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Comment by Torn | Hacker News Reader

Yeah, listening closely you can see how it gets "55" from his "bye bye". The strong accent makes it quite hard for the software to guess the phonemes being spoken.

You can't have a "one size fits all" approach in voice recognition if there are people pronouncing exactly the same words in completely different ways.

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I don’t see why you can’t have "one size fits all" recognition. It just requires more advanced profiling. The computer has to be smart enough to use all the words leading up to that one hard to recognize word. Not to mention other cues like grammar check (which would have revealed a lot of what went wrong in the example the author uses)

I’m not saying it’s easy. In fact, I’d be willing to bet money that I personally don’t have the programming chops to do it effectively. But I know enough to know it can be done.

Thinking about the United States and the variety of cultures / accents (mexican, chinese, etc.) I guess errors will happen very often.

This brings up an interesting problem with the future coding of Google Voice. How is it suppose to determine whether it's someone with an accent saying bye bye or someone without an accent saying 55. Even if the dielects are taken into consideration, that is still going to be quite a difficult problem!

Context. You could compute the log likelihood ratio of "bye bye" given the previous word versus the log likelihood ratio of "55" given the previous word. If that's not good enough you can generalize this to use the previous N words.

Google should have a large enough corpus of text at it's disposal to be able to approach the problem this way, and they very well may already be doing so.

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