| Titles |
|
English :
|
Tuning Statistical Machine Translation Parameters
|
|
| Abstract |
Word alignment is the basis of statistical machine
translation. GIZA++ is a popular tool for producing word alignments
and translation models. It uses a set of parameters that affect the
quality of word alignments and translation models. These parameters
exist to overcome some problems such as overfitting. This paper
addresses the problem of tuning GIZA++ parameter for better
translation quality. The results show that our systematic procedure
for parameter tuning can improve the translation quality.
|
| URL |
|
| Publication year |
2004
|
| Pages |
15-18
|
| Organization Name |
Climate Change Information Center & Renewable Energy & Expert Systems
|
| Country |
Turkey
|
| Publisher |
Name:
ENFORMATIKA
|
| serial title |
International Journal of Information Technology
|
| Web Page |
|
| ISSN |
1305-2403
|
| Volume |
VOLUME 1
.
|
| Author(s) from ARC |
|
| Agris Categories |
Documentation and information
|
| Proposed Agrovoc |
Parameter tuning; smoothing factors; training;
|
| Publication Type |
Journal
|