Not really... Even if the code is difficult to patch, speech/audio recognition doesn't advance much when an attacker figures out how to remove the (non-random) noise added by a machine over the sound file. Actual speech recognition relies on the ability to filter out background noise - which is a lot more complex/random - added by surroundings, not a machine.
It's very difficult to generate some sort of noise via algorithm that a) humans can filter out and b) can't be removed by some algorithm. As a result, audio captchas are a huge vulnerability and the weakest link in almost any captcha system, although you can't get rid of them by law.
Hypotheticals aside, the code was easy to patch - note the footnote:
> In the hours before our presentation/release, Google pushed a new version of reCAPTCHA which fully nerfs our attack.
Could one take real recorded noise and add that rather than noise generated via algorithm? Wouldn't that force attackers to solve a real problem (removing background noise from an speech sample)?
It's not really solving the "real" problem... If I'm just mashing two audio files together, that's going to be different than someone talking in the middle of a train platform and there will likely be algorithmicly-determinable difference from the artificially generated words and the naturally generated noise.
All of this aside, removing background noise is not a huge issue anymore. We have pretty decent noise-cancellation technology. Speech recognition - the other big component - has advanced a lot in recent times and is actually pretty good, although not for every company/product.
Even if it would be helpful, you'd have to record an incredible amount of noise in the first place, seeing as you're getting millions of hits a day and if you have a small sample set, the attackers will just figure out the solutions to that sample set and be done.
I'm not saying it's impossible, but I am saying it's probably not worth it at this point. Captchas (in their traditional forms) don't make sense as a long-term strategy anyways.
If the attacker manages to obtain all the random noise, they could index every window in the noise in a k-d-tree and perform an efficient nearest neighbour search for the exact background from the CAPTCHA audio, and then simply subtract the background, giving perfect segmentation in O(log(N)) asymptotic average time complexity for N windows (at 64kHz and 2000 hours of audio, N=460800000, log N = 19.95).
It's very difficult to generate some sort of noise via algorithm that a) humans can filter out and b) can't be removed by some algorithm. As a result, audio captchas are a huge vulnerability and the weakest link in almost any captcha system, although you can't get rid of them by law.
Hypotheticals aside, the code was easy to patch - note the footnote: > In the hours before our presentation/release, Google pushed a new version of reCAPTCHA which fully nerfs our attack.