Audio Data Augmentation
Similar to image and text augmentation, the objective of audio data augmentation is to extend the dataset to gain a higher accuracy forecast or prediction in a generative AI system. Audio augmentation is cost-effective and is a viable option when acquiring additional audio files is expensive or time-consuming.
Writing about audio augmentation methods poses unique challenges. The first is that audio is not visual like images or text. If the format is audiobooks, web pages, or mobile apps, then we play the sound, but the medium is paper. Thus, we must transform the audio signal into a visual representation. The Waveform graph, also known as the time series graph, is a standard method for representing an audio signal. You can listen to the audio in the accompanying Python Notebook.
In this chapter, you will learn how to write Python code to read an audio file and draw a Waveform graph from scratch. Pluto has provided a preview here so that we can discuss...
