Book Image

Hands-On Music Generation with Magenta

By : Alexandre DuBreuil
Book Image

Hands-On Music Generation with Magenta

By: Alexandre DuBreuil

Overview of this book

The importance of machine learning (ML) in art is growing at a rapid pace due to recent advancements in the field, and Magenta is at the forefront of this innovation. With this book, you’ll follow a hands-on approach to using ML models for music generation, learning how to integrate them into an existing music production workflow. Complete with practical examples and explanations of the theoretical background required to understand the underlying technologies, this book is the perfect starting point to begin exploring music generation. The book will help you learn how to use the models in Magenta for generating percussion sequences, monophonic and polyphonic melodies in MIDI, and instrument sounds in raw audio. Through practical examples and in-depth explanations, you’ll understand ML models such as RNNs, VAEs, and GANs. Using this knowledge, you’ll create and train your own models for advanced music generation use cases, along with preparing new datasets. Finally, you’ll get to grips with integrating Magenta with other technologies, such as digital audio workstations (DAWs), and using Magenta.js to distribute music generation apps in the browser. By the end of this book, you'll be well-versed with Magenta and have developed the skills you need to use ML models for music generation in your own style.
Table of Contents (16 chapters)
1
Section 1: Introduction to Artwork Generation
3
Section 2: Music Generation with Machine Learning
8
Section 3: Training, Learning, and Generating a Specific Style
11
Section 4: Making Your Models Interact with Other Applications

Technical requirements

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

  • Command line or Bash to launch Magenta from the terminal
  • Python and Magenta to convert trained models for Magenta.js
  • TensorFlow.js and Magenta.js to create music generation apps in the browser
  • JavaScript, HTML, and CSS to write Magenta.js web applications
  • A recent browser (Chrome, Firefox, Edge, Safari) for up-to-date web APIs
  • Node.js and npm to install Magenta.js and its dependencies server side
  • FluidSynth to listen to generated MIDI from the browser

In Magenta.js, we'll make the use of the Music RNN and MusicVAE models for MIDI sequence generation and GANSynth for audio generation. We'll cover their usage in depth, but if you feel like you need more information, the Magenta.js Music README in the Magenta.js source code (github.com/tensorflow/magenta-js/tree/master/music) is a good place...