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title: README
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MAAP LAB 🎵 — Music AI & Audio Research
“Why are there so few labs in Korea dedicated to Music AI? We built one.”
Focus areas:
🎼 Audio Generation · 🏷️ Music Tagging · 🗣️ Voice Conversion · 🧠 Transformers · 💨 Diffusion
Mission
Advance the foundations of Music AI through practical research in tagging, generation, and dataset-centric methods — then share our results openly with the community. ✨
Open Science
We aim to publish at top venues (e.g., ICASSP, ISMIR, AAAI) and release code, models, and datasets whenever possible. 📢
Latest News 🗞️
- ✅ NeurIPS Workshop 2025:
- Accepted 🎉 AIBA: Attention-based Instrument Band Alignment for Text-to-Audio Diffusion
- ✍️ ICASSP 2026 submission:
- Resubmitted and extended version of Jamendo-QA
- Preprint available on arXiv (2509.15662)
- 🧰 GPU resources via university support: NVIDIA A100, A6000, RTX 4090 ⚙️
Our Activities 🎯
Project 1 — Music Tagging (Completed) 🏷️
- Built a tagging & augmentation pipeline with CLAP, Beam Search, Stable Audio
- Focus: dataset augmentation/creation for future work
- Targets: short-term word generation → long-term sentence generation with LLMs
- Outcome: 2 NeurIPS Workshop submissions (1 accepted, 1 rejected → resubmitted to ICASSP)
AIBA — Accepted ✅ · Jamendo-QA — Arxiv 🔗
Project 2 — Efficient Music Generation (In Progress) 🎶
- Exploring Diffusion & DiT (e.g., Flux)
- LoRA/Adapters to avoid full fine-tuning
- Goal: robust generation for data-scarce genres/instruments/domains
- Roadmap: dataset curation → baseline reproduction → adapter experiments → ablations → release
Publications & Submissions 📚
- AIBA: Attention-based Instrument Band Alignment for Text-to-Audio Diffusion — Accepted at NeurIPS Workshop 2025
- Jamendo-QA: A Large-Scale Music Question Answering Dataset — Submitted to ICASSP 2026 · Preprint on arXiv
Get Involved 🤝
Interested in collaborating on Music AI? We welcome discussions on datasets, evaluation, and model design.
Contact: arsol970812@gmail.com ✉️
© 2025 MAAP LAB • Built with ❤️ for music & AI.