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

Introducing Magenta.js and TensorFlow.js

In the previous chapters, we've covered Magenta in Python, its usage, and its inner workings. We'll now be looking at Google's Magenta.js, a smaller implementation of Magenta in JavaScript. Magenta and Magenta.js both have their advantages and disadvantages; let's compare them to see which one we should use, depending on the use case.

A Magenta.js application is easy to use and deploy since it executes in the browser. Developing and deploying a web application is easy: all you need is an HTML file and a web server, and your application is available for the whole world to see and use. This is a major advantage of making a browser-based application, since not only does it enable us to create our own music generation application easily, but it also makes it easy to use it collaboratively. See the Further reading section...