I have a .csv file with information about a soundtrack and it is divided into beats (per minute). As in: the index corresponds to each beat. I already have tried some different ways to make a spectrogram. Now, I need to divide it into beat-sized chunks to train a deep neural network.

I used the librosa.core.spectrum to create a logarithmic spectrogram out of a .wav file. I have tried looking for tutorials on how to use spectrograms to train DNNs but they already have separated sound files which they then convert into a spectrogram.

I need to take a spectrogram and divide it into chunks the size and duration of a beat (total number of beats = beats per minute multiplied by the length of the song), but I don’t know where to begin looking for guidance on that process.

Unless there’s a different way to relate each beat in the .csv to each segment of the spectrogram? What would you recommend?