The document discusses the integration of machine translation (MT) and translation memory (TM) systems, outlining an experiment conducted to assess their compatibility. It details a 14-step process involving the use of Trados and Google Translate, along with metrics for evaluating the translation quality. The findings highlight the varying performance of MT and TM through specific scoring and error analysis of the translated texts.

1. MIXING COMPUTER-ASSISTED TRANSLATION AND MACHINE TRANSLATION: THE GOOD, THE BAD AND THE UGLY

2. THE ISSUE Can we combine TM and MT? Copyright 2008 Cris Silva and Giovana Boselli

3. OUTLINE Our story How MT and TM can work together Defining MT and TM systems Our 14-step experiment Final considerations Copyright 2008 Cris Silva and Giovana Boselli

4. COMPUTER-ASSISTED TRANSLATION Spellcheckers Grammar checkers Dictionaries on CD-ROM Terminology databases Translation memories Alignment tools Project management software Copyright 2008 Cris Silva and Giovana Boselli

5. DEFINING TM AND MT TRANSLATION MEMORY = searchable database containing source and translated sentences MACHINE TRANSLATION = application of computers to the task of translating texts from one natural language to another. Copyright 2008 Cris Silva and Giovana Boselli

6. OUR SCENARIO Trados + Google Translate + MS old Glossaries Copyright 2008 Cris Silva and Giovana Boselli

7. PROCESS STEPS Conversion of Excel CSV Microsoft glossaries into a Trados translation memory-friendly format. Creation of a blank memory in Trados. Import of Microsoft glossaries into Trados memory. Writing of 3 unique sample texts (500 words each) Pre-translation of sample texts in Trados. Copying 0% match results of pre-translation from Trados. Pasting of 0% match results of pre-translation to an Excel file. Feeding of Excel file into Google Translate. Translation by Google Translate. Copying Google results from Google screen Pasting results back into Excel file. Error analysis of Google Translate Scoring Final score Copyright 2008 Cris Silva and Giovana Boselli

8. STEP 1: CONVERSION OF EXCEL CSV MICROSOFT GLOSSARIES INTO A TRADOS TRANSLATION MEMORY-FRIENDLY FORMAT Copyright 2008 Cris Silva and Giovana Boselli

9. STEP 1: CONVERSION OF EXCEL CSV MICROSOFT GLOSSARIES INTO A TRADOS TRANSLATION MEMORY-FRIENDLY FORMAT Copyright 2008 Cris Silva and Giovana Boselli

10. STEP 2: CREATION OF A BLANK MEMORY IN TRADOS Copyright 2008 Cris Silva and Giovana Boselli

11. STEP 3: IMPORT OF MICROSOFT GLOSSARIES INTO TRADOS MEMORY Copyright 2008 Cris Silva and Giovana Boselli

12. 3 unique texts, 500 words each written especifically for this experiment based on Microsoft terminology and products. focus on MS Word features. leverage proportions from memory: 30% same as memory (i.e., with a 100% match) 25% based on the memory, adding words or terms 25% based on the memory, deleting words or terms 20% new text from Microsoft Help web site for Word. STEP 4: WRITING OF SAMPLE TEXTS Copyright 2008 Cris Silva and Giovana Boselli

13. STEP 4: SAMPLES Copyright 2008 Cris Silva and Giovana Boselli IN MEMORY OUR TEXT LEVERAGE Router does not have IPX installed. Router does not have IPX installed. 30% same as memory SECOND disk is bad or incompatible SECOND disk is bad or incompatible 30% same as memory Unable to view drive information. Unable to view drive information required . 25% based on the memory, with additions of words or terms Windows 2000 IP Configuration. Windows 2000 IP Configuration is ready. 25% based on the memory, with additions of words or terms Proxy Interface: has no group entries Proxy Interface: has group entries 25% based on the memory, cutting off words or terms A preference level does not exist for the protocol. A preference level exists for the protocol. 25% based on the memory, cutting off words or terms - In the Manage list, select Word Add-ins, and then click Go. 20 % new text from Microsoft Help web site for Word - Click the Templates tab. 20 % new text from Microsoft Help web site for Word

14. STEP 5: PRE-TRANSLATION OF SAMPLE TEXTS IN TRADOS Copyright 2008 Cris Silva and Giovana Boselli

15. STEP 6: COPYING OF 0% MATCH RESULTS OF PRE-TRANSLATION TO AN EXCEL FILE. Copyright 2008 Cris Silva and Giovana Boselli

16. STEP 7: PASTING OF 0% MATCH RESULTS OF PRE-TRANSLATION TO AN EXCEL FILE Copyright 2008 Cris Silva and Giovana Boselli

17. STEP 8: ENTERING EXCEL FILE INTO GOOGLE TRANSLATE Copyright 2008 Cris Silva and Giovana Boselli

18. STEP 9: TRANSLATION BY GOOGLE TRANSLATE Copyright 2008 Cris Silva and Giovana Boselli

19. STEP 10: COPYING TRANSLATED TEXT FROM GOOGLE Copyright 2008 Cris Silva and Giovana Boselli

20. STEP 11: PASTING GOOGLE TRANSLATE RESULTS INTO EXCEL Copyright 2008 Cris Silva and Giovana Boselli

21. ATA FRAMEWORK FOR ERROR MARKING Copyright 2008 Cris Silva and Giovana Boselli

22. OUR ERROR CATEGORIES Copyright 2008 Cris Silva and Giovana Boselli

23. A MATTER OF PERCEPTION? Copyright 2008 Cris Silva and Giovana Boselli

24. STEP 12: ERROR ANALYSIS OF GOOGLE TRANSLATION Copyright 2008 Cris Silva and Giovana Boselli

25. METRICS Copyright 2008 Cris Silva and Giovana Boselli

26. OUR EVALUATION SCHEME Copyright 2008 Cris Silva and Giovana Boselli

27. STEP 13: SCORING Copyright 2008 Cris Silva and Giovana Boselli

28. STEP 14: TOTAL SCORE Copyright 2008 Cris Silva and Giovana Boselli ORIGINAL SOURCE GOOGLE TRANSLATED (0% MATCH) SCORE T1 500 271 44.5 T2 500 319 39.75 T3 500 274 27.5

29. THANK YOU… Cris Silva Giovana Boselli [email_address] [email_address] We would like to thank Renato Beninatto Sue Ellen Wright Jonathan Mendoza Riccardo Schiaffino Copyright 2008 Cris Silva and Giovana Boselli