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TAUS ROUNDTABLE 2014
22 May/ Moscow (Russia)
THURSDAY, 22 May /15:00 – 15:30
Machine Translation in the
Professional Translation Process:
Continuous Customization and ...
Challenge accepted
• The amount of content generated almost doubles annually
• Translation speed and number of translators...
Machine translation
Preconditions
• Big projects, tight deadlines
• New, less visible types of content
• Well structured t...
The Process
• Extract and translate terminology;
• Use linguistic assets both for MT customization and translation;
• Eval...
Translation workflow automation
• Integrated terminology management process
• Web-based CAT tool
• Integrated MT engines
•...
Engine retraining
Terminology
• Extract
• Improve
• Retrain
Reuse of translated and post-edited segments
• Use your post-e...
Dynamic selection of assets
Dynamic engine selection
• Personal preferences
• Editing effort and productivity parameters a...
Quality
Dynamic selection of segments for quality control
• Editing history
• Time spent
• Automatic QA results
Dynamic se...
Our plans
• Integrated term extraction and suggestion
• Adding more context information
• More QA checks
• Deeper integrat...
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Machine Translation in Professional Translation Process: Continuous Customization and Measured Productivity. Anton Voronov, ABBYY Language Services

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Although many companies have found MT inevitable, the threshold of its implementation into professional translation process remains high. Customization of MT requires time, budgets and considerable amount of translation memory databases. The choice and integration of different MT systems into professional translation process is also challenging. So what should we aim for when introducing MT to our existing working environment? This presentation focuses on the means of continuous MT customization via TM and glossaries updated in real time. Anton will discuss the ways of how to approach MT engines training, touch upon the practices of measuring the productivity of translators and see what can be done when there is no large TM corpus to customize the MT system.

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Machine Translation in Professional Translation Process: Continuous Customization and Measured Productivity. Anton Voronov, ABBYY Language Services

  1. 1. TAUS ROUNDTABLE 2014 22 May/ Moscow (Russia)
  2. 2. THURSDAY, 22 May /15:00 – 15:30 Machine Translation in the Professional Translation Process: Continuous Customization and Measured Productivity Anton Voronov, ABBYY Language Services TAUS ROUNDTABLE 2014 22 May/ Moscow (Russia)
  3. 3. Challenge accepted • The amount of content generated almost doubles annually • Translation speed and number of translators are more or less constant Main tools to increase productivity • Dictionaries, glossaries • Translation memory • Machine translation • Crowdsourcing Machine translation • Increases translation speed • Enables new types of content to be translated
  4. 4. Machine translation Preconditions • Big projects, tight deadlines • New, less visible types of content • Well structured texts with high repetition rates • Combined processes with flexible quality requirements (e.g. crowdsourcing) Requirements • Considerable volume of translation memory • Customization of MT engines • Proper choice of an MT system • Deep integration of MT systems into professional translation process
  5. 5. The Process • Extract and translate terminology; • Use linguistic assets both for MT customization and translation; • Evaluate MT engines and select the best one for each particular text; • Retrain the engine based on process results (dynamically); • Control MT quality (dynamically); • Decide which (MT or TM) is the better option for each particular segment based on metrics and terminology (dynamically); • Control and improve overall quality (dynamically); • Measure all the parameters both to estimate your PE rate and further tune the process; • Have a platform which will allow you to do all this automatically.
  6. 6. Translation workflow automation • Integrated terminology management process • Web-based CAT tool • Integrated MT engines • Agile workflow automation • Simultaneous multi-user collaboration on the same document • Automated logging of every post-editing action and its time • Built-in QA In our case all this is done in ABBYY SmartCAT, a unified cloud environment for professional translation automation.
  7. 7. Engine retraining Terminology • Extract • Improve • Retrain Reuse of translated and post-edited segments • Use your post-edited segments as soon as possible • The content translated now is more relevant
  8. 8. Dynamic selection of assets Dynamic engine selection • Personal preferences • Editing effort and productivity parameters at all stages Dynamic MT / TM selection • Match percentage • Terminology consistency • Personal preferences
  9. 9. Quality Dynamic selection of segments for quality control • Editing history • Time spent • Automatic QA results Dynamic selection of process stages • Adjust your process based on statistics and confidence
  10. 10. Our plans • Integrated term extraction and suggestion • Adding more context information • More QA checks • Deeper integration of more metrics into the process

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