ccmusic-database/chest_falsetto

Dataset Card for Chest voice and Falsetto Dataset

The raw dataset comprises 1,280 monophonic singing audio files in .wav format (sample rate is 22,050 Hz), consisting of chest and falsetto voices performed, recorded, and annotated by students majoring in Vocal Music at the China Conservatory of Music. The chest voice is tagged as chest and the falsetto voice is tagged as falsetto. Additionally, the dataset includes the Mel spectrogram, Mel frequency cepstral coefficient (MFCC), and spectral characteristics of each audio segment, resulting in a total of 5,120 CSV files. The original dataset did not differentiate between male and female voices, an omission that is critical for accurately identifying chest and falsetto vocal techniques. To address this, we conducted a meticulous manual review and added gender annotations to the dataset. Besides the original content, the preprocessed version during the evaluation which will be detailed in section IV is also provided. This approach which provides two versions is applied to the two subsequent classification datasets that have not been evaluated as well: Music Genre Dataset, Bel Conto & Chinese Folk Singing Dataset.

Eval Subset

from datasets import load_dataset

ds = load_dataset("ccmusic-database/chest_falsetto", 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

ds = load_dataset("ccmusic-database/chest_falsetto", 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/chest_falsetto
cd chest_falsetto

Dataset Summary

For the pre-processed version, the audio clip was into 0.25 seconds and then transformed to Mel, CQT and Chroma spectrogram in .jpg format, resulting in 8,974 files. The chest/falsetto label for each file is given as one of the four classes: m chest, m falsetto, f chest, and f falsetto. The spectrogram, the chest/falsetto label and the gender label are combined into one data entry, with the first three columns representing the Mel, CQT and Chroma. The fourth and fifth columns are the chest/falsetto label and gender label, respectively. Additionally, the integrated dataset provides the function to shuffle and split the dataset into training, validation, and test sets in an 8:1:1 ratio. This dataset can be used for singing-related tasks such as singing gender classification or chest and falsetto voice classification.

Supported Tasks and Leaderboards

Audio classification, singing method classification, voice classification

Languages

Chinese, English

Dataset Structure

Eval Subset

mel(.jpg, 48000Hz)	cqt(.jpg, 48000Hz)	chroma(.jpg, 48000Hz)	label	gender	singing_method
			m_chest, m_falsetto, f_chest, f_falsetto	male, female	chest, falsetto
...	...	...	...	...	...

Raw Subset

audio(.wav, 22050Hz)	mel(spectrogram, .jpg, 22050Hz)	label(4-class)	gender(2-class)	singing_method(2-class)
		m_chest, m_falsetto, f_chest, f_falsetto	male, female	chest, falsetto
...	...	...	...	...

Data Instances

.zip(.wav, .jpg)

Data Fields

m_chest, f_chest, m_falsetto, f_falsetto

Data Splits

Split	Eval	Raw
total	8974	1280
train(80%)	7179	1024
validation(10%)	897	128
test(10%)	898	128

Dataset Creation

Curation Rationale

Lack of a dataset for Chest voice and Falsetto

Source Data

Initial Data Collection and Normalization

Zhaorui Liu, Monan Zhou

Who are the source language producers?

Students from CCMUSIC

Annotations

Annotation process

1280 monophonic singing audio (.wav format) of chest and falsetto voices, with chest voice tagged as chest and falsetto voice tagged as falsetto.

Who are the annotators?

Students from CCMUSIC

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 chest and falsetto voices

Other Known Limitations

Recordings are cut into slices that are too short; The CQT spectrum column has the problem of spectrum leakage, but because the original audio slice is too short, only 0.5s, it cannot effectively avoid this problem.

Additional Information

Dataset Curators

Zijin Li

Evaluation

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

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 chest and falsetto voices