This document provides tips and tricks for expediting the process of post-editing machine translation output. It defines post-editing as achieving the same or higher quality as a full human translation. It recommends getting to know the typical errors of different machine translation systems and using keyboard shortcuts, regular expressions, search and replace functions, and macros to automate repetitive post-editing tasks. The document also suggests keeping statistical data on post-editing efforts to continue improving machine translation quality over time.

1. Tips and Tricks for
Full Post Editing
Ruben de la Fuente

2. About Me
• 4-year degree in translation
• Worked as translator for 10+ years
• Working full time in MT for the past
year

3. Agenda
• Some definitions about PE
• Some useful knowledge about MT
• Tips for expediting PE

4. How many of you have ever been
involved with PE?
How many would do it again?

5. Full PE in lay man’s terms
Same (or higher) level of quality as
translation from scratch

6. Does the # errors matter?
It matters more how easy they are to fix

7. Think Patterns
MT often trips over the same stone

8. Know the Systems
Know what to expect
Know what can be improved

9. MT Typical Errors
RbMT is good at Accuracy
SMT is good at Fluency

10. MT Typical Errors (II)
Error RbMT SMT
Missing word Less likely Likely
Word order Likely Less likely
Incorrect word Likely Likely
Unknown word Less likely Likely
Punctuation Less likely Likely

11. Master the Keyboard
Do you know your shortcuts?

12. Two-Second Rule
If edits are not obvious after a quick look,
discard the segment and re-translate from
scratch

13. First pass with QA Check tool
• Empty/untranslated segments
• Doubled words
• Checks of length (shorter/longer src%)
• Punctuation, spaces
• Language tool rules
• Terminology adherence

14. CheckMate: General

15. CheckMate: Length

16. CheckMate: Terminology

17. Global Search and Replace
Recurring edits can be automated
through search and replace

18. Why Bother With Regex?
5-10 regular search replace operations =
1 operation with regex
That’s why ;-)

19. Regex Basics
• Wildcards: . s d w
• Quantifiers: +*{1,5}
• Charsets: [a-z] [0-9] [Aa]
• Non-printable: n, r, t
• Anchors: ^, $, b
• Alternation: |
• Grouping&remembering: ()

20. Issues fixable with RegEx
• Misspellings
• Punctuation
• Grammar agreement
• Word order
• Dissambiguation
• Style

21. Source of Examples
www.rafaelguzman.ie particularly,
•Automating PE with regular expressions
•Advanced automatic PE

22. Fixing number agreement
Están activos/inactivos/abiertos/cerrados

23. Word Order
Java-basadosbasados en Java

24. Consistent Style
Usted debe/necesita/tiene queEs
necesario

25. Dissambiguation
Active queCompruebe que

26. Macros/Scripts
• S+R operations can be stored in a
macro for later re-use

27. PE report
• Edit distance to see leverage
• Detailed info on edits; action for
improvement

28. Statistical PE
• Keep a corpus of raw vs. PE
• Treat them as separate language pairs
• Run them through a Statistical Machine
Translation toolkit
• Create raw vs. PE engine

29. Key take-away
Don’t do manually what can be done
automatically

30. Questions?
Speak now…
Or reach me at:
www.facebook.com/xlation
www.wordbonds.es
@rubendelafuente
http://www.linkedin.com/in/rubendelafuen
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