---
title: acapella
canonical_url: "https://www.modelscope.cn/datasets/ccmusic-database/acapella"
md_url: "https://www.modelscope.cn/datasets/ccmusic-database/acapella.md"
repository: ccmusic-database/acapella
chinese_name: "歌唱干声评价数据集"
last_updated: 2026-08-05
license: CC-BY-NC-ND
storage_size: "1.3 GB"
domain:
  - audio
tasks:
  - audio-classification
downloads: 3752
stars: 17
---

# acapella

> acapella - ccmusic-database 在 ModelScope 开源的数据集。本数据集包含由22位歌手翻唱的6首普通话歌曲，共132段（.wav格式），每段翻唱均由一段主歌及一段副歌组成。由4位专业评委从音准、节奏、音域、音色、发音、颤音、音量变化、气息控制、整体表现等九个方面进行评价打分，满分10分制。打分情况记录在《调查问卷评分结果》中。

ccmusic-database/acapella 是 ModelScope 魔搭社区上的audio-classification数据集，涉及 audio 领域，存储大小 1.3 GB，采用 CC-BY-NC-ND 许可。

- **Repository**: ccmusic-database/acapella
- **License**: CC-BY-NC-ND
- **Tasks**: audio-classification
- **Domain**: audio
- **Storage size**: 1.3 GB
- **Downloads**: 3752
- **Stars**: 17
- **Last updated**: 2026-08-05

Source: https://www.modelscope.cn/datasets/ccmusic-database/acapella

---

# 简介 Intro
原始数据集来源于 [歌唱干声评价数据集](https://ccmusic-database.github.io/database/ccm.html#shou2)，包括由 22 位歌手演唱的六首华语流行歌曲片段，共产生了 132 个音频剪辑。每个片段都包括一段主歌和副歌。来自中国音乐学院的四位评委根据音准、节奏、音域、音色、发音、颤音、音量、气息控制和整体表现这九个维度对演唱进行评估，使用 10 分制量表。评估结果记录在 .xls 格式的 Excel 电子表格中。

由于原始数据集包含音频录音和评估表的独立文件，这妨碍了高效的数据检索，因此我们将原始声乐录音和相应的评估表合并在一起，构建出了当前集成版数据集的 [默认子集](#快速使用-usage)，其数据结构见 [数据预览](https://www.modelscope.cn/datasets/ccmusic-database/acapella/dataPeview)。当前数据集已有发表的文章背书，因此无需再构建校验子集。

The original dataset, sourced from the [Acapella Evaluation Dataset](https://ccmusic-database.github.io/en/database/ccm.html#shou2), 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.

Due to the original dataset comprising separate files for audio recordings and evaluation sheets, which hindered efficient data retrieval, we combined the original vocal recordings with their corresponding evaluation sheets to construct the [default subset](#快速使用-usage) of the current integrated version of the dataset. The data structure can be viewed in the [viewer](https://www.modelscope.cn/datasets/ccmusic-database/acapella/dataPeview). The current dataset is already endorsed by published articles, hence there is no need to construct the eval subset.

## 总量统计 Totals
| 总数据量 Total count | 总时长(秒) Total duration(s) |
| :------------------: | :--------------------------: |
|        `132`         |     `12493.827541666662`     |

## 快速使用 Usage
:modelscope-code[]{type="sdk"}

## 维护 Clone with HTTP
```bash
GIT_LFS_SKIP_SMUDGE=1 
```

:modelscope-code[]{type="git"}

## 镜像 Mirror
<https://huggingface.co/datasets/ccmusic-database/acapella>

## 校验 Evaluation
[1] [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)

## 引用 Cite
```bibtex
@article{Li2022SingingVoiceTE,
  title   = {Singing-Voice Timbre Evaluations Based on Transfer Learning},
  author  = {Rongfeng Li and Mingtong Zhang},
  journal = {Applied Sciences},
  year    = {2022},
  url     = {https://api.semanticscholar.org/CorpusID:252766951}
}
```

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