[djsamseng]

Agreed theoretically however if I gave you two spectrograms, would you be able to tell which one is clear speech and which one is garbled? I’d bet we’d be able to come up with one that wouldn’t pass the sniff test.

If you know of any implementations that can look at a spectrogram and say “hey there’s peaks at 150hz, 220hz and 300hz with standard deviations of 5hz, 7hz, and 10hz, decreasing in frequency over time thus this is a deep voice saying ‘ay’” and get it right every time I’d be really interested in seeing it (besides neural networks)

[HarHarVeryFunny]

Maybe an expert linguist (not me) could do a pretty good job of distinguishing noisy speech in most cases, but a neural net should certainly be able to be super-human as this.

Some sources of noise like the constant background hum (e.g. computer fan) are easy to spot though.