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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.”
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**Focus areas:**
🎼 Audio Generation · 🏷️ Music Tagging · 🗣️ Voice Conversion · 🧠 Transformers · 💨 Diffusion
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## 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. 📢
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## Latest News 🗞️
- ✅ **First project achieved!** Submitted **2 papers** to a **NeurIPS Workshop** based on our Music Tagging pipeline and dataset work.
<sub><em>Links to be added 🔗</em></sub>
- 🧰 GPU resources via university support: **NVIDIA A100**, **A6000**, **RTX 4090** ⚙️
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## 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** ✅
<sub>Links: _to be added_ 🔗</sub>
### 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
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## Publications & Submissions 📚
- NeurIPS Workshop Submission #1 — (TBD) ✍️
- NeurIPS Workshop Submission #2 — (TBD) ✍️
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## Get Involved 🤝
Interested in collaborating on **Music AI**? We welcome discussions on datasets, evaluation, and model design.
**Contact:** [email protected]_ ✉️
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<sub>© 2025 MAAP LAB • Built with ❤️ for music & AI.</sub> |