Audio applications

Welcome to the second unit of the Hugging Face audio course! Previously, we explored the fundamentals of audio data and learned how to work with audio datasets using the 🤗 Datasets and 🤗 Transformers libraries. We discussed various concepts such as sampling rate, amplitude, bit depth, waveform, and spectrograms, and saw how to preprocess data to prepare it for a pre-trained model.

At this point you may be eager to learn about the audio tasks that 🤗 Transformers can handle, and you have all the foundational knowledge necessary to dive in! Let’s take a look at some of the mind-blowing audio task examples:

In this unit, you’ll learn how to use pre-trained models for some of these tasks using the pipeline() function from 🤗 Transformers. Specifically, we’ll see how the pre-trained models can be used for audio classification and automatic speech recognition. Let’s get started!