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pretty_name: SongFormBench |
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tags: |
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- MSA |
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- Benchmark |
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license: cc-by-4.0 |
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language: |
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- en |
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- zh |
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--- |
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# SongFormBench π |
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[English ο½ [δΈζ](README_ZH.md)] |
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**A High-Quality Benchmark for Music Structure Analysis** |
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[](https://huggingface.co/datasets/ASLP-lab/SongFormBench) |
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[](https://huggingface.co/ASLP-lab/SongFormer) |
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[](https://github.com/ASLP-lab/SongFormer) |
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[]() |
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--- |
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## π What is SongFormBench? |
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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. |
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### π Dataset Composition |
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- **πΈ SongFormBench-HarmonixSet (BHX)**: 200 songs from HarmonixSet |
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- **π€ SongFormBench-CN (BC)**: 100 Chinese popular songs |
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**Total: 300 high-quality annotated songs** |
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--- |
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## β¨ Key Highlights |
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### π― **Unified Evaluation Standard** |
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- Establishes a **standardized benchmark** for fair comparison across MSA models |
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- Eliminates inconsistencies in evaluation protocols |
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### π·οΈ **Simple Label System** |
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- Adopts the widely used 7-class classification system (as described in [arxiv.org/abs/2205.14700](https://arxiv.org/abs/2205.14700) |
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) |
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- Preserves **pre-chorus** segments for enhanced granularity |
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- Easy conversion to 7-class (pre-chorus β verse) for compatibility |
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### π¨βπ¬ **Expert-Verified Quality** |
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- Multi-source validation |
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- Manual corrections by expert annotators |
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### π **Multilingual Coverage** |
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- **First Chinese MSA dataset** (100 songs) |
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- Bridges the gap in Chinese music structure analysis |
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- Enables cross-lingual MSA research |
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--- |
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## π Getting Started |
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### Quick Load |
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```python |
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from datasets import load_dataset |
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# Load the complete benchmark |
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dataset = load_dataset("ASLP-lab/SongFormBench") |
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``` |
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--- |
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## π Resources & Links |
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- π Paper: *coming soon* |
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- π» Code: [GitHub Repository](https://github.com/ASLP-lab/SongFormer) |
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- π§βπ» Model: [SongFormer](https://huggingface.co/ASLP-lab/SongFormer) |
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- π Dataset: [SongFormDB](https://huggingface.co/datasets/ASLP-lab/SongFormDB) |
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--- |
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## π€ Citation |
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comming soon. |
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--- |
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## πΌ Mel Spectrogram Details |
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<details> |
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<summary>Click to expand/collapse</summary> |
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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. |
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### πΈ SongFormBench-HarmonixSet |
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Uses official HarmonixSet mel spectrograms. To reproduce: |
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```bash |
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# Clone BigVGAN repository |
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git clone https://github.com/NVIDIA/BigVGAN.git |
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# Navigate to utils |
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cd utils/HarmonixSet |
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# Update BIGVGAN_REPO_DIR in inference_e2e.sh |
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# Run the inference script |
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bash inference_e2e.sh |
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``` |
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### π€ SongFormBench-CN |
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Reproduce using [**bigvgan_v2_44khz_128band_256x**](https://huggingface.co/nvidia/bigvgan_v2_44khz_128band_256x) |
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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: |
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```python |
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# See implementation |
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utils/CN/infer.py |
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``` |
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</details> |
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--- |
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## π§ Contact |
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For questions, issues, or collaboration opportunities, please visit our [GitHub repository](https://github.com/ASLP-lab/SongFormer) or open an issue. |
