Delete README.md

README.md

@@ -1,49 +0,0 @@
----
-task_categories:
-- audio-classification
-size_categories:
-- 100B<n<1T
----
-
-
-# VGGSound
-VGG-Sound is an audio-visual correspondent dataset consisting of short clips of audio sounds, extracted from videos uploaded to YouTube.
-
-
-- **Homepage:** https://www.robots.ox.ac.uk/~vgg/data/vggsound/
-- **Paper:** https://arxiv.org/abs/2004.14368
-- **Github:** https://github.com/hche11/VGGSound
-
-## Analysis
-
-- **310+ classes:** VGG-Sound contains audios spanning a large number of challenging acoustic environments and noise characteristics of real applications.
-- **200,000+ videos:** All videos are captured "in the wild" with audio-visual correspondence in the sense that the sound source is visually evident.
-- **550+ hours:** VGG-Sound consists of both audio and video. Each segment is 10 seconds long.
-
-![](src/data.png)
- 
-
-## Download
-
-We provide a csv file. For each YouTube video, we provide YouTube URLs, time stamps, audio labels and train/test split. Each line in the csv file has columns defined by here.
-
-```
-# YouTube ID, start seconds, label, train/test split. 
-```
-
-And you can download VGGSound directly from this [repository](https://huggingface.co/datasets/Loie/VGGSound/tree/main).
-
-
-## License
-The VGG-Sound dataset is available to download for commercial/research purposes under a Creative Commons Attribution 4.0 International License. The copyright remains with the original owners of the video. A complete version of the license can be found [here](https://thor.robots.ox.ac.uk/datasets/vggsound/license_vggsound.txt).
-
-## Citation
-Please cite the following if you make use of the dataset.
-```
-@InProceedings{Chen20,
-  author       = "Honglie Chen and Weidi Xie and Andrea Vedaldi and Andrew Zisserman",
-  title        = "VGGSound: A Large-scale Audio-Visual Dataset",
-  booktitle    = "International Conference on Acoustics, Speech, and Signal Processing (ICASSP)",
-  year         = "2020",
-}
-```