README.md

---
license: mit
task_categories:
- audio-classification
language:
- zh
- en
tags:
- music
- art
pretty_name: Chest voice and Falsetto Dataset
size_categories:
- 1K<n<10K
viewer: false
---

# 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
```python
from modelscope.msdatasets import MsDataset

ds = MsDataset.load("ccmusic/chest_falsetto", subset_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
```python
from modelscope.msdatasets import MsDataset

ds = MsDataset.load("ccmusic/chest_falsetto", subset_name="default")
for item in ds["train"]:
    print(item)

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

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

## Maintenance
```bash
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/datasets/ccmusic/chest_falsetto.git
cd chest_falsetto
```

## Dataset Description
- **Homepage:** <https://ccmusic-database.github.io>
- **Repository:** <https://huggingface.co/datasets/ccmusic-database/chest_falsetto>
- **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/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
<style>
  .datastructure td {
    vertical-align: middle !important;
    text-align: center;
  }
  .datastructure th {
    text-align: center;
  }
</style>
### Eval Subset
<table class="datastructure">
    <tr>
        <th>mel(.jpg, 48000Hz)</th>
        <th>cqt(.jpg, 48000Hz)</th>
        <th>chroma(.jpg, 48000Hz)</th>
        <th>label</th>
        <th>gender</th>
        <th>singing_method</th>
    </tr>
    <tr>
        <td><img src="./data/W8wy7pkYZtCt3lI5Oq39l.jpeg"></td>
        <td><img src="./data/48qPVDDIZe0ttsYXrTJEh.jpeg"></td>
        <td><img src="./data/zm0KorKYtmvOje8qmivHJ.jpeg"></td>
        <td>m_chest, m_falsetto, f_chest, f_falsetto</td>
        <td>male, female</td>
        <td>chest, falsetto</td>
    </tr>
    <tr>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
    </tr>
</table>

### Raw Subset
<table class="datastructure">
    <tr>
        <th>audio(.wav, 22050Hz)</th>
        <th>mel(spectrogram, .jpg, 22050Hz)</th>
        <th>label(4-class)</th>
        <th>gender(2-class)</th>
        <th>singing_method(2-class)</th>
    </tr>
    <tr>
        <td><audio controls src="https://cdn-uploads.huggingface.co/production/uploads/655e0a5b8c2d4379a71882a9/LKSBb11kCyPl15b-DJo6V.wav"></audio></td>
        <td><img src="./data/0001_m_chest.jpg"></td>
        <td>m_chest, m_falsetto, f_chest, f_falsetto</td>
        <td>male, female</td>
        <td>chest, falsetto</td>
    </tr>
    <tr> 
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
    </tr>
</table>

### 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
```bibtex
@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