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Comment by abrookewood | Hacker News Reader

I thought the figures sound a little suspect too - if automated text-to-speech was really that bad, then presumably products like Dragon Dictate etc would never have been successful. Obviously they have the benefit of training, but still, 20% sounds ludicrously low.

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I think you need to take into consideration that this is designed to be used on voice where the speaker is not aware that they are speaking to a computer (or that they are being recorded at all).

When people talk to Siri, Cortana, or Dragon, they take unnatural care in the clarity of their speech compared to normal talk only meant for humans. Also the speaker may not have been speaking directly into a microphone, lots of background noise, etc.

All of these factors probably combine for a much lower accuracy than what Apple, Microsoft, and Google are going to be dealing with in usual cases. Also keep in mind they all have incentive to inflate their own products accuracy score. Not that the same incentive doesn't also exist for this company/product.

I had a friend working in speech recognition at Nuance for several years. I'm trying to remember what sort of accuracy he quoted to me about two years ago. It was something large like 80% or something and that getting the last stretch of accuracy was really hard with the techniques they employed back then. That figure may have been for a very specific application, which was a lot of phone menu stuff. He then moved on to Siri at Apple.

20% is very low. We use machine transcription at work, and although the per-word confidence of machine algorithms varies wildly given the quality of the audio and the speaker's mannerisms. It can easily get into the 80% range with good audio, especially televised audio where people are close to microphones and there is not a lot of non-speech noise.

Microsoft claims 93-94 percent correct, or in other words "6.3% word error rate"

http://www.zdnet.com/article/microsofts-newest-milestone-wor...

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