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---
language:
- en
library_name: diffusers
metrics:
- PER
- WER
- SongEval
- Audio Aesthetics
- MuQ
- FAD
pipeline_tag: text-to-audio
tags:
- music
- art
- song-generation
- lyrics-to-song
- flow-matching
- direct-preference-optimization
license: other
---
<div align="center">
<img src="https://declare-lab.github.io/jamify-logo-new.png" width="200"/ >
<br/>
<h1>JAM: A Tiny Flow-based Song Generator with Fine-grained Controllability and Aesthetic Alignment</h1>
<br/>
[](https://arxiv.org/abs/2507.20880) [](https://huggingface.co/declare-lab/JAM-0.5) [](https://huggingface.co/datasets/declare-lab/JAME) [](https://huggingface.co/spaces/declare-lab/JAM) [](https://github.com/declare-lab/jamify) [](https://declare-lab.github.io/jamify)
</div>
# JAME Dataset
**JAME** (JAM Evaluation) is a comprehensive music dataset containing 250 high-quality music tracks designed for **standardized evaluation of song generation models**.
This dataset is part of **Project Jamify** developed by [DeCLaRe Lab](https://github.com/declare-lab/jamify/tree/main) and supports research in controllable music generation.
## Dataset Overview
- **Total Tracks**: 250 carefully curated tracks (50 per genre, 5 genres total)
- **Duration**: Approximately 230 seconds per track
- **Genres**: Hip-Hop/Rap, Rock/Metal, Electronic/Dance, R&B/Soul/Jazz, Country/Folk
- **Release Time**: select tracks released after 1st May 2025 to avoid data contaimination.
- **Purpose**: Standardized evaluation benchmark for song generation models
## Dataset Structure
```
jame/
βββ README.md # This file
βββ metadata.jsonl # Complete metadata for all tracks
βββ spotify_urls.txt # Plain text list of Spotify URLs
βββ transcriptions/ # JSON transcription files
β βββ Artist - Title.json
β βββ ...
βββ struct/ # JSON structure analysis files
βββ Artist - Title.json
βββ ...
```
## Audio Access
Audio files are not directly provided in this dataset. Users can legally access the audio through:
- **Spotify**: Using the provided `spotify_url` links
- **YouTube Music**: Using the provided `youtube_url` links
- **Legal Streaming Services**: Search by artist and title information
Please ensure compliance with terms of service and copyright laws when accessing audio content.
## Metadata Format
Each line in `metadata.jsonl` contains a JSON object with the following fields:
```json
{
"file_name": "Artist - Title",
"artist": "Artist Name",
"title": "Song Title",
"spotify_url": "https://open.spotify.com/track/...",
"youtube_url": "https://music.youtube.com/watch?v=...",
"duration": 180,
"year": 2025,
"genre": "Hip-Hop/Rap",
"transcription_path": "transcriptions/Artist - Title.json",
"struct_path": "struct/Artist - Title.json",
"song_id": "spotify_track_id"
}
```
### Field Descriptions
- **file_name**: Base filename without extension
- **artist**: Primary artist name
- **title**: Song title
- **spotify_url**: Official Spotify track URL
- **youtube_url**: YouTube Music URL
- **duration**: Track duration in seconds
- **year**: Release year
- **genre**: Music genre category
- **transcription_path**: Path to transcription JSON file
- **struct_path**: Path to structure analysis JSON file
- **song_id**: Spotify track identifier
## Genre Distribution
The dataset contains 250 tracks evenly distributed across 5 genres (50 tracks per genre):
- **Hip-Hop/Rap** (50 tracks): Urban and rap music
- **Rock/Metal** (50 tracks): Rock, alternative, and metal tracks
- **Electronic/Dance** (50 tracks): Electronic, EDM, and dance music
- **R&B/Soul/Jazz** (50 tracks): R&B, soul, and jazz-influenced tracks
- **Country/Folk** (50 tracks): Country, folk, and acoustic music
## File Formats
- **Metadata**: JSONL (JSON Lines) format with complete track information
- **Transcriptions**: JSON format with detailed transcription data
- **Structure**: JSON format with musical structure annotations
- **URLs**: Plain text file with Spotify URLs for easy access
## License and Attribution
Please ensure proper attribution when using this dataset. Check individual track licenses through their respective Spotify and YouTube Music pages.
## Dataset Statistics
- **Total Duration**: ~15.3 hours (250 tracks Γ ~230 seconds)
- **Completeness**: 100% metadata coverage for all 250 tracks
- **Quality**: High-quality metadata with detailed annotations
- **Coverage**: Complete Spotify and YouTube URL mapping
## Citation
If you use the JAME dataset in your research, please cite:
```bibtex
@misc{liu2025jamtinyflowbasedsong,
title={JAM: A Tiny Flow-based Song Generator with Fine-grained Controllability and Aesthetic Alignment},
author={Renhang Liu and Chia-Yu Hung and Navonil Majumder and Taylor Gautreaux and Amir Ali Bagherzadeh and Chuan Li and Dorien Herremans and Soujanya Poria},
year={2025},
eprint={2507.20880},
archivePrefix={arXiv},
primaryClass={cs.SD},
url={https://arxiv.org/abs/2507.20880},
}
```
## License and Attribution
This dataset is released under **Project Jamify License** for **non-commercial, academic, and entertainment purposes only**.
### Key Restrictions:
- **No copyrighted material** was used in a way that would intentionally infringe on intellectual property rights
- **Commercial use strictly prohibited**
- **Attribution required**: Must cite the JAM paper and maintain license notices
- Users must ensure compliance with applicable legal and ethical standards
For complete license terms, see the [Project Jamify repository](https://github.com/declare-lab/jamify).
## Contact
For questions about this dataset:
- π§ Open an issue on the [Project Jamify GitHub](https://github.com/declare-lab/jamify)
- π Visit the [DeCLaRe Lab website](https://declare-lab.github.io/jamify)
- π Refer to the [JAM paper](https://arxiv.org/abs/2507.20880) for technical details |