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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

Score transformation with MusicVAE and GrooVAE

In the previous chapters, we've learned to generate various parts of a score. We've generated percussion and monophonic and polyphonic melodies and learned about expressive timing. This section builds on that foundation and shows how to manipulate the generated scores and transform them. In our example, we'll sample two small scores from the latent space, we'll then interpolate between the two samples (progressively going from the first sample to the second sample), and finally, we'll add some groove (or humanization, see the following information box for more information) on the resulting score.

For our example, we'll work on percussion since adding groove in MusicVAE only works on drums. We'll be using different configurations and pre-trained models in MusicVAE to perform the following steps. Remember...

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