---
license: cc-by-nc-nd-4.0
task_categories:
- audio-classification
language:
- zh
- en
tags:
- music
- art
pretty_name: Musical Instruments Timbre Evaluation Database
size_categories:
- n<1K
viewer: false
---

# Dataset Card for Chinese Musical Instruments Timbre Evaluation Database
The raw dataset encompasses subjective timbre evaluation scores comprising 16 terms, such as bright, dark, raspy, etc, evaluated across 37 Chinese instruments and 24 Western instruments by 14 participants with musical backgrounds in a subjective evaluation experiment. Additionally, it includes 10 reports on spectrogram analysis of 10 instruments.

## Viewer
<https://www.modelscope.cn/datasets/ccmusic-database/instrument_timbre/dataPeview>

## Dataset Structure
<style>
  .datastructure td {
    vertical-align: middle !important;
    text-align: center;
  }
  .datastructure th {
    text-align: center;
  }
</style>

<table class="datastructure">
    <tr>
        <th>audio(.wav, 22050Hz)</th>
        <th>mel(.jpg, 22050Hz)</th>
        <th>instrument_name</th>
        <th>slim / bright / ... / turbid</th>
    </tr>
    <tr>
        <td><audio controls src="https://huggingface.co/datasets/ccmusic-database/instrument_timbre/resolve/main/data/36.wav"></td>
        <td><img src="./data/36.jpg"></td>
        <td>string</td>
        <td>float(0-10)</td>
    </tr>
    <tr>
        <td>...</td>
        <td>...</td>
        <td>...</td>
        <td>...</td>
    </tr>
</table>

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

### Data Fields
Chinese traditional instruments / Western instruments

### Data Splits
Chinese, Western

## Dataset Description
- **Homepage:** <https://ccmusic-database.github.io>
- **Repository:** <https://huggingface.co/datasets/ccmusic-database/CMITE>
- **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-database/instrument_timbre>

### Dataset Summary
During the integration, we have crafted the Chinese part and the Non-Chinese part into two splits. Each split is composed of multiple data entries, with each entry structured across 18 columns. The Chinese split encompasses 37  entries, while the Non-Chinese split includes 24 entries. The premier column of each data entry presents the instrument recordings in the .wav format, sampled at a rate of 22,050 Hz. The second column provides the Chinese pinyin or English name of the instrument. The subsequent 16 columns correspond to the 10-point score of the 16 terms. This dataset is suitable for conducting timber analysis of musical instruments and can also be utilized for various single or multiple regression tasks related to term scoring.

### Supported Tasks and Leaderboards
Musical Instruments Timbre Evaluation

### Languages
Chinese, English

## Usage
```python
from datasets import load_dataset

dataset = load_dataset("ccmusic-database/instrument_timbre")
for item in ds["Chinese"]:
    print(item)

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

## Maintenance
```bash
GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/ccmusic-database/instrument_timbre
cd instrument_timbre
```

## Dataset Creation
### Curation Rationale
Lack of a dataset for musical instruments timbre evaluation

### Source Data
#### Initial Data Collection and Normalization
Zhaorui Liu, Monan Zhou

#### Who are the source language producers?
Students from CCMUSIC

### Annotations
#### Annotation process
Subjective timbre evaluation scores of 16 subjective timbre evaluation terms (such as bright, dark, raspy) on 37 Chinese national and 24 Non-Chinese terms given by 14 participants in a subjective evaluation experiment

#### 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 traditional instruments

### Other Known Limitations
Limited data

## Additional Information
### Dataset Curators
Zijin Li

### Evaluation
#### For Chinese instruments
[Yiliang, J. et al. (2020) ‘Analysis of Chinese Musical Instrument Timbre Based on Objective Features’, Journal of Fudan University(Natural Science), pp. 346-353+359. doi:10.15943/j.cnki.fdxb-jns.2020.03.014.](https://kns.cnki.net/kcms/detail/detail.aspx?dbcode=CJFD&dbname=CJFDLAST2020&filename=FDXB202003014&uniplatform=NZKPT&v=85qLeLUyrDt%25mmd2Btak%25mmd2BN90N7vYZSv%25mmd2BVc1EfPmaYcvpvrgY1XkL215gYG4J%25mmd2FD09viR0w)
#### For Non-Chinese instruments
[Jiang, Wei et al. “Analysis and Modeling of Timbre Perception Features of Chinese Musical Instruments.” 2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS) (2019): 191-195.](https://ieeexplore.ieee.org/document/8940168)

### 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 musical instruments' timbre evaluation