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--- |
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license: mit |
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task_categories: |
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- audio-classification |
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- table-question-answering |
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- summarization |
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language: |
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- zh |
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- en |
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tags: |
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- music |
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- art |
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pretty_name: Acapella Evaluation Dataset |
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size_categories: |
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- n<1K |
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viewer: false |
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--- |
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# Dataset Card for Acapella Evaluation |
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This raw dataset comprises six Mandarin pop song segments performed by 22 singers, resulting in a total of 132 audio clips. Each segment includes both a verse and a chorus. Four judges from the China Conservatory of Music assess the singing across nine dimensions: pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamics, breath control, and overall performance, using a 10-point scale. The evaluations are recorded in an Excel spreadsheet in .xls format. |
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## Dataset Description |
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- **Homepage:** <https://ccmusic-database.github.io> |
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- **Repository:** <https://huggingface.co/datasets/CCMUSIC/acapella_evaluation> |
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- **Paper:** <https://doi.org/10.5281/zenodo.5676893> |
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- **Leaderboard:** <https://www.modelscope.cn/datasets/ccmusic/acapella> |
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- **Point of Contact:** <https://www.mdpi.com/2076-3417/12/19/9931> |
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### Dataset Summary |
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Due to the original dataset comprising separate files for audio recordings and evaluation sheets, which hindered efficient data retrieval, we have consolidated the raw vocal recordings with their corresponding assessments. The dataset is divided into six segments, each representing a different song, resulting in a total of six divisions. Each segment contains 22 entries, with each entry detailing the vocal recording of an individual singer sampled at 22,050 Hz, the singer's ID, and evaluations across the nine dimensions previously mentioned. Consequently, each entry encompasses 11 columns of data. This dataset is well-suited for tasks such as vocal analysis and regression-based singing voice rating. For instance, as previously stated, the final column of each entry denotes the overall performance score, allowing the audio to be utilized as data and this score to serve as the label for regression analysis. |
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### Supported Tasks and Leaderboards |
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Acapella evaluation/scoring |
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### Languages |
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Chinese, English |
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## Maintenance |
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```bash |
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GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/ccmusic-database/acapella |
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cd acapella |
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``` |
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## Usage |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("ccmusic-database/acapella") |
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for i in range(1, 7): |
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for item in dataset[f"song{i}"]: |
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print(item) |
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``` |
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## Dataset Structure |
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| audio(22050Hz) | mel(22050Hz) | singer_id | pitch / rhythm / ... / overall_performance | |
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| :-------------------------------------------------------------------------------------------------------------------------: | :-------------------------------: | :-------: | :----------------------------------------: | |
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| <audio controls src="https://huggingface.co/datasets/ccmusic-database/acapella/resolve/main/data/song1%20(16).wav"></audio> | <img src="./data/song1 (16).jpg"> | int | float(0-10) | |
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| ... | ... | ... | ... | |
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### Data Instances |
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.wav & .csv |
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### Data Fields |
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song, singer id, pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dynamic, breath control and overall performance |
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### Data Splits |
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song1-6 |
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## Dataset Creation |
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### Curation Rationale |
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Lack of a training dataset for the acapella scoring system |
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### Source Data |
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#### Initial Data Collection and Normalization |
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Zhaorui Liu, Monan Zhou |
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#### Who are the source language producers? |
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Students and judges from CCMUSIC |
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### Annotations |
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#### Annotation process |
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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 on a sheet. |
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#### Who are the annotators? |
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Judges from CCMUSIC |
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### Personal and Sensitive Information |
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Singers' and judges' names are hided |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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Providing a training dataset for the acapella scoring system may improve the development of related Apps |
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### Discussion of Biases |
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Only for Mandarin songs |
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### Other Known Limitations |
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No starting point has been marked for the vocal |
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## Additional Information |
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### Dataset Curators |
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Zijin Li |
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### Evaluation |
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[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) |
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### Licensing Information |
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``` |
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MIT License |
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Copyright (c) CCMUSIC |
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Permission is hereby granted, free of charge, to any person obtaining a copy |
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of this software and associated documentation files (the "Software"), to deal |
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in the Software without restriction, including without limitation the rights |
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell |
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copies of the Software, and to permit persons to whom the Software is |
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furnished to do so, subject to the following conditions: |
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The above copyright notice and this permission notice shall be included in all |
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copies or substantial portions of the Software. |
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
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SOFTWARE. |
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``` |
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### Citation Information |
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```bibtex |
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@dataset{zhaorui_liu_2021_5676893, |
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author = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han}, |
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title = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research}, |
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month = {mar}, |
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year = {2024}, |
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publisher = {HuggingFace}, |
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version = {1.2}, |
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url = {https://huggingface.co/ccmusic-database} |
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} |
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``` |
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### Contributions |
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Provide a training dataset for the acapella scoring system |
