How to Classify Audio Chords with a Convolutional Neural Network 🎹🎵

In this video, I will show you how to use a convolutional neural network (CNN) to classify audio chords.

I will start by examining a few audio files and playing them back. Then, I will code a transform process to convert the audio files to spectrogram images. Spectrogram images are visual representations of sound waves. They can be used to identify different frequencies and amplitudes, which can be used to classify chords.

Next, I will write a CNN model to generate a binary classification between major and minor chords. I will train the model on a dataset of spectrogram images that have been labeled with the correct chord. The model will learn to identify the features of each chord and to classify them accordingly.

Finally, I will test the model on a new set of spectrogram images that have not been labeled. The model will predict the chord for each image and you can compare its predictions to the ground truth labels.

This video is for anyone who is interested in learning how to use deep learning to classify audio chords. It is also a good resource for music producers who want to use machine learning to improve their music.

I hope you enjoy the video!

Code for this video here : https://ko-fi.com/s/585fb97174

More relevant content in this playlist : https://youtube.com/playlist?list=PLdkryDe59y4Ze9_12JhWu3cs-lOGYwYeD

A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V 
I also recommend this book for deep dive in deep learning : https://amzn.to/3TTZym7
~~~~~~~~~~~~~~~ Chapters  ~~~~~~~~~~~~~~~ 

00:00 Intro
00:38 Let's start coding - Get the dataset
16:19 Build the CNN model
27:20 Test the CNN model with a new fresh image

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Music by Vincent Rubinetti 
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