task_categories:audio-classification task_categories:table-question-answering task_categories:summarization size_categories:n<1K language:zh language:en license:mit music art region:us
This database contains 6 Mandarin song segments sung by 22 singers, totaling 132 audio clips. 
Each segment consists of a verse and a chorus. Four judges evaluate the singing from nine aspects 
which are pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and 
overall performance on a 10-point scale. The scores are recorded in a sheet.
@dataset{zhaorui_liu_2021_5676893,
  author       = {Zhaorui Liu, Monan Zhou, Shenyang Xu and Zijin Li},
  title        = {{Music Data Sharing Platform for Computational Musicology Research (CCMUSIC DATASET)}},
  month        = nov,
  year         = 2021,
  publisher    = {Zenodo},
  version      = {1.1},
  doi          = {10.5281/zenodo.5676893},
  url          = {https://doi.org/10.5281/zenodo.5676893}
}
---
license: mit
task_categories:
- audio-classification
- table-question-answering
- summarization
language:
- zh
- en
tags:
- music
- art
pretty_name: Acapella Evaluation Dataset
size_categories:
- n<1K
---
# Dataset Card for Acapella Evaluation Dataset

## Dataset Description

- **Homepage:** <https://ccmusic-database.github.io>
- **Repository:** <https://huggingface.co/datasets/CCMUSIC/acapella_evaluation>
- **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 6 Mandarin song segments sung by 22 singers, totaling 132 audio clips. Each segment consists of a verse and a chorus. Four judges evaluate the singing from nine aspects which are pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and overall performance on a 10-point scale. The scores are recorded in a sheet.

### Supported Tasks and Leaderboards

Acapella evaluation/scoring

### Languages

Chinese, English

## Dataset Structure

### Data Instances

.wav & .csv

### Data Fields

song, singer id, pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and overall performance

### Data Splits

song1-6

## Dataset Creation

### Curation Rationale

Lack of a training dataset for acapella scoring system

### Source Data

#### Initial Data Collection and Normalization

Zhaorui Liu, Monan Zhou

#### Who are the source language producers?

Students and judges from CCMUSIC

### Annotations

#### Annotation process

6 Mandarin song segments were sung by 22 singers, totaling 132 audio clips. Each segment consists of a verse and a chorus. Four judges evaluate the singing from nine aspects which are pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and overall performance on a 10-point scale. The scores are recorded in a sheet.

#### Who are the annotators?

Judges from CCMUSIC

### Personal and Sensitive Information

Singers' and judges' names are hided

## Considerations for Using the Data

### Social Impact of Dataset

Providing a training dataset for acapella scoring system may improve the developement of related Apps

### Discussion of Biases

Only for Mandarin songs

### Other Known Limitations

No starting point has been marked for the vocal

## Additional Information

### Dataset Curators

Zijin Li

### Evaluation
[Li, R.; Zhang, M. Singing-Voice Timbre Evaluations Based on Transfer Learning. Appl. Sci. 2022, 12, 9931. https://doi.org/10.3390/app12199931](https://www.mdpi.com/2076-3417/12/19/9931)

### 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 and Zijin Li},
  title        = {CCMUSIC DATABASE: 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 training dataset for acapella scoring system