ccmusic-database/bel_canto

Dataset Card for Bel Conto and Chinese Folk Song Singing Tech

The raw dataset contains 203 acapella singing clips (sampled at 22,050 Hz) that are sung in two styles, Bel Conto and Chinese folk singing style by professional vocalists. All of them are sung by professional vocalists and were recorded in professional commercial recording studios. Besides the original version, the pre-processed version is included.

Usage

Eval Subset

from datasets import load_dataset

dataset = load_dataset("ccmusic-database/bel_canto", name="eval")
for item in ds["train"]:
    print(item)

for item in ds["validation"]:
    print(item)

for item in ds["test"]:
    print(item)

Raw Subset

from datasets import load_dataset

dataset = load_dataset("ccmusic-database/bel_canto", name="default")
for item in ds["train"]:
    print(item)

for item in ds["validation"]:
    print(item)

for item in ds["test"]:
    print(item)

Maintenance

GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/ccmusic-database/bel_canto
cd bel_canto

Dataset Summary

This database contains hundreds of acapella singing clips that are sung in two styles, Bel Conto and Chinese national singing style by professional vocalists. All of them are sung by professional vocalists and were recorded in professional commercial recording studios.

Supported Tasks and Leaderboards

Audio classification, Image classification, singing method classification, voice classification

Languages

Chinese, English

Dataset Structure

Eval Subset

mel (.jpg, 1.6s, 48000Hz)	cqt (.jpg, 1.6s, 48000Hz)	chroma (.jpg, 1.6s, 48000Hz)	label (4-class)	gender (2-class)	singing_method (2-class)
			m_bel, f_bel, m_folk, f_folk	male, female	Folk_Singing, Bel_Canto
...	...	...	...	...	...

Raw Subset

audio(.wav, 22050Hz)	mel(spectrogram, .jpg, 22050Hz)	label(4-class)	gender(2-class)	singing_method(2-class)
		m_bel, f_bel, m_folk, f_folk	male, female	Folk_Singing, Bel_Canto
...	...	...	...	...

Data Instances

.zip(.wav, .jpg)

Data Fields

m_bel, f_bel, m_folk, f_folk

Data Splits

Split	Eval	Raw
total	9603	203
train(80%)	7682	162
validation(10%)	960	20
test(10%)	961	21

Dataset Creation

Curation Rationale

Lack of a dataset for Bel Conto and Chinese folk song singing tech

Source Data

Initial Data Collection and Normalization

Zhaorui Liu, Monan Zhou

Who are the source language producers?

Students from CCMUSIC

Annotations

Annotation process

All of them are sung by professional vocalists and were recorded in professional commercial recording studios.

Who are the annotators?

professional vocalists

Personal and Sensitive Information

None

Considerations for Using the Data

Social Impact of Dataset

Promoting the development of AI in the music industry

Discussion of Biases

Only for Chinese songs

Other Known Limitations

Some singers may not have enough professional training in classical or ethnic vocal techniques.

Additional Information

Dataset Curators

Zijin Li

Evaluation

https://huggingface.co/ccmusic-database/bel_canto

Licensing Information

MIT License

Copyright (c) CCMUSIC

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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 distinguishing Bel Conto and Chinese folk song singing tech