It's interesting that the article said human recognition is up to 98%. We're not perfect. So perhaps another tack is for the computer to correct mistakes in a more natural way. eg. by asking; by checking what the word makes sense in terms of subsequent context. BTW I didn't notice that "woods" was a speecho, but read it as "words".
I agree that linguists are sometimes too theory-focussed to notice the data. Pinker's excellent but self-consciously clever The Language Instinct has examples of nested phrases that he claims are understandable - but I can't parse them using my native speech recognition technology (I can parse them using linguistic theory):
The rapidity that the motion that the wing has has is remarkable. ["has" is repeated]
In other words: my native human grammar does not nest arbitrarily; the linguistic theory does. I'm going with the theory being wrong.
Anyway, as has been said, we'll have speech recognition when we have speed comprehension, ie strong AI.
I agree that linguists are sometimes too theory-focussed to notice the data. Pinker's excellent but self-consciously clever The Language Instinct has examples of nested phrases that he claims are understandable - but I can't parse them using my native speech recognition technology (I can parse them using linguistic theory):
The rapidity that the motion that the wing has has is remarkable. ["has" is repeated]
In other words: my native human grammar does not nest arbitrarily; the linguistic theory does. I'm going with the theory being wrong.
Anyway, as has been said, we'll have speech recognition when we have speed comprehension, ie strong AI.