Voice and the uncanny valley of AI
Voice is a Big Deal in tech this year. Amazon has probably sold 10m Echos, you couldn’t move for Alexa partnerships at CES, Google has made its own and, it seems, this is the new platform. There are a couple of different causes for this explosion, and, also, a couple of problems. To begin, the causes.
First, voice is a big deal because voice input now works in a way that it did not until very recently. The advances in machine learning in the past couple of years mean (to simplify hugely) that computers are getting much better at recognizing what people are saying. Technically, there are two different fields here; voice recognition and natural language processing. Voice recognition is the transcribing of audio to text and natural language processing is taking that text and working out what command might be in it. Since 2012, error rates for these tasks have gone from perhaps a third to under 5%. In other words, this works, mostly, when in the past it didn’t. This isn’t perfect yet – with normal use a 5% error rate can be something you run into every day or two, and Twitter is full of people posting examples of voice assistants not understanding at all. But this is continuing to improve – we know how to do this now.
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