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.

1. Getting the Most
from MT + PE
Reducing turn-around times and maximizing cost-
effectiveness

2. In translation
since 1982

3. Working with
MT since 1991

4. Practical
advice

5. Method?

6. Overview
 Laying foundations
 Defining requirements
 Arranging the platform
 Running projects

7. Laying foundations
Devising strategies

8. Modes of use
Fully
automatic
High
quality
Unrestricted
texts
Restricted
input
Impractical
Low
quality Interactive

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. Not exactly
child’s play
 Technology
 Data
 Skills

11. A typical
translation
industry
mindset

12. Would you ask
a barber if you
need a haircut?

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. Defining
requirements
KISS, or Keep It Short and Simple

15. Building blocks
 Scope
 Goals
 Expectations

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.  Reduce cost
• By cutting labor
 Boost productivity
• Greater volumes, faster delivery
 Improve consistency
• Of terminology and style
 Reach a global audience
Goals

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. Requirements
 Spending cap
 Timeline
 Technology
 Security
 Expertise
 Reporting & analytics
 Support

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. Pick the right
vendor
Not all beers are created equal.
(Not all vendors are created equal.)

22. Prepare
 Data
 Configuration plan
 Training/recruiting program

23. Business
model

24. Be realistic MT grants no immunity to price pressure

25. Note the trend
More and more, intermediaries are cut out

26. Building the
platform
Selecting vendors, completing set-up, training staff,
testing

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. Set-up
 Data
• Maintenance
 Customized engine
• +50,000 segments
 Tool settings
• Sub-segment recall
• Fuzzy match repair

29. In-house or
outsourced?
 Total cost of ownership
 Integration
 In-house expertise
 Confidentiality
 Intellectual property issues

30. Best practices
Running projects

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. 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. 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. And remember:
Tell the customer you are using MT
So you won’t get sued

35. The fuel Output is only as good as the data used

36. Quantity and
quality
 1,000,000 words/50,000 segments
• No contiguous/inclusive domains
 More data  higher quality
• Good data

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. The output Accept that output is unpredictable

39. Automatic
metrics
Use all available automatic metrics

40. Post-editing:
expectations
1. Fast
2. Unchallenging
3. Flowing

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. Can only be computed downstreamEdit time

43. Post‐editing
effort
 Probabilistic forecasts
• Based on automatic metrics
 Depending on
• Post‐editing level
• Volume
• Turn‐around time

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. 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. Dos
 Test before operating
 Provide MT samples for negotiation
 Negotiate throughput rates
 Provide glossary (with DNT words)
 Provide instructions
 Provide feedback forms

47. Don’ts
 Use MT to curb the pressure on prices
 Process poor MT outputs
 Treat post-editing as fuzzy matches

48. Post-editing
instructions
 Tool selection
 Environment setup
 General references
 Conventions
 Project details
 Pricing model
 Operating instructions

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. 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. Automatic
processing
 Empty and/or untranslated segments
 Duplications
 Punctuation, diacritics, extra spaces,
noise
 Numbers, dates, weights, measures
 Terminology
 Spellcheck

52. Automatic tasks
Pre-processing
 Segmentation
 Normalization
 Formatting
 Terminology
Post-processing
 Encoding
 Normalization
 Formatting (tag injection)
 Terminology