Update README.md

README.md

@@ -12,6 +12,14 @@ dataset_info:
   download_size: 373552088
   dataset_size: 378108023.375
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-# Dataset Card for "audio3600"
+# MDCT-1k
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+Over 1000 audio clips from the [Google music captions dataset](https://huggingface.co/datasets/google/MusicCaps) represented as 512x512 time-frequency images.
+
+The time-frequency images are created from the MDCT coefficients of the 0-12kHz frequency band for 20 second audio clips.
+
+Please see [this notebook showing how to load the dataset and convert from the MDCT images back to audio](load_dataset.ipynb)
+
+Most other audio diffusion models operate in the space of the magnitude spectrogram or mel magnitude spectrogram. Since the phase is discarded, this requires the use of a vocoder for audio generation. When operating in the space of the mel-spectrogram, high frequencies are represented with insufficient time resolution, leading to a noticable loss of quality.
+
+Operating in the MDCT space does not require a vocoder, nor does it oversample or undersample any range of frequencies.