---
title: SongFormBench
canonical_url: "https://www.modelscope.cn/datasets/ASLP-lab/SongFormBench"
md_url: "https://www.modelscope.cn/datasets/ASLP-lab/SongFormBench.md"
repository: ASLP-lab/SongFormBench
last_updated: 2026-05-15
license: cc-by-4.0
storage_size: "5.0 GB"
downloads: 1902
stars: 0
---

# SongFormBench

> SongFormBench - ASLP-lab 在 ModelScope 开源的数据集。A High-Quality Benchmark for Music Structure Analysis

ASLP-lab/SongFormBench 是 ModelScope 魔搭社区上的数据集，存储大小 5.0 GB，采用 cc-by-4.0 许可。

- **Repository**: ASLP-lab/SongFormBench
- **License**: cc-by-4.0
- **Storage size**: 5.0 GB
- **Downloads**: 1902
- **Stars**: 0
- **Last updated**: 2026-05-15

Source: https://www.modelscope.cn/datasets/ASLP-lab/SongFormBench

---

# SongFormBench 🏆

[English ｜ [中文](README_ZH.md)]

**A High-Quality Benchmark for Music Structure Analysis**

<div align="center">

![Python](https://img.shields.io/badge/Python-3.10-brightgreen)
![License](https://img.shields.io/badge/License-CC%20BY%204.0-lightblue)
[![arXiv Paper](https://img.shields.io/badge/arXiv-2510.02797-blue)](https://arxiv.org/abs/2510.02797)
[![GitHub](https://img.shields.io/badge/GitHub-SongFormer-black)](https://github.com/ASLP-lab/SongFormer)
[![HuggingFace Space](https://img.shields.io/badge/HuggingFace-space-yellow)](https://huggingface.co/spaces/ASLP-lab/SongFormer)
[![HuggingFace Model](https://img.shields.io/badge/HuggingFace-model-blue)](https://huggingface.co/ASLP-lab/SongFormer)
[![Dataset SongFormDB](https://img.shields.io/badge/HF%20Dataset-SongFormDB-green)](https://huggingface.co/datasets/ASLP-lab/SongFormDB)
[![Dataset SongFormBench](https://img.shields.io/badge/HF%20Dataset-SongFormBench-orange)](https://huggingface.co/datasets/ASLP-lab/SongFormBench)
[![Discord](https://img.shields.io/badge/Discord-join%20us-purple?logo=discord&logoColor=white)](https://discord.gg/p5uBryC4Zs)
[![lab](https://img.shields.io/badge/🏫-ASLP-grey?labelColor=lightgrey)](http://www.npu-aslp.org/)

</div>

<div align="center">
  <h3>
    Chunbo Hao<sup>1*</sup>, Ruibin Yuan<sup>2,6*</sup>, Jixun Yao<sup>1</sup>, Qixin Deng<sup>3,6</sup>,<br>Xinyi Bai<sup>4,6</sup>, Yanbo Wang<sup>5</sup>, Wei Xue<sup>2</sup>, Lei Xie<sup>1†</sup>
  </h3>


  <p>
    <sup>*</sup>Equal contribution &nbsp;&nbsp; <sup>†</sup>Corresponding author
  </p>
  <p>
    <sup>1</sup>Audio, Speech and Language Processing Group (ASLP@NPU),<br>School of Computer Science, Northwestern Polytechnical University<br>
    <sup>2</sup>Hong Kong University of Science and Technology<br>
    <sup>3</sup>Northwestern University<br>
    <sup>4</sup>Cornell University<br>
    <sup>5</sup>University of New South Wales<br>
    <sup>6</sup>Multimodal Art Projection (M-A-P)
  </p>

</div>

---

## 🌟 What is SongFormBench?

SongFormBench is a **carefully curated, expert-annotated benchmark** designed to revolutionize music structure analysis (MSA) evaluation. Our dataset provides a unified standard for comparing MSA models.

### 📊 Dataset Composition

- **🎸 SongFormBench-HarmonixSet (BHX)**: 200 songs from HarmonixSet
- **🎤 SongFormBench-CN (BC)**: 100 Chinese popular songs

**Total: 300 high-quality annotated songs**

---

## ✨ Key Highlights

### 🎯 **Unified Evaluation Standard**
- Establishes a **standardized benchmark** for fair comparison across MSA models
- Eliminates inconsistencies in evaluation protocols

### 🏷️ **Simple Label System**
- Adopts the widely used 7-class classification system (as described in [arxiv.org/abs/2205.14700](https://arxiv.org/abs/2205.14700)
)
- Preserves **pre-chorus** segments for enhanced granularity
- Easy conversion to 7-class (pre-chorus → verse) for compatibility

### 👨‍🔬 **Expert-Verified Quality**
- Multi-source validation
- Manual corrections by expert annotators

### 🌏 **Multilingual Coverage**
- **First Chinese MSA dataset** (100 songs)
- Bridges the gap in Chinese music structure analysis
- Enables cross-lingual MSA research

---

## 🚀 Getting Started

### Quick Load
```python
from datasets import load_dataset

# Load the complete benchmark
dataset = load_dataset("ASLP-lab/SongFormBench")
```

---

## 🤝 Citation

```bibtex
@misc{hao2026songformerscalingmusicstructure,
      title={SongFormer: Scaling Music Structure Analysis with Heterogeneous Supervision}, 
      author={Chunbo Hao and Ruibin Yuan and Jixun Yao and Qixin Deng and Xinyi Bai and Yanbo Wang and Wei Xue and Lei Xie},
      year={2026},
      eprint={2510.02797},
      archivePrefix={arXiv},
      primaryClass={eess.AS},
      url={https://arxiv.org/abs/2510.02797}, 
}
```

---

## 🎼 Mel Spectrogram Details

<details>
  <summary>Click to expand/collapse</summary>

Environment configuration can refer to the official implementation of BigVGan. If the audio source becomes invalid, you can reconstruct the audio using the following method.

### 🎸 SongFormBench-HarmonixSet
Uses official HarmonixSet mel spectrograms. To reproduce:

```bash
# Clone BigVGAN repository
git clone https://github.com/NVIDIA/BigVGAN.git

# Navigate to utils
cd utils/HarmonixSet

# Update BIGVGAN_REPO_DIR in inference_e2e.sh
# Run the inference script
bash inference_e2e.sh
```

### 🎤 SongFormBench-CN  
Reproduce using [**bigvgan_v2_44khz_128band_256x**](https://huggingface.co/nvidia/bigvgan_v2_44khz_128band_256x)

You should first download bigvgan_v2_44khz_128band_256x, then add its project directory to your PYTHONPATH, after which you can use the code below:

```python
# See implementation
utils/CN/infer.py
```
</details>

---

## 📧 Contact

For questions, issues, or collaboration opportunities, please visit our [GitHub repository](https://github.com/ASLP-lab/SongFormer) or open an issue.