In this tutorial, we start by introducing techniques for extracting audio features from music data. We then show how to implement a music genre classifier from scratch in TensorFlow/Keras using those features calculated by the Librosa library.
In this article, we explore the progress that deep learning has made in the field of music in numerous tasks related to audio and signal processing. We then proceed to model and generate our own music files using pretty_midi.
This tutorial will guide you through auditory classification using a Jupyter notebook and TensorFlow. It covers essential concepts of signal processing and the best techniques for achieving accurate audio classification.
In the second part of a series on audio analysis and processing, we'll look at notes, harmonics, octaves, chroma representation, onset detection methods, beat, tempo, tempograms, spectrogram decomposition, and more!
