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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 3: Generating Polyphonic Melodies

  1. Vanishing gradients (values get multiplied by small values in each RNN step) and exploding gradients are common RNN problems that occur when training during the backpropagation step. LSTM provides a dedicated cell state that is modified by forget, input, and output gates to alleviate those problems.

  2. Gated recurrent units (GRUs) are simpler but less expressive memory cells, where the forget and input gates are combined into a single update gate.

  3. For a 3/4 time signature, you need 3 steps per quarter note, times 4 steps per quarter note, which equals 12 steps per bar. For a binary step counter to count to 12, you need 5 bits (like for 4/4 time) that will only count to 12. For 3 lookbacks, you'll need to look at the past 3 bars, with each bar being 12 steps, so you have [36, 24, 12].
  4. The resulting vector is the sum of the previous...
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