--- 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 ---

JAM: A Tiny Flow-based Song Generator with Fine-grained Controllability and Aesthetic Alignment


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# 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/ ├── README.md # This file ├── metadata.jsonl # Complete metadata for all tracks ├── spotify_urls.txt # Plain text list of Spotify URLs ├── transcriptions/ # JSON transcription files │ ├── Artist - Title.json │ └── ... └── struct/ # JSON structure analysis files ├── Artist - Title.json └── ... ``` ## 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 × ~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: - 📧 Open an issue on the [Project Jamify GitHub](https://github.com/declare-lab/jamify) - 🔗 Visit the [DeCLaRe Lab website](https://declare-lab.github.io/jamify) - 📄 Refer to the [JAM paper](https://arxiv.org/abs/2507.20880) for technical details