4 ms·
What is your current approach if you can answer? Some kind of spatial beamforming or you must use a given recorded measurement and decompose by frequency conten
by JorgeGT 10y ago
What is your current approach if you can answer? Some kind of spatial beamforming or you must use a given recorded measurement and decompose by frequency content as best as you can?
I guess this kind of machine learning that not uses total frequency spectrum but the time-domain evolution of short-time Fourier transforms (as in the spectrogram he is painting over in the demo) has a lot of potential for acoustic source separation. For instance training the machine to recognize the particular time-frequency signature of human voice and automatically filter it from a song.
- Anechoic 10y agoMicrophone array (beamforming) or sound intensity. But since those approaches typically require expensive hardware, the current approach is basically "we don't" unless the frequency characteristics are clearly distinct and we can use traditional equalization processes. Machine learning has potential (and a lot of people have tried) but it's only as good at it's training.