4 ms·

Oddly, I found the RNNoise suppression more distracting than the less sophisticated Speex suppressor. If you'll forgive the figurative language; compared with

Oddly, I found the RNNoise suppression more distracting than the less sophisticated Speex suppressor. If you'll forgive the figurative language; compared with the noisy tracks, speex de-emphasises the noise into a quieter but smoother robotic 'bokeh', which allowed me to concentrate on the main speakers. RNNoise on the other hand seemed to detect silences well, but left artifacts in the speech such that it had a choppy and artificial feel. Lacking the smoothness in the background I found I was more distracted by the distortions in the words.

dmpk2k 9y ago
The Speex suppressor is subjectively much nicer in all babble scenarios, but in some scenarios the RNN is better. E.g. it really excels at 20db car noise.
- Mithaldu 9y ago
  Personally i prefer speex even for car noise, as the rnn adds clicks and scratches that annoy me a lot more than more frequent soft distortions.
zimpenfish 9y ago
> a choppy and artificial feel. To me it sounds like the kind of flange-y wafty MP3 glitches you used to get. At 0dB on the babble sample, it's painful to listen to whilst Speex is perfectly fine. For me, Speex wins on all samples.
- croon 9y ago
  I didn't do any technical analysis, but to me RNN sounded as if they had just cut all noise between the narrators speech, and played all sound during their words, giving you a sharp amplitude difference and "stabbing" sensation. At least that's my take on why Speex is subjectively more pleasant, with which I agree.
  - zimpenfish 9y ago
    That's it, yeah, a kind of gated ramp effect at the beginning and end of words.
    - baldfat 9y ago
      That means if they had access to the gate we can change that to our taste. Hope that is an option in the function.
  - rhizome 9y ago
    Sounds like the difference between (e.g. soft-knee) compression and a noise gate.
ZeroGravitas 9y ago
I didn't notice any issue with RNN at the lower levels of background noise, but as the background got noisier, I too heard what sounded like speaker distortion which seemed more distracting than the background noise. I was slightly confused by the text that claimed that it was expected for the intelligibility to go down though, so maybe that's all working as intended.
jmvalin 9y ago
Interesting -- and unexpected. I also wrote the Speex suppressor and one of the things that specifically annoyed me about it was the robotic noise and the pseudo-reverberation it adds to the speech, but it seems like some people (like you) like that. Trying to understand exactly what you don't like about RNNoise... is it how the remaining background noise sounds or how sharply it turns on/off? I did a quick hack to RNNoise to smooth out the attenuation and prevent it from cancelling more than 30 dB. I'd be curious if it improves or makes things worse for you (compared to the samples in the demo): https://jmvalin.ca/misc_stuff/rnn_hack1/ https://jmvalin.ca/misc_stuff/rnn_hack1/
- mrob 9y ago
  I also much prefer the Speex version. The robotic noise is consistent and easy to ignore. The NN version has a "choppy" feel to it that catches my attention. It reminds me of H264 vs VP9 video codecs at the same bitrate. VP9 is supposed to be better, but H264 artifacts are more artificial looking. VP9 artifacts look more natural, almost like mold/decay on film, which I find more distracting. I prefer your hacked RNNoise version to the original, but I still prefer the Speex version. Robotic is predictable, and predictable is good. I don't want denoising artifacts to feel like there's some intelligent agent behind them, just as I don't want any software tool to feel intelligent. The smarter the tool the more jarring it is when it misreads my intentions. It might help average performance but it harms worst-case performance, and worst-case performance is subjectively more important because humans pay attention to outliers.
- mtrimpe 9y ago
  Subjectively it seems to me that the RNNoise sample doesn't trigger my brain to attempt to fill in the gaps. With the Speex/raw ones I have all the data so if I listen to it again over and over I can get more out of it eventually. With the RNNoise one I obviously don't even have enough extra data to even try doing that so all I can do is blame the algorithm. Perhaps what you really want is an algorithm that lets through a bit more of the 'possible noise' for the human brain to have another go at.
  - jmvalin 9y ago

dmpk2k 9y ago

The Speex suppressor is subjectively much nicer in all babble scenarios, but in some scenarios the RNN is better. E.g. it really excels at 20db car noise.

Mithaldu 9y ago
Personally i prefer speex even for car noise, as the rnn adds clicks and scratches that annoy me a lot more than more frequent soft distortions.

zimpenfish 9y ago

> a choppy and artificial feel. To me it sounds like the kind of flange-y wafty MP3 glitches you used to get. At 0dB on the babble sample, it's painful to listen to whilst Speex is perfectly fine. For me, Speex wins on all samples.

croon 9y ago
I didn't do any technical analysis, but to me RNN sounded as if they had just cut all noise between the narrators speech, and played all sound during their words, giving you a sharp amplitude difference and "stabbing" sensation. At least that's my take on why Speex is subjectively more pleasant, with which I agree.
- zimpenfish 9y ago
  That's it, yeah, a kind of gated ramp effect at the beginning and end of words.
  - baldfat 9y ago
    That means if they had access to the gate we can change that to our taste. Hope that is an option in the function.
- rhizome 9y ago
  Sounds like the difference between (e.g. soft-knee) compression and a noise gate.

ZeroGravitas 9y ago

I didn't notice any issue with RNN at the lower levels of background noise, but as the background got noisier, I too heard what sounded like speaker distortion which seemed more distracting than the background noise. I was slightly confused by the text that claimed that it was expected for the intelligibility to go down though, so maybe that's all working as intended.

jmvalin 9y ago

Interesting -- and unexpected. I also wrote the Speex suppressor and one of the things that specifically annoyed me about it was the robotic noise and the pseudo-reverberation it adds to the speech, but it seems like some people (like you) like that. Trying to understand exactly what you don't like about RNNoise... is it how the remaining background noise sounds or how sharply it turns on/off? I did a quick hack to RNNoise to smooth out the attenuation and prevent it from cancelling more than 30 dB. I'd be curious if it improves or makes things worse for you (compared to the samples in the demo): https://jmvalin.ca/misc_stuff/rnn_hack1/ https://jmvalin.ca/misc_stuff/rnn_hack1/

mrob 9y ago
I also much prefer the Speex version. The robotic noise is consistent and easy to ignore. The NN version has a "choppy" feel to it that catches my attention. It reminds me of H264 vs VP9 video codecs at the same bitrate. VP9 is supposed to be better, but H264 artifacts are more artificial looking. VP9 artifacts look more natural, almost like mold/decay on film, which I find more distracting. I prefer your hacked RNNoise version to the original, but I still prefer the Speex version. Robotic is predictable, and predictable is good. I don't want denoising artifacts to feel like there's some intelligent agent behind them, just as I don't want any software tool to feel intelligent. The smarter the tool the more jarring it is when it misreads my intentions. It might help average performance but it harms worst-case performance, and worst-case performance is subjectively more important because humans pay attention to outliers.
mtrimpe 9y ago
Subjectively it seems to me that the RNNoise sample doesn't trigger my brain to attempt to fill in the gaps. With the Speex/raw ones I have all the data so if I listen to it again over and over I can get more out of it eventually. With the RNNoise one I obviously don't even have enough extra data to even try doing that so all I can do is blame the algorithm. Perhaps what you really want is an algorithm that lets through a bit more of the 'possible noise' for the human brain to have another go at.
- jmvalin 9y ago