
# Dataset Card for Bel Conto and Chinese Folk Song Singing Tech
## Maintenance
```bash
GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/ccmusic-database/bel_canto
```

## Dataset Description
- **Homepage:** <https://ccmusic-database.github.io>
- **Repository:** <https://huggingface.co/datasets/ccmusic-database/bel_canto>
- **Paper:** <https://doi.org/10.5281/zenodo.5676893>
- **Leaderboard:** <https://ccmusic-database.github.io/team.html>
- **Point of Contact:** N/A

### 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
<style>
  #belcanto td {
    vertical-align: middle !important;
    text-align: center;
  }
  #belcanto th {
    text-align: center;
  }
</style>
<table id="belcanto">
    <tr>
        <th>mel<br>(.jpg, 1.6s)</th>
        <th>cqt<br>(.jpg, 1.6s)</th>
        <th>chroma<br>(.jpg, 1.6s)</th>
        <th>label<br>(4-class)</th>
        <th>gender<br>(2-class)</th>
        <th>singing_method<br>(2-class)</th>
    </tr>
    <tr>
        <td><img src="https://cdn-uploads.huggingface.co/production/uploads/655e0a5b8c2d4379a71882a9/TSTXTg2s2j6gs3O8q_bpD.jpeg"></td>
        <td><img src="https://cdn-uploads.huggingface.co/production/uploads/655e0a5b8c2d4379a71882a9/BiuWkk_rkYBfN2hqG60Iy.jpeg"></td>
        <td><img src="https://cdn-uploads.huggingface.co/production/uploads/655e0a5b8c2d4379a71882a9/WmcP0UsMe_9lmLmNpAOzr.jpeg"></td>
        <td>m_bel, f_bel, m_folk, f_folk</td>
        <td>male, female</td>
        <td>Folk_Singing, Bel_Canto</td>
    </tr>
    <tr>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
    </tr>
</table>

### Data Instances
.zip(.wav, .jpg)

### Data Fields
m_bel, f_bel, m_folk, f_folk

### Data Splits 
|      total      | 9603  |
| :-------------: | :---: |
|   train(80%)    | 7682  |
| validation(10%) |  960  |
|    test(10%)    |  961  |

## 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       = {Zhaorui Liu, Monan Zhou, Shenyang Xu, Yuan Wang, Zhaowen Wang, Wei Li and Zijin Li},
  title        = {CCMUSIC DATABASE: A Music Data Sharing Platform for Computational Musicology Research},
  month        = {nov},
  year         = {2021},
  publisher    = {Zenodo},
  version      = {1.1},
  doi          = {10.5281/zenodo.5676893},
  url          = {https://doi.org/10.5281/zenodo.5676893}
}
```

### Contributions
Provide a dataset for distinguishing Bel Conto and Chinese folk song singing tech
task_categories:audio-classification task_categories:image-classification size_categories:1K<n<10K language:zh language:en license:mit music art region:us
{"language": ["zh", "en"], "license": "mit", "size_categories": ["1K<n<10K"], "task_categories": ["audio-classification", "image-classification"], "pretty_name": "Bel Conto and Chinese Folk Song Singing Tech", "tags": ["music", "art"], "viewer": false}
TAGS
#task_categories-audio-classification #task_categories-image-classification #size_categories-1K<n<10K #language-Chinese #language-English #license-mit #music #art #region-us 

Dataset Card for Bel Conto and Chinese Folk Song Singing Tech
=============================================================


Maintenance
-----------


Dataset Description
-------------------


* Homepage:
* Repository: <URL
* Paper: <URL
* Leaderboard: <URL
* Point of Contact: N/A


### 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
-----------------



 #belcanto td {
 vertical-align: middle !important;
 text-align: center;
 }
 #belcanto th {
 text-align: center;
 }



| mel(.jpg, 1.6s) | cqt(.jpg, 1.6s) | chroma(.jpg, 1.6s) | label(4-class) | gender(2-class) | singing\_method(2-class) |
| --- | --- | --- | --- | --- | --- |
| <img src="URL
 <td>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



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


<URL


### Licensing Information


### Contributions


Provide a dataset for distinguishing Bel Conto and Chinese folk song singing tech



### 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
-----------------



 #belcanto td {
 vertical-align: middle !important;
 text-align: center;
 }
 #belcanto th {
 text-align: center;
 }



| mel(.jpg, 1.6s) | cqt(.jpg, 1.6s) | chroma(.jpg, 1.6s) | label(4-class) | gender(2-class) | singing\_method(2-class) |
| --- | --- | --- | --- | --- | --- |
| <img src="URL
 <td>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



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


<URL ### Licensing Information ### Contributions


Provide a dataset for distinguishing Bel Conto and Chinese folk song singing tech
TAGS
#task_categories-audio-classification #task_categories-image-classification #size_categories-1K<n<10K #language-Chinese #language-English #license-mit #music #art #region-us 
 ### 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
-----------------



 #belcanto td {
 vertical-align: middle !important;
 text-align: center;
 }
 #belcanto th {
 text-align: center;
 }



| mel(.jpg, 1.6s) | cqt(.jpg, 1.6s) | chroma(.jpg, 1.6s) | label(4-class) | gender(2-class) | singing\_method(2-class) |
| --- | --- | --- | --- | --- | --- |
| <img src="URL
 <td>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



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


<URL ### Licensing Information ### Contributions


Provide a dataset for distinguishing Bel Conto and Chinese folk song singing tech
passage: TAGS
#task_categories-audio-classification #task_categories-image-classification #size_categories-1K<n<10K #language-Chinese #language-English #license-mit #music #art #region-us 
### 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
-----------------



 #belcanto td {
 vertical-align: middle !important;
 text-align: center;
 }
 #belcanto th {
 text-align: center;
 }



| mel(.jpg, 1.6s) | cqt(.jpg, 1.6s) | chroma(.jpg, 1.6s) | label(4-class) | gender(2-class) | singing\_method(2-class) |
| --- | --- | --- | --- | --- | --- |
| <img src="URL
 <td>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



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.