license: cc-by-nc-nd-4.0
task_categories:
- time-series-forecasting
language:
- en
tags:
- music
- art
pretty_name: Song Structure Annotation Database
size_categories:
- n<1K
viewer: false
Dataset Card for Song Structure
The raw dataset comprises 300 pop songs in .mp3 format, sourced from the NetEase music, accompanied by a structure annotation file for each song in .txt format. The annotator for music structure is a professional musician and teacher from the China Conservatory of Music. For the statistics of the dataset, there are 208 Chinese songs, 87 English songs, three Korean songs and two Japanese songs. The song structures are labeled as follows: intro, re-intro, verse, chorus, pre-chorus, post-chorus, bridge, interlude and ending. Below figure shows the frequency of each segment label that appears in the set. The labels chorus and verse are the two most prevalent segment labels in the dataset and they are the most common segment in Western popular music. Among them, the number of “Postchorus” tags is the least, with only two present.
Viewer
https://www.modelscope.cn/datasets/ccmusic-database/song_structure/dataPeview
Dataset Structure
| audio | mel | label |
|---|---|---|
| .mp3, 22050Hz | .jpg, 22050Hz | {onset_time:uint32,offset_time:uint32,structure:string} |
| ... | ... | ... |
Maintenance
git clone git@hf.co:datasets/ccmusic-database/song_structure
cd song_structure
Data Instances
.zip(.mp3), .txt
Data Fields
intro, chorus, verse, pre-chorus, post-chorus, bridge, ending
Data Splits
train
Dataset Description
- Homepage: https://ccmusic-database.github.io
- Repository: https://huggingface.co/datasets/ccmusic-database/song_structure
- Paper: https://doi.org/10.5281/zenodo.5676893
- Leaderboard: https://ccmusic-database.github.io/team.html
- Point of Contact: https://www.modelscope.cn/datasets/ccmusic-database/song_structure
Dataset Summary
Unlike the above three datasets for classification, this one has not undergone pre-processing such as spectrogram transform. Thus we provide the original content only. The integrated version of the dataset is organized based on audio files, with each item structured into three columns: The first column contains the audio of the song in .mp3 format, sampled at 22,050 Hz. The second column consists of lists indicating the time points that mark the boundaries of different song sections, while the third column contains lists corresponding to the labels of the song structures listed in the second column. Strictly speaking, the first column represents the data, while the subsequent two columns represent the label.
Supported Tasks and Leaderboards
time-series-forecasting
Languages
Chinese, English
Usage
from datasets import load_dataset
dataset = load_dataset("ccmusic-database/song_structure", split="train")
for item in dataset:
print(item)
Dataset Creation
Curation Rationale
Lack of a dataset for song structure
Source Data
Initial Data Collection and Normalization
Zhaorui Liu, Monan Zhou
Who are the source language producers?
Students from CCMUSIC
Annotations
Annotation process
Students from CCMUSIC collected 300 pop songs, as well as a structure annotation file for each song
Who are the annotators?
Students from CCMUSIC
Personal and Sensitive Information
Due to copyright issues with the original music, only features of audio by frame are provided in the dataset
Considerations for Using the Data
Social Impact of Dataset
Promoting the development of the AI music industry
Discussion of Biases
Only for mp3
Other Known Limitations
Most are Chinese songs
Additional Information
Dataset Curators
Zijin Li
Evaluation
https://www.modelscope.cn/models/ccmusic-database/song_structure
Citation Information
@dataset{zhaorui_liu_2021_5676893,
author = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han},
title = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research},
month = {mar},
year = {2024},
publisher = {HuggingFace},
version = {1.2},
url = {https://huggingface.co/ccmusic-database}
}
Contributions
Provide a dataset for song structure