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Futuregazing translationRoberto Silva, April 2015
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How translators used to work in the past?
Antonio da Fabriano II: St. Jerome in study (The Walters Art Museum).
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How translators used to work in the past?
Source: http://www.ucg.org/vertical-thought/types-of-bible-translations
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How translators used to work in the past?
Source: Champollion’s Description of the Ptolemy and Cleopatra Cartouche. http://traveltoeat.com/the-rosetta-stone-british-museum-london/
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How translators work today?
Local Terminology search (dictionaries, glossaries)
Online Terminology search (databases, translation resources)
Reference documents
Online collaborative translation
Project management, including quoting and invoicing
Online and offline research
CAT tools, including translation memory
Machine translation
Dictation
Training
Solve issues (file format, DTP, etc.)
Certifications
Marketing, social networking
Source: Google image search
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Is it enough?
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Why?
Source: DOMO (http://www.domo.com/blog/2014/04/data-never-sleeps-2-0/, data compiled from many original sources)
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Present efforts
Cloud based collaborative translation, sharing
translation and terminology
Authoring + Translation + Revision in parallel
Learning from other industries and cooperating with
them
Working together customers, agencies, translators,
researchers, developers
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Present efforts
Technology convergence: touch translation + voice
recognition + eye tracking + AI driven big data analysis
Deep learning (machine learning from data)
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Disruptive technologies
Mobile computing
Wearables (smart bands, watches, glasses, clothing, furniture)
Roll-up digital screens (Source-Gated-Transistor based or similar) and graphene-based apps
Body embedded nanotechnology
Universal translator as a goal for helping humans
Permanent connectivity
Source: Own research
3D aware devices will create new services
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Disruptive trends
Kids are 100% digital. They will drive the new generation of products and will expect them to be fully and instantly multilingual.
Security will require complex interaction between human translators and computers
As companies become more and more global, shareholders and decision makers will require translation of all kind of materials at a much faster rate
On demand services and applications will require new translation services, included online help
Webrooming will become more common than showrooming. Millennials prefer it.
Younger generations use privacy to exchange. Traditional view on privacy is gone.
Open source in translation
Source: Own research
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Why translators won’t be
replaced (soon)
Disfluency (the difference between how people write and talk) makes voice recognition very difficult
Humans understand a concept that does not have direct translation or does not exist in another language. Computers don’t.
Mixing speech recognition, machine translation and human translation today is not achievable
Skype translator and Microsoft Translator are not good enough
Persuasive technology needs human translation
Virtual reality will require demanding translation and interpreting services
Source: Own research
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The future?
Translation (text/voice) embedded in every device
Multimodal (including Brain to computer interaction),
multidevice, multisource translation input
Automatic translation of adapted content based on
human profile recognition
Real time high quality cross language information
retrieval
Real-time on demand translation
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Google Word lens
Source: https://plus.google.com/explore/wordlens
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Deep learning
Source: Own research
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Deep learning
Source: Own research
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Deep learning
Source: LEVAN project, http://levan.cs.washington.edu/
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Deep learning
Source: Google research blog, http://googleresearch.blogspot.co.uk/2014/11/a-picture-is-worth-thousand-coherent.html
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Deep learning
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Deep learning
Source: Microsoft Image Recognition research
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Deep learning
Source: http://www.freegreatpicture.com/kitty/cat-and-goldfish-3062
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Deep learning
Real time examples:
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Roberto Silva
roberto.silva@conversis.com
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