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The Babel Fish Swims Closer to Reality
Posted by Donald A. DePalma on May 25, 2016  in the following blogs: Translation and Localization, Technology
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Today we celebrate The Hitchhiker's Guide to the Galaxy (H2G2, for short), the Douglas Adams novel that created the most enduring model for machine translation, the babel fish. May 25th is Towel Day, a commemoration of Arthur Dent's unplanned and sudden exodus from Earth, first described in a 1978 BBC radio series.

On that day, Ford Prefect, alien visitor from planet Betelgeuese, tells Dent to grab a towel, "the most massively useful thing an interstellar hitchhiker can carry." Then both he and Dent consume three pints of beer and packets of salted nuts to prepare for a journey that begins with their transport via a matter transference beam to a Vogon Constructor Fleet spaceship just before it destroyed Earth. In short order, Dent is given a babel fish to put in his ear. This leechlike creature allowed him to to understand instantly anything spoken in any language, anytime, anywhere on his journey around the galaxy.

That requirement of instantaneous, ubiquitous translation has driven the machine translation sector since its inception. The first MT solutions required massive time-sharing mainframes, so they missed on both axes of instant and ubiquitous. Today, software with APIs to cloud-based arrays of servers on demand produce really fast output and can power a wide variety of devices and apps. 

This week announcements of a Skype SDK to integrate messaging into any application promises more work along the lines of Skype Translator, while an in-ear device slated for 2017 mimics Douglas Adams' own babel fish. If you can't wait for the actual working device, you could always try the candy version

And if you'd like to find out more about MT usage, see our survey-based research on MT's journey to the enterprise and the calculus of global content. In our mathematical deconstruction of the Earth-bound digital universe, we found that the challenges of growing content volumes, shrinking turnaround times, burgeoning number of target languages, and flat budgets severely limit the capacity of human translation. Our demand-side primary research shows that the mechanical babel fish – on computers or in your ear – will be a major component in removing language as a barrier to communication.

 

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The Business Case for Machine Translation
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