This document discusses combining translation memory (TM) and statistical machine translation (SMT). It summarizes that TM works best for repetitive text but SMT is more reliable when there are no close matches. It then reviews the speaker's previous work on combining TM and SMT during decoding and before decoding, and presents results showing BLEU score improvements on several language pairs.

1. Combination of TM and SMT
Liangyou Li (ESR 8)
ADAPT Centre, School of Computing
Dublin City University
liangyouli@computing.dcu.ie

2.  TM can produce high
quality and consistent
translations for repetitive
materials.
 When no high similar
instances exist, SMT is
more reliable
Why combining TM and SMT?
(Koehn and Senellart, 2010)

3.  Combination During Decoding
 AMTA 2014
 EAMT 2016
 Combination Before Decoding
 ACL 2016
Contributions

4. Combination During Decoding
Input
TM
SMT
output
Fuzzy matches

5. Combination During Decoding
Input
TM
SMT
output
Fuzzy matches
Find rules
extract
features
add features
to decoder
Input
TM
matches

6. Combination During Decoding
Results on English-Spanish Data from Hermes

7. Combination Before Decoding
Input
TM
SMT
output
Fuzzy matches
new
input

8. Combination Before Decoding
Input
TM
SMT
output
Fuzzy matches
new
input

9. Combination Before Decoding
Results on English-Chinese and English-French

10. Conclusion
BLEU scores VS Productivity Gains
(Parra Escartín and Arcedillo, 2015)

11. The End!
Thank You !