A software synthesizer like FluidSynth will have less functionalities, but have the advantage of being lightweight and easy to use.

  2. Most music software won't open MIDI ports by themselves, so to send sequences back and forth between them we have to manually open ports.
  3. See the code in chapter_09_example_05.py in this chapter's code.
  4. Because syncing two pieces of software that have desynced requires restarting them. A MIDI clock enables syncing once per beat.
  5. Because Magenta Studio integrates with existing music production tools such as DAWs and doesn't require any technical knowledge, it makes AI-generated music available to a greater audience, which is ultimately...

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