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Translation 101:
Industry overview
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Looking into the future
Automatic translation based on profile recognition
Technology convergence: touch translation + voice recognition +
eye tracking, Big data
Cloud-based collaborative translation, sharing translation and
terminology
Learning from other industries and cooperating
Authoring + Translation + Revision in parallel
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Some background
Why do we need translation and linguistic services after all?
Size of the language industry
Most of the industry are SME
Innovation is coming mainly from SMEs
How many freelance translators?
How many words can they handle?
Why does translation cost money?
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Concepts Source: Roberto Silva (2012)
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Linguistic industry areas Source: Status and potential of the European Language technology markets, LT Innovate (2013)
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Challenges
What are the biggest challenges of the industry?
What makes a translation company more productive?
What makes a translator more productive?
How can the customer help with the productivity workflow?
Will translation be free of charge in the near future?
How do we define quality?
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Quality matters
What is quality after all?
How do we provide the level of quality required?
Do all customers and all projects require the same level of quality?
How can technology help in keeping and improving quality levels?
Standards adoption: 30% UNE15038, 27% ISO9001
Other standards: Medical devices (ISO13485), Security (27001),
Environment (ISO14001)
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Technology can help
“The expansion of the size of the market is driven primarily by
technology” (LT Innovate, 2013)
What technologies are there for the translation sector?
What technologies do the translators use?
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Technology can help: Tools Source: Own research, Roberto Silva (2013)
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Technology can help: CAT
Main tool: Translation memories and CAT
Matching issues
Translators report that translation is 20-30% faster with CAT tools,
better quality, more consistent (terminology)
Terminology banks
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Technology can help: CAT Source: Graphic based on Survey Gough (2013), Roberto Silva (2014)
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Technology can help: CAT Source: Survey Gough (2013)
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Technology can help: CAT Source: Own research, Roberto Silva (2013)
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Technology can help: MT
Machine translation? Any good? Types?
Issues for implementing MT
Post-editing? Any benefits for the customer? For translators?
Why does MT sometimes give bad results?
Why can’t MT provide consistent good results?
MT and TM: TM is better integrated
Productivity puzzle
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Technology can help: MT usage Source: Survey QTLaunchPad (2013)
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Technology can help: MT usage Source: State of the industry for freelance translators, Proz (2012)
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Translation workflow complexity Source: Own research, Roberto Silva (2013)
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Translation workflow complexity Source: Own research, Roberto Silva (2013)
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Task complexity: search Source: Industry Survey, Gough (2013)
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Task complexity: file formats Source: Integrating Post-Editing MT in a Professional Translation Workflow (Chapter 2 of Post-editing of Machine Translation:
Processes and Applications), Roberto Silva, Cambridge Scholars Publishing (2013)
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Improving productivity
Is translation project management different from other PM?
Is technology useful for this task?
Does it benefit the customer?
Is translator productivity increasing?
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Improving productivity Source: Who is using CAT tools, Proz (2013)
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Improving productivity Source: State of the industry for freelance translators, Proz (2012)
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Improving productivity Source: State of the industry for freelance translators, Proz (2012)