# Voice Isolation AI — Project Idea

## Concept

Build a voice isolation / denoising web app using Meta's pretrained **Demucs** model, wrapped in a simple full-stack pipeline. No model training from scratch — focus on building the pipeline and a live demo.

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## Recommended Stack

| Layer | Tool |
|---|---|
| AI Model | Meta's Demucs (pretrained, open source) |
| Backend | Python + FastAPI |
| Frontend | Basic HTML/JS (file upload + audio playback) |
| Deployment | Hugging Face Spaces (free) |

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## Build Plan

| Step | What to do | Skill shown on CV |
|---|---|---|
| 1 | Install & run Demucs on audio files via Python | Python, audio processing |
| 2 | Build a FastAPI endpoint that accepts audio uploads | Backend API design |
| 3 | Simple frontend to upload audio & play cleaned result | Full-stack thinking |
| 4 | Deploy on Hugging Face Spaces | Deployment, MLOps basics |

**Realistic timeline:** 2–3 weeks of evenings.

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## Key Concepts

### WebRTC
Browser-native protocol for real-time audio/video streaming (used by Google Meet, Discord). Useful for a future real-time version of this project.

### ONNX Model
A format for exporting trained models (from PyTorch/TensorFlow) so they can run anywhere — browser, mobile, edge — without Python or a GPU server. Good for a future client-side version.

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## Why This Works for a Beginner ML Dev

- No math-heavy training required
- Engages with a real production-grade ML model
- End result is a **live, linkable demo** — more impressive than code alone
- Covers Python, APIs, basic frontend, and deployment in one project

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## Future Enhancements (after basics)

- Real-time processing via WebRTC + ONNX Runtime in the browser (fully client-side)
- Fine-tune Demucs on a specific domain (call centers, hearing aids)
- Add a React frontend for a polished UI

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*Created: 2026-05-01*