image
imagewidth (px)
256
256
audio_file
stringlengths
19
22
slice
int16
0
0
./-gunr91dUe8_10.mp3
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./hz0zGSZu6GQ_57.mp3
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./0bLxAtJqpLQ_55.mp3
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./sCjpbjCH5L0_17.mp3
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./eYVaV9ujHdE_0.mp3
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./Ccs2rt0oSzQ_20.mp3
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./JgpPk4ooo7E_0.mp3
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./PEt8BJyez0g_56.mp3
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./QbzkwLWK-Ps_140.mp3
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./iclcv3-_L-w_0.mp3
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./VE8ENpivjsw_461.mp3
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./A9Ik81plN_Q_12.mp3
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./ZOk9F5LLabo_143.mp3
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./1ddC4OCYEcc_200.mp3
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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
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Models trained or fine-tuned on teticio/audio-diffusion-breaks-256