Google Translate is an amazing tool but
it also kind of sucks it's a service that's come a long way over the last 18
years but it's still nowhere near the perfect Universal translator we're used
to seeing in science fiction like Star Trek and hitchhiker Guide to the Galaxy
but how far away from that kind of seamless translation technology are we
really Google Translate is an example of machine translation a subfield of
computational linguistics that has been under development since the 1950s early
machine translators used a rule-based approach which required programmers to
explicitly describe every rule governing a language which was both labor
intensive and flawed in the 1980s
statistical translation models became popular these used probability and
heuristics to determine the best translation for a given phrase which was
more efficient but they struggled to translate between languages with
significant differences in terms of grammar and word order JM is a pretty
normal French phrase but its word order isn't I love you it's
I you love this is one of the reasons
why even relatively fast real-time interpretation programs always come with
a significant delay the software needs to hear the full sentence before it
knows how it's supposed to order the words in its translation when it
launched in 2006 Google translate originally used a statistical
translation model and typically translated Languages by converting them
to English then converting them into into the desired target language in late
2016 Google transitioned its translation service to neural machine translation
which uses a neural network to translate phrases and passages holistically
meaning that it can use the larger text as context when translating specific
phrases Google Translate in particular excels because it's so widely used and
has a massive flow of user feedback to help refine its output that being said
experts do not consider any translation programs today to be capable of fully
automated high quality translation as the technology is still too unreliable
for formal purposes like translating works for publication or interpreting a
witness statement during a court hearing however professional translators do use
a fair number of automated Tools in what is called computer assisted translation
their cyborgs to be fair accurate enough for a court hearing is a pretty high bar
so how accurate is Google Translate really well it can vary a lot depending
on the language pairing if you're a unilingual English speaker Google
translate might actually seem to work really really well that's because
English has the most speakers out of any human language with almost 1.5 billion
and half of websites are written in English Google translate has tons of
English language reference material to draw from but the majority of the other
132 languages supported by Google translate are only represented by a
small fraction of users and websites according to a 2019 UCLA study English
to Spanish was around 94% accurate but English to Armenian was only 55%
accurate but isn't this accuracy Gap just going to go away with
time well yes and no this technology will inevitably become more accurate as
time goes on but there are several deeper problems with machine translation
that we have yet to really solve we'll tell you what they are after this
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your busted laptop a new lease on life it's tempting to think that the route to
a universal translator is just more data
and that would definitely help in arm media case but even with our extremely
sophisticated neural network and plenty of training data machine translators
tend to struggle in a few key areas of human communication most notably slang
jokes and figurative language a lot of human communication relies on
abstraction and double meanings especially metaphors and idioms the
French phrase okam twam I'm sorry is a
Whimsical idiom typically used to describe the height of young children
the rough English equivalent is knee high to a grasshopper but if you
translate it literally it means three apples High Google translate interprets
this French phrase as little person which is sort of right but also very
very wrong similarly the humor of it
ain't rocket surgery just isn't going to translate well without a human being
willing to put in the groundwork to find a suitable cultural equivalent because
French people don't use rocket science or brain surgery as benchmarks for
difficulty they use sourc now this isn't an impossible hurdle for
a machine translator to handle because idioms tend to be said the exact same
way every time you could teach the software how to translate a long list of
specific idioms so long as you are willing to put enough resources into it
teaching it to consistently translate word play and jokes however might very
well be impossible sing is always a real headache for translators both machine
and human because it's typically used by relatively small Niche subcultures and
it's unlikely to wind up in Main language repositories like dictionaries
and thorth slang also tends to change
quickly and rely on community specific cultural references if you were to try
and translate a slang heavy Kendrick Lamar song by pushing it through a
machine translator the result would not be just aesthetically questionable but
also basically incoherent to a person unfamiliar with American rap culture
helping a machine translator to understand slang is again possible it
would just be a bit expensive and require near constant updating where
things get tricky is that there's a slight difference between a translation
being accurate and a translation being good especially when it comes to Art
machine translation can often be technically correct but still fail to
communicate the tone and cultural connotations of the original on a purely
technical level how are you what's up and how's it hanging all mean basically
the same thing but one is a double on Tandra and a weird thing to say to your
grandma we might be happy enough with a machine translation of a menu if it just
accurately communicates what food is available but a translated novel or poem
needs to find a good balance between accuracy and Aesthetics in order to
create a similar experience as the original this means that a literary
translator needs to be creative and make astute artistic judgments in the same
way that an author does the basic problem with translation software is
that there's no mind behind it that truly understands the purpose or intent
of the words its processing an optimistic goal of machine translation
as a discipline is to one day have translation software that is so
sophisticated and nuanced that it only needs a human Editor to check its work
and fix whatever errors they find more pessimistically highquality fully
Automated machine translation might require the development of something
like AGI artificial general intelligence
a machine capable of human-like intelligence and making Nuance judgment
calls so Google translate might need to
be capable of forming opinions before
it's ready to translate poetry thanks for watching guys if you like this video
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