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Getting the Most from MT + PE

The slide deck of the presentation given on June 16 at Localization World 34 in Barcelona.
To successfully run an MT platform and MT projects, a very specific skillset is needed. The right combination of MT and post-editing (PE) can help reduce turn-around times even in low-tech contexts while maximizing cost-effectiveness.
This presentation introduces to the strategies for an effective solution for translation buyers and vendors.
Read about the dos and don’ts when dealing with MT + PE in regard to improving productivity and increasing speed and ease of translation; the best setup for an operating environment based on the right project requirements and practices specifically devised; and the primary challenges posed by MT and PE, as preparing data, assessing quality of outputs, estimating the post-editing effort, vetting, selecting, instructing and compensating human resources.

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Getting the Most from MT + PE

  1. 1. Getting the Most from MT + PE Reducing turn-around times and maximizing cost- effectiveness
  2. 2. In translation since 1982
  3. 3. Working with MT since 1991
  4. 4. Practical advice
  5. 5. Method?
  6. 6. Overview  Laying foundations  Defining requirements  Arranging the platform  Running projects
  7. 7. Laying foundations Devising strategies
  8. 8. Modes of use Fully automatic High quality Unrestricted texts Restricted input Impractical Low quality Interactive
  9. 9. Cobbler, stick to thy last Zapatero, a tus zapatos Schuster, bleib bei deinem Leisten! Schoenmaker, blijf bij je leest Ne supra crepidam sutor iudicaret
  10. 10. Not exactly child’s play  Technology  Data  Skills
  11. 11. A typical translation industry mindset
  12. 12. Would you ask a barber if you need a haircut?
  13. 13. 3 tips for getting started 1. Recap your goals and requirements 2. Hire an independent consultant 3. Qualify your business processes for MT
  14. 14. Defining requirements KISS, or Keep It Short and Simple
  15. 15. Building blocks  Scope  Goals  Expectations
  16. 16.  E-services • Knowledge bases, assistance-and-support pages, intranets • Real-time communication  Productivity • User support, technical and user documentation  Intelligence • Text mining and analysis, research, CRM, patents  Communication • Emails, messaging, chats Scope
  17. 17.  Reduce cost • By cutting labor  Boost productivity • Greater volumes, faster delivery  Improve consistency • Of terminology and style  Reach a global audience Goals
  18. 18. Expectations  Financial • Develop business • Increase revenue • Increase profits  Business • Expand offering • Increase service levels • Streamline processes  Performance • Boost productivity • Deliver faster • Offer higher quality
  19. 19. Requirements  Spending cap  Timeline  Technology  Security  Expertise  Reporting & analytics  Support
  20. 20. Trust the consultant  Reconcile goals and expectations  Outline an exploratory program  Benchmark performance  Prepare the specs  Draft a SOW  Write the RFP  Vet vendors  Prepare your data  Revise business and pricing models  Retrofit processes
  21. 21. Pick the right vendor Not all beers are created equal. (Not all vendors are created equal.)
  22. 22. Prepare  Data  Configuration plan  Training/recruiting program
  23. 23. Business model
  24. 24. Be realistic MT grants no immunity to price pressure
  25. 25. Note the trend More and more, intermediaries are cut out
  26. 26. Building the platform Selecting vendors, completing set-up, training staff, testing
  27. 27. Givens  Not all engines are created equal  Raw output can vary across systems— and language pairs  Errors may not follow a consistent pattern  Engine performance also varies
  28. 28. Set-up  Data • Maintenance  Customized engine • +50,000 segments  Tool settings • Sub-segment recall • Fuzzy match repair
  29. 29. In-house or outsourced?  Total cost of ownership  Integration  In-house expertise  Confidentiality  Intellectual property issues
  30. 30. Best practices Running projects
  31. 31. Key questions  Buyer or vendor?  Dos & Don’ts?  How do I deal with data?  How do I assess quality?  How do I hire staff?  What about post-editing?
  32. 32. Dos  Know your data  Consider training necessary  Leverage quality evaluation metrics  Define AQLs  Plan for continuous improvement  Arrange for post-editing  Devise a compensation scheme
  33. 33. Don’ts  Treat all content equally  DIY  Rely on vendors only  Mess with data  Trust one single metric  Rush  Mess with staff  Expect miracles
  34. 34. And remember: Tell the customer you are using MT So you won’t get sued
  35. 35. The fuel Output is only as good as the data used
  36. 36. Quantity and quality  1,000,000 words/50,000 segments • No contiguous/inclusive domains  More data  higher quality • Good data
  37. 37. Good data  Few reliable sources  Single domain  Current data  Same encoding  No empty segments  No errors  Terminologically consistent segments  Same style  Same-length segments
  38. 38. The output Accept that output is unpredictable
  39. 39. Automatic metrics Use all available automatic metrics
  40. 40. Post-editing: expectations 1. Fast 2. Unchallenging 3. Flowing
  41. 41. Post-editing: measures  Edit Time • The time required to get a raw MT output to the desired standard  Post-editing effort • Percentage of edits to be applied to raw MT output to attain the desired standard
  42. 42. Can only be computed downstreamEdit time
  43. 43. Post‐editing effort  Probabilistic forecasts • Based on automatic metrics  Depending on • Post‐editing level • Volume • Turn‐around time
  44. 44. Post-editing levels  Gisting • Volatile content – Automatic scripts to fix mechanical/recurring errors  Light • Continuous delivery – Fixing capitalization and punctuation, replacing unknown words, removing redundant words, ignoring stylistic issues  Full • Publishing and engine training – Fixing meaning distortion, fixing grammar and syntax, translating untranslated terms (possibly new terms), adjusting fluency
  45. 45. Vetting and training editors  Tests not applicable • Dedicated or properly-filtered vendor base – Previous experience – Specific certifications – Domain expertise – Ability to follow instructions and style guides – Ability to process linguistic data  Specific training • Specific engines • Clients served • Instructions
  46. 46. Dos  Test before operating  Provide MT samples for negotiation  Negotiate throughput rates  Provide glossary (with DNT words)  Provide instructions  Provide feedback forms
  47. 47. Don’ts  Use MT to curb the pressure on prices  Process poor MT outputs  Treat post-editing as fuzzy matches
  48. 48. Post-editing instructions  Tool selection  Environment setup  General references  Conventions  Project details  Pricing model  Operating instructions
  49. 49. Pricing and compensation  Upstream • Clear-cut predictive scheme – No fuzzy match scheme o Fuzzy match over 85% are inherently correct while MT segments may contain errors and inaccuracies  Downstream • Measurement of actual work
  50. 50. Negotiation grid  Generals • Engine – Generic or trained • Quality – Raw output – Expectations • Formats and formatting  Compensation • Per-word rate – Productivity rate • Hourly rate – Time tracking
  51. 51. Automatic processing  Empty and/or untranslated segments  Duplications  Punctuation, diacritics, extra spaces, noise  Numbers, dates, weights, measures  Terminology  Spellcheck
  52. 52. Automatic tasks Pre-processing  Segmentation  Normalization  Formatting  Terminology Post-processing  Encoding  Normalization  Formatting (tag injection)  Terminology

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