five

freesound-laion-640k-commercial-16khz-tiny

收藏
魔搭社区2025-11-27 更新2025-03-22 收录
下载链接:
https://modelscope.cn/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-tiny
下载链接
链接失效反馈
官方服务:
资源简介:
# About this Repository This repository is the training split of [the complete FreeSound LAION 640k dataset](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k), limited only to licenses that permit commercial works, resampled to `16khz` using `torchaudio.transforms.Resample`. This is ideal for use cases where a variety of audio is desired but fidelity and labels are unnecessary, such as background audio for augmenting other datasets. ## Dataset Versions - The [full](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-full) dataset contains **403,146** unique sounds totaling **37.5 GB**. - The [large](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-large) dataset contains **200,000** unique sounds totaling **18.7 GB**. - The [medium](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-medium) dataset contains **100,000** unique sounds totaling **9.29 GB**. - The [small](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-small) dataset contains **50,000** unique sounds totaling **4.64 GB**. - *You are looking at the **tiny** dataset which contains **20,000** unique sounds totaling **1.84 GB**. ## Sampling Method To generate the smaller datasets, the following method was applied: - Using the complete dataset's tag metadata, generate a feature vector for each sample. - Cluster the feature vectors using k-means sampling. - Sample from each cluster in a round-robin fasion until the desired dataset size is reached. ## What about download links? Links were ommitted for the sake of size, as they can be constructed from the data already present. To reconstruct a link, use the following format: `https://freesound.org/people/{username}/sound/{id}` # About this Dataset > LAION-Audio-630K is a large-scale audio-text dataset consisting of 633,526 pairs with the total duration of 4,325.39 hours. It contains audios of human activities, natural sounds and audio effects, consisting of 8 data sources (see the data source table below) from publicly available websites. We collect these datasets by downloading audios and relevant text descriptions. Based on our current knowledge, LAION-Audio-630K is the largest audio-text dataset publicly available and a magnitude larger than previous audio-text datasets (by 2022-11-05). > > [LAION-AI, github.com](https://github.com/LAION-AI/audio-dataset/blob/main/laion-audio-630k/) ## Acknowledgment The whole collection process as well as all usage of the LAION-Audio-630K are conducted by Germany non-profit pure research organization LAION. All contributors and collectors of the dataset are considered as open source contributors affiliated to LAION. These community contributors (Discord ids) include but not limited to: @marianna13#7139, @Chr0my#0173, @PiEquals4#1909, @Yuchen Hui#8574, @Antoniooooo#4758, @IYWO#9072, krishna#1648, @dicknascarsixtynine#3885, and @turian#1607. We would like to appreciate all of them for their efforts on the LAION-Audio-630k dataset. ## License - LAION dataset metadata is released under [The MIT License.](https://mit-license.org/) - Audio is released under one of four licenses: | License | URL | | ------- | --- | | CC0-1.0 | https://creativecommons.org/publicdomain/zero/1.0/ | | CC-BY 4.0 | https://creativecommons.org/licenses/by/4.0/ | | CC-BY 3.0 | https://creativecommons.org/licenses/by/3.0/ | | CC-Sampling+ | https://creativecommons.org/licenses/sampling+/1.0/ | **Please read the entirety of these licenses before deciding if you can use the audio for your project.**

# 本仓库说明 本仓库为[完整FreeSound LAION 640k数据集](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k)的训练子集,仅包含允许商用的授权音频,并已通过`torchaudio.transforms.Resample`重采样至`16kHz`。 本数据集非常适合需要多样化音频但无需高保真度与标注的场景,例如用于扩充其他数据集的背景音频。 ## 数据集版本 - [完整版](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-full)数据集包含**403,146**条独立音频,总容量达**37.5 GB**。 - [大型版](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-large)数据集包含**200,000**条独立音频,总容量达**18.7 GB**。 - [中型版](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-medium)数据集包含**100,000**条独立音频,总容量达**9.29 GB**。 - [小型版](https://huggingface.co/datasets/benjamin-paine/freesound-laion-640k-commercial-16khz-small)数据集包含**50,000**条独立音频,总容量达**4.64 GB**。 - *您当前查看的为**微型版**数据集,包含**20,000**条独立音频,总容量达**1.84 GB**。 ## 采样方法 为生成各小型子集,我们采用如下采样流程: - 基于完整数据集的标签元数据,为每个样本生成特征向量。 - 采用k-means采样对特征向量进行聚类。 - 以轮询方式从每个聚类中采样,直至达到目标数据集规模。 ## 下载链接说明 为控制仓库体积,我们未直接嵌入下载链接,可通过现有数据快速构造链接。构造格式如下: `https://freesound.org/people/{username}/sound/{id}` # 数据集概况 LAION-Audio-630K是一款大规模音频-文本数据集,包含633,526组音频-文本配对,总时长达4,325.39小时。数据集涵盖人类活动音频、自然音效与音频特效,包含8个公开网站来源的数据(详见下文数据源表格)。我们通过下载音频及相关文本描述完成数据集采集。据我们目前所知,截至2022年11月5日,LAION-Audio-630K是公开可用的规模最大的音频-文本数据集,其体量较此前的同类数据集提升了一个数量级。 [LAION-AI, github.com](https://github.com/LAION-AI/audio-dataset/blob/main/laion-audio-630k/) ## 致谢 LAION-Audio-630K的全部采集流程与使用均由德国非营利纯研究机构LAION主导。所有数据集贡献者与采集者均视为隶属于LAION的开源贡献者。社区贡献者(Discord账号)包括但不限于:@marianna13#7139、@Chr0my#0173、@PiEquals4#1909、@Yuchen Hui#8574、@Antoniooooo#4758、@IYWO#9072、krishna#1648、@dicknascarsixtynine#3885以及@turian#1607。我们谨向所有为LAION-Audio-630K数据集付出努力的人员致以诚挚谢意。 ## 授权协议 - LAION数据集元数据采用[MIT开源协议](https://mit-license.org/)发布。 - 音频文件采用以下四种协议之一发布: | 授权协议 | 协议链接 | | ------- | --- | | CC0-1.0(Creative Commons Zero 1.0) | https://creativecommons.org/publicdomain/zero/1.0/ | | CC-BY 4.0(Creative Commons Attribution 4.0) | https://creativecommons.org/licenses/by/4.0/ | | CC-BY 3.0(Creative Commons Attribution 3.0) | https://creativecommons.org/licenses/by/3.0/ | | CC-Sampling+(Creative Commons Sampling Plus 1.0) | https://creativecommons.org/licenses/sampling+/1.0/ | **请务必完整阅读所有相关授权协议后,再决定是否将音频用于您的项目。**
提供机构:
maas
创建时间:
2025-03-18
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作