Part 1 Lesson 1 - Classifying music genres


I am trying my hand at practicing the exercises in Lesson 1. To do this, I picked up the task of classifying music genres. I wanted to try 2 approaches:

  1. Can the model look at sheet music notation and identify what genre the song belongs to?
  2. Can the model look at the audio spectrogram and identify what genre the song belongs to?

For approach 1)
Training set size: 600 images/genre
I downloaded some well labeled guitar sheet music belonging to the genres such as ‘rock’, ‘pop’, ‘classical’, ‘blues’, ‘jazz’. This approach gave me an accuracy of 35% using restnet34. This was after adjusting the learning rate.
I used about 600 sheet music examples per genre

For approach 2)
Training set size: 25 images/genre
I created spectrograms for songs using a tool called spek. After creating and labelling the spectrograms, I passed it through the model and got a dismal 20% accuracy.

I am curious to know if there is a better approach to solving this classification problem.

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