license: mit
size_categories:
- 100K<n<1M
task_categories:
- audio-to-audio
- audio-classification
- text-to-audio
dataset_info:
features:
- name: url
dtype: string
- name: title
dtype: string
- name: author
dtype: string
- name: description
dtype: string
- name: genre
dtype: float64
- name: album
dtype: float64
- name: tags
dtype: string
splits:
- name: train
num_bytes: 544489321
num_examples: 315523
download_size: 231674441
dataset_size: 544489321
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- music
- audio
- art
📺 YouTube-CC-BY-Music 📺
YouTube-CC-BY-Music is a comprehensive collection of metadata for 316,000 music tracks shared on YouTube. If you want the version of this dataset including prompt, see https://huggingface.co/datasets/WaveGenAI/youtube-cc-by-music_annoted.
Content
The dataset includes descriptions, tags, and other metadata associated with 316,000 music videos uploaded to YouTube under the CC-BY license. These videos come from a diverse range of artists and genres, providing a rich resource for various music-related tasks in artificial intelligence and machine learning.
Key Features:
- 316,000 music tracks with accompanying metadata
- Detailed metadata including descriptions, tags, channel names, video titles, and upload dates
This dataset is ideal for training and evaluating models for:
- Music generation
- Music tagging and classification
- Audio-to-text generation (e.g., automatic description of music)
License and Ethics
All metadata in this dataset is sourced from YouTube videos shared under the CC-BY license. As per the license requirements, all contributions are fully credited, ensuring proper attribution to the content creators.
Acknowledgements
The dataset description was inspired by the YouTube-Commons project.