Frankly, what I hear is very similar to the results of classic spectral denoising, even with the characteristic FFT artifacts (for Linux, there's Noise Repellen

Frankly, what I hear is very similar to the results of classic spectral denoising, even with the characteristic FFT artifacts (for Linux, there's Noise Repellent [1] available for advanced spectral denoising; there's also a ton of commercial spectral processors available). The demonstration could use more random background noises to separate it from FFT noise suppressors (as it's the primary benefit of ML-based filters), and more varied speech to separate it from RNNoise [2] which tends to suppress breath and cut the sibilants in an unnatural manner. The latency is also important - is it as low as in RNNoise? What about the CPU load? [1] https://github.com/lucianodato/noise-repellent https://github.com/lucianodato/noise-repellent [2] https://github.com/werman/noise-suppression-for-voice https://github.com/werman/noise-suppression-for-voice