so when I was a kid having a conversation with your computer went a little something like this you would lie
down on the couch and vent about all the problems in your life or whatever then
you'd have to get up type your own response press enter and listen back to
the insights that it had to offer pathetic right fast forward 25
years and voice recognition a technology
kind of like VR where someone is always claiming that they've made a big
breakthrough and it turns out to be kind of crap is finally gaining widespread
adoption so early forms of voice recognition had very limited
vocabularies some of the first systems from the 1950s could only recognize
about 10 words and even about 30 years
later that number had grown to only around 20,000 which may seem like a lot
but remember that the English language has over 1 million words on top of that
early software couldn't predict what words you were trying to say by using
context so to these programs it was just
as likely that you were trying to say bacon and legs as bacon and eggs
fortunately though we finally got computers in the late 1980s and early
1990s that had more storage and processing power allowing them to
comprehend more natural speech instead of forcing you to talk like this so they
could understand and nowadays Technologies like Siri and Cortana don't
rely on a limited dictionary or the relatively weak processor in your device
at all instead they use huge Cloud
databases that store millions of words and phrases and have lightning fast CPUs
to understand what you mean with much more Precision Google speech recognition
software even learns from real search engine strings and can also recognize a
variety of accents so you can use it whether you're from Eastern Canada or
Southern Texas but can the power of the cloud do more when you ask your phone
for a sports score how does it know to
tell you how your favorite team is doing instead of where to find a spor store
well instead of listening to just one word at a time and I alluded to this
before it listens to other words as well
for context and uses probabilities to determine what you're trying to say this
is a pretty involved process that uses complex mathematical models Google for
example uses an artificial neural network that functions similarly to your
own brain using dig neurons to learn what people are saying
and you can actually see this in action as Google Now often changes what it
thinks you said on the fly as you continue speaking and it gets better
greater amounts of processing power have enabled everything from realtime
translation to being able to talk to game characters with a VR headset to
emotion tracking in which a computer can use the timing and pitch of your voice
to figure out how you're feeling we're even seeing it deployed in fighter
aircraft so Pilots can concentrate on mission objectives instead of fiddling
with cockpit switches but although voice recognition has come a really long way
its proliferation has presented us with some new challenges one big concern has
been finding ways to filter out background noise so you'll still get
correct results even if you're standing in the middle of a busy street and
speaking of standing in public another massive issue is privacy many types of
voice recognition software imp improve upon themselves by learning user habits
and combined with Cloud processing we've already seen some real concerns such as
with Samsung Smart TVs earlier this year
which had a privacy policy which some people believed allowed Samsung to
monitor your living room conversations so while the tech has
great potential we also need to make sure it won't leave us all feeling like
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