ccmusic-database/song_structure

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 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