youtube_filtered

# Creative Commons YouTube

## Description
YouTube is a large-scale video-sharing platform where users have the option of uploading content under a CC BY license. To collect high-quality speech-based textual content and combat the rampant license laundering on YouTube, we manually curated a set of over 2,000 YouTube channels that consistently release original openly licensed content containing speech. The resulting collection spans a wide range of genres, including lectures, tutorials, reviews, video essays, speeches, and vlogs. From these channels, we retrieved over 1.1 million openly licensed videos comprising more than 470,000 hours of content. Finally, each video was transcribed to text using the [Whisper speech recognition model](https://github.com/openai/whisper). Code for collecting, processing, and preparing this dataset is available [here](https://github.com/nkandpa2/youtube-commons).

## Dataset Statistics
| Documents | UTF-8 GB |
|-----------|----------|
| 998,104 | 18.6 |

## License Issues
While we aim to produce datasets with completely accurate licensing information, license laundering and inaccurate metadata can cause us to erroneously assign the incorrect license to some documents (for further discussion of this limitation, please see [our paper](https://huggingface.co/papers/2506.05209)). If you believe you have found an instance of incorrect licensing in this dataset, please [start a discussion](https://github.com/r-three/common-pile/discussions/new) on this repository.

## Other Versions
This is the "filtered" version of the Creative Commons YouTube dataset. If you are looking for the raw version, you can find it [here](https://huggingface.co/datasets/common-pile/youtube_raw).

## Citation
If you use this dataset, please cite:
```bibtex
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}
```

# 知识共享（Creative Commons）YouTube数据集

## 数据集描述
YouTube是一款大型视频分享平台，用户可选择采用知识共享署名（CC BY）许可协议上传内容。为收集高质量的语音类文本内容并打击YouTube平台上猖獗的许可盗用行为，我们手动筛选了超过2000个持续发布包含语音内容的开源许可原创内容的YouTube频道。最终收集的内容涵盖多种类型，包括讲座、教程、评测、视频随笔、演讲及视频博客（vlog）。从这些频道中，我们共获取了超过110万个采用开源许可的视频，总时长超过47万小时。最后，我们使用[Whisper语音识别模型（Whisper speech recognition model）](https://github.com/openai/whisper)将所有视频转录为文本。本数据集的收集、处理与制备代码可于[此处](https://github.com/nkandpa2/youtube-commons)获取。

## 数据集统计
| 文本条目数 | UTF-8 存储量（GB） |
|-----------|-------------------|
| 998,104 | 18.6 |

## 许可相关问题
尽管我们致力于生成许可信息完全准确的数据集，但许可盗用与元数据不准确问题可能导致我们错误地为部分文本条目分配了错误的许可协议。（关于此局限性的进一步讨论，请参阅[我们的论文](https://huggingface.co/papers/2506.05209)。）若您发现本数据集中存在许可信息错误的案例，请在本仓库[发起讨论](https://github.com/r-three/common-pile/discussions/new)。

## 其他版本
本数据集为**过滤版**知识共享YouTube数据集。若需获取原始版数据集，可于[此处](https://huggingface.co/datasets/common-pile/youtube_raw)获取。

## 引用说明
若您使用本数据集，请引用以下文献：
bibtex
@article{kandpal2025common,
title={{通用语料库v0.1：一个8TB的公有领域与开源许可文本数据集}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv预印本},
year={2025}
}