Machine Translation

1. Machine Translation

by Victoria Nalimova

2. Machine Translation Engines

Rule-based
Statistical
use linguistic rules;
produces predictable
output for terminology and
grammar;
do not require bilingual
corpus
uses statistical models;
is built by analyzing
bilingual corpus;
requires an appropriate
volume of bilingual content

3.

The engine chosen for a project depends on:
the target languages
Machine
Translation
the availability of
reference materials
“Raw”
Machine
Translation
output
Translation
Memory
matches
Post-edition
by
experienced
linguists

4. Why Machine Translation?

increase in productivity
reduction in time-to-market
reduction in translation costs
increase in consistency of
terminology

5. Metrics of quality

F-Measure
BLEU Scores
TER Scores
Post-editing
Efficiency

6. Terminology lists

Machine Translation;
computational linguistics;
language engineering;
customized terminology lists;
bilingual corpus;
post-editing

7. Thank you for your attention