There is a lot of cool research in separating sound sources in general. From friends in the industry, I know that the traditional approach taking advantage of p

There is a lot of cool research in separating sound sources in general. From friends in the industry, I know that the traditional approach taking advantage of phase difference between microphones is hard, because the of the small separation distance (within 1 hearing aid device and even when you have one in each ear). Conversely I haven't fully comprehended it yet, because I've similarly read that Google Android's beamforming microphone tech should be quite good: https://github.com/shichaog/WebRTC-audio-processing/tree/master/webrtc-audio-processing/webrtc/modules/audio_processing/beamformer https://github.com/shichaog/WebRTC-audio-processing/tree/mas... Here are some examples of new research with neural networks https://www.youtube.com/watch?v=FMEk8cHF-OA https://www.youtube.com/watch?v=FMEk8cHF-OA og https://www.youtube.com/watch?v=zL6ltnSKf9k https://www.youtube.com/watch?v=zL6ltnSKf9k