I recently built a real-time noise suppression engine by combining classical DSP techniques in C++ with a PyTorch neural network. It’s amazing to see how these two technologies can come together to create something truly powerful.
The idea of using machine learning to improve noise cancellation is not new, but implementing it in real-time is a significant challenge. By leveraging the strengths of both C++ and PyTorch, I was able to create an engine that can suppress noise in real-time, making it possible to use in a variety of applications.
What I find particularly interesting is the potential for this technology to be used in areas like audio conferencing, voice assistants, and even hearing aids. The ability to suppress background noise in real-time could greatly improve the quality of these applications.
If you’re interested in learning more, I’ve open-sourced the project on GitHub. I’d love to hear your thoughts and feedback on this project.
How do you think this technology could be used to improve our daily lives?