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Translation in the 21 st Century

Translation in the 21 st Century. January 1954. Tower of Babel. Divide & Unite. Language as Instinct. Translation is very difficult …. October 2004. Reality Check. … TAUS founded. Let a Thousand MT Systems Bloom!. Effectiveness of Data. Profit from sharing (“Pirate’s Dilemma”).

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Translation in the 21 st Century

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  1. Translation in the 21st Century

  2. January 1954

  3. Tower of Babel Divide & Unite Language as Instinct Translation is very difficult …

  4. October 2004 Reality Check … TAUS founded.

  5. Let a Thousand MT Systems Bloom! Effectiveness of Data Profit from sharing (“Pirate’s Dilemma”)

  6. MT is here to stay Translation as a Utility … as a Human Right Five years ahead …

  7. Enterprises in 5 Years Need a Language Strategy not just reducing word rates “Dual Linguaspheres” Automate Innovate Collaborate

  8. Technology in 5 Years No Real Breakthroughs Hybrid Systems Targeted Correction (communities, games) Real-time Training

  9. TMs in 5 Years Cleaning Semantic Clustering Corpus Linguistics Preserve Endangered Languages Exciting new perspectives …

  10. Profession in 5 Years Choices End to Repetitive Tasks Productivity 5 to 10 Times Higher Supplemented by Non-Professional Volunteers

  11. Applications in 5 Years Translation out of the Wall Virtuous Circle Spoken Translation

  12. Industry in 5 Years Machines New Business Models ? Shared Resources & Utilities Growth Open (Collaborative) Closed (Competitive) Innovation comes from outside It’s all about the data Helping the world communicating better … Human & Machine

  13. Scenario-Based Planning • Adobe • Autodesk • Bowne • CA Technologies • Cisco • Dell • eBay • EMC • Google • Intel • Lionbridge • McAfee • Microsoft • Oracle • Paypal • Philips • SDL • Siemens • Symantec • Yahoo!

  14. Thinking about Drivers/Trends(notes from the Copenhagen meeting) Certain • Content explosion • Shift from text to text and multi-media • Mobile user, hand held devices • Real time/Just in time demand • Balance of cost, timeliness and quality Uncertain • Cloud translation replaces LSPs • Open (collaborative) Vs Closed (competitive)? • Fee Vs free? • Human Vs Machine? (incremental step or Technology breakthrough)

  15. Industry in 5 Years Machines Capability axe Collaboration axe ? Open (Collaborative) Closed (Competitive) Human & Machine

  16. Industry in 5 Years – Open/Machine Machines New Hope (free light saberon applications) ? Open (Collaborative) Closed (Competitive) Human & Machine

  17. Events that would Drive the Industry to the Open/Machine Quadrant • Pricing pressure from buyers are driving to a higher degree of automation • Transparency in collaborative environments supports benchmarking and thus competition • Standardization of measurements and quality levels provides comparability • Demand outpaces supply • Increased global competition of LSPs • Volume and price pressure forces LSPs to source globally, which is only possible using open standards • Buyers less concerned about competing with their peers.

  18. Characteristics of the Open/Machine Quadrant • Openness increases available resources • Cheaper per word than today • Cost reduction through a normalized and standardized pipeline • Shared TMs • Shared and standardized interfaces increase degree of automation • Standardized measurements are available to all

  19. Implications to the Translation Industry • Move away from per-word pricing to compensation for value-add activities • LSPs pick focus areas other than translating words.

  20. Characteristics Closed/Machines Machines The Dishwasher! ? Open (Collaborative) Closed (Competitive) Human & Machine

  21. Events that would Drive the Industry to the Closed/Machines Quadrant • If for any reason, open source fails • New, proprietary, much better private MT, patented, disruptive…. • This is where industry momentum is headed • Content mix shifts

  22. Implications to the Translation Industry • Lost opportunity for market • Seller’s market – cost stays high • Less richness of languages/localization • Less global availability • Less innovation

  23. Characteristics Closed/Human-Machines Machines ? Open (Collaborative) Closed (Competitive) Status Quo Human & Machine

  24. Events that would Drive the Industry to this Closed/Human Quadrant • Increased government regulation • Failure of MT to improve quality • Technology makes humans more efficient • Move to SAAS keeps control on IT costs • Sues Google and wins, locking content IT • Consolidation in the industry leads to stagnation • Increasing litigious society makes human checking essential • Maximizing shareholder value implies closed markets

  25. Key Characteristics of theClosed/Human Quadrant • Majority of “translation editing” is done with humans • Supply chain localisation stays with a few publishers • Only junk content gets MT’d • Crowd sourcing turns into email-spam

  26. Implications to the Translation Industry • No disruptive changes • Breeds complacency • Someone else will invent it for us • Clever people go elsewhere • Cloud and community stay around • People pay for software • Only first world to translation services

  27. Open/Human-Machine Machines ? Open (Collaborative) Closed (Competitive) Cyborg Cloud Human & Machine

  28. Events that would Drive the Industry to the Open-Human/Machines Quadrant • Geo-political • Availability of social networking (for example, PRC) • Accessibility to the technology • Online democratization • Content value / quality target • Human = high value/high quality, MT = lower value / lower quality • Post edit versus raw • Technology plateau • Limits of performance and quality • Legal requirement for human translation and quality • Drive to multimedia

  29. Key Characteristics of the Open/Machine Quadrant • Economic conditions drive to Open/Human • For example, recession • Slower technology evolution • Need to translate between a greater number of languages (for example Swahili and Brazilian Portuguese)

  30. Implications to the Translation Industry • More focus on standards • Cloud providers and social providers will play a greatly role • Opportunity to develop new tools for the human / machine translation interface • Cyborg • Voice-to-text

  31. in 5 Years Industry Think Tank Open Translation Platforms Language Business Innovation Industry Collaboration Translation Automation www.translationautomation.com

  32. in 5 Years Industry Data Resources Billions of Words Translation Matching TM Cleaning Matching Scores www.tausdata.org

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