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Data Augmentation with Python

You're reading from   Data Augmentation with Python Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data

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Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781803246451
Length 394 pages
Edition 1st Edition
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Author (1):
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Duc Haba Duc Haba
Author Profile Icon Duc Haba
Duc Haba
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Data Augmentation
2. Chapter 1: Data Augmentation Made Easy FREE CHAPTER 3. Chapter 2: Biases in Data Augmentation 4. Part 2: Image Augmentation
5. Chapter 3: Image Augmentation for Classification 6. Chapter 4: Image Augmentation for Segmentation 7. Part 3: Text Augmentation
8. Chapter 5: Text Augmentation 9. Chapter 6: Text Augmentation with Machine Learning 10. Part 4: Audio Data Augmentation
11. Chapter 7: Audio Data Augmentation 12. Chapter 8: Audio Data Augmentation with Spectrogram 13. Part 5: Tabular Data Augmentation
14. Chapter 9: Tabular Data Augmentation 15. Index 16. Other Books You May Enjoy

Audio augmentation libraries

There are many commercial and open source audio data augmentation libraries. In this chapter, we will focus on open source libraries available on GitHub. Some libraries are more robust than others, and some focus on a particular subject, such as human speech. Pluto will write wrapper functions using the libraries provided to do the heavy lifting; thus, you can select more than one library in your project. If a library is implemented in the CPU, it may not be suitable for dynamic data augmenting during the ML training cycle because it will slow down the process. Instead, choose a library that can run on the GPU. Choose a robust and easy-to-implement library to learn new audio augmentation techniques or output the augmented data on local or cloud disk space.

The well-known open source libraries for audio augmentation are as follows:

  • Librosa is an open source Python library for music and audio analysis. It was made available in 2015 and has long...
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