Bootstrapping a Stochastic Transducer
for Arabic-English Transliteration Extraction
We propose a bootstrapping approach
to training a memoriless stochastic transducer
for the task of extracting transliterations
from an English-Arabic bitext.
The transducer learns its similarity metric
from the data in the bitext, and thus can function directly
on strings written in different writing scripts without
any additional language knowledge.
We show that this bootstrapped transducer
performs as well or better than a model
designed specifically to detect
Arabic-English transliterations.