Datasets:

teticio
/

audio-diffusion-breaks-256

image imagewidth (px) 256 256	audio_file stringlengths 19 22	slice int16 0 0
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	./hz0zGSZu6GQ_57.mp3	0
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	./KCgYPlOuvgM_1.mp3	0
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	./owUgop9PJ9s_10.mp3	0
	./umUHR1JlT_c_107.mp3	0
	./ZyswjkZJugI_10.mp3	0
	./A3UlqskQCOs_42.mp3	0
	./N3zUBUqAOQ8_40.mp3	0
	./eJO5HU_7_1w_3.mp3	0
	./MBdVXkSdhwU_15.mp3	0
	./EIYymBQ05S8_1.mp3	0
	./1ddC4OCYEcc_200.mp3	0
	./rceRAelUtzA_0.mp3	0
	./dh7N-7Hv2so_5.mp3	0

End of preview. Expand in Dataset Viewer.

30,000 256x256 mel spectrograms of 5 second samples that have been used in music, sourced from WhoSampled and YouTube. The code to convert from audio to spectrogram and vice versa can be found in https://github.com/teticio/audio-diffusion along with scripts to train and run inference using De-noising Diffusion Probabilistic Models.

x_res = 256
y_res = 256
sample_rate = 22050
n_fft = 2048
hop_length = 512

Downloads last month: 65

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Size of downloaded dataset files:

1.3 GB

Size of the auto-converted Parquet files:

1.3 GB

Number of rows:

29,825

Models trained or fine-tuned on teticio/audio-diffusion-breaks-256

teticio/audio-diffusion-breaks-256

Updated Jan 25 • 12 • 4