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README.md
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# MDCT-1k
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Over 1000 audio clips from the [Google music captions dataset](https://huggingface.co/datasets/google/MusicCaps) represented as 512x512 time-frequency images.
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The time-frequency images are created from the MDCT coefficients of the 0-12kHz frequency band for 20 second audio clips.
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Operating in the MDCT space does not require a vocoder, nor does it oversample or undersample any range of frequencies.
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More information is provided in the [report](MP3_diffusion.pdf).
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Please see [this notebook showing how to load the dataset and convert from the MDCT images back to audio](load_dataset.ipynb)
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Additionally, [this notebook includes an example of the audio generated by fine tuning on this dataset and shows how to use the inference pipeline](music_inference.ipynb)
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---
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# MDCT-1k
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Over 1000 audio clips from the [Google music captions dataset](https://huggingface.co/datasets/google/MusicCaps) represented as 512x512 time-frequency images. More information is provided in the [report](MP3_diffusion.pdf).
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The time-frequency images are created from the MDCT coefficients of the 0-12kHz frequency band for 20 second audio clips.
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Operating in the MDCT space does not require a vocoder, nor does it oversample or undersample any range of frequencies.
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Please see [this notebook showing how to load the dataset and convert from the MDCT images back to audio](load_dataset.ipynb)
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Additionally, [this notebook includes an example of the audio generated by fine tuning on this dataset and shows how to use the inference pipeline](music_inference.ipynb)
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