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E-raamat: Build AI-Enhanced Audio Plugins with C++

  • Formaat: 362 pages
  • Ilmumisaeg: 21-Jun-2024
  • Kirjastus: Focal Press
  • Keel: eng
  • ISBN-13: 9781040047200
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Build AI-Enhanced Audio Plugins with C++Suurem pilt
  • Formaat: 362 pages
  • Ilmumisaeg: 21-Jun-2024
  • Kirjastus: Focal Press
  • Keel: eng
  • ISBN-13: 9781040047200
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Build AI-Enhanced Audio Plugins with C++ explains how to embed artificial intelligence technology inside tools that can be used by audio and music professionals, through worked examples using Python, C++ and audio plug-in APIs which demonstrate how to combine technologies to produce professional, AI-enhanced creative tools.



Build AI-Enhanced Audio Plugins with C++ explains how to embed artificial intelligence technology inside tools that can be used by audio and music professionals, through worked examples using Python, C++ and audio APIs which demonstrate how to combine technologies to produce professional, AI-enhanced creative tools.

Alongside a freely accessible source code repository created by the author that accompanies the book for readers to reference, each chapter is supported by complete example applications and projects, including an autonomous music improviser, a neural network-based synthesizer meta-programmer and a neural audio effects processor. Detailed instructions on how to build each example are also provided, including source code extracts, diagrams and background theory.

This is an essential guide for software developers and programmers of all levels looking to integrate AI into their systems, as well as educators and students of audio programming, machine learning and software development.

Arvustused

"This book is long overdue. With the explosion of activity in the field of AI-assisted music creation, the need for mastering all the chain of software from ideas to actual plugins is stronger than ever. Matthew has a direct, hands-on approach that not only will be of great help to people wanting to contribute to the field, but will also encourage others to experiment and share their code. Matthew's experience in teaching shows and definitely contributes to making the book easy to read and to-the-point."

François Pachet, Research Director

Part 1: Getting started
1. Introduction to the book
2. Setting up your
development environment
3. Installing JUCE
4. Installing and using CMake
5.
Set up libtorch
6. Python setup instructions
7. Common development
environment setup problems
8. Basic plugin development
9. FM synthesizer
plugin Part 2: ML-powered plugin control: the meta-controller
10. Using
regression for synthesizer control
11. Experiment with regression and
libtorch
12. The meta-controller
13. Linear interpolating Superknob
14.
Untrained Torchknob
15. Training the torchknob
16. Plugin meta-controller
17.
Placing plugins in an AudioProcessGraph structure
18. Show a plugins user
interface
19. From plugin host to meta-controller Part 3: The autonomous
music improviser
20. Background: all about sequencers
21. Programming with
Markov models
22. Starting the Improviser plugin
23. Modelling note onset
times
24. Modelling note duration
25. Polyphonic Markov model Part 4: Neural
audio effects
26. Welcome to neural effects
27. Finite Impulse Responses,
signals and systems
28. Convolution
29. Infinite Impulse Response filters
30.
Waveshapers
31. Introduction to neural guitar amplifier emulation
32. Neural
FX: LSTM network
33. JUCE LSTM plugin
34. Training the amp emulator: dataset
35. Data shapes, LSTM models and loss functions
36. The LSTM training loop
37. Operationalising the model in a plugin
38. Faster LSTM using RTNeural
39.
Guide to the projects in the repository
Matthew John Yee-King is a professor in the department of computing at Goldsmiths, University of London. He is an experienced educator as well as the programme director for the University of London's online BSc Computer Science degree.
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