The Ingoose Project represents a paradigm shift in the realm of audio technology and its seamless integration into our daily devices. At its core, this project has meticulously crafted models that have undergone rigorous training, calibration, and validation phases. These models, embodying the culmination of cutting-edge research and innovation, have been adeptly deployed into chipsets designed specifically for mobile devices and microphones.
What sets the Ingoose Project apart is its dedication to preserving the innate and unique characteristics of pre-recorded singers. The technology does not just reproduce audio; it brings it to life. By ensuring that real-time audio output mirrors the tonal quality, timbre, and nuances of original recordings, the project enhances the auditory experience, making it richer, more profound, and immersive. This is not just an upgrade to existing audio technologies but a revolutionary step that redefines how we experience sound on our devices.
Follow these steps for a seamless setup:
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Prerequisites 📋:
- Python >= 3.10
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Frameworks 🔧:
- Install PyTorch (tested with
torch.__version__=='2.0.1',torchaudio.__version__=='2.0.2', andtorchvision.__version__=='0.15.2')
- Install PyTorch (tested with
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Dependencies 📦:
python -m pip install cython
Project Setup ⚙️:
bash Copy code python -m pip install -e . Development Tools 🛠️:
bash Copy code python -m pip install pre-commit && pre-commit install 📖 Examples Dive into examples to see igoose in action!
📜 License License
This project is licensed under the MIT License - see the LICENSE file for details.
🌟 Star the repo if you found it useful! Feedback and contributions are always welcome! 🙌