Transliteration is the task of converting a word from one alphabetic
script to another.
We present a novel, substring-based approach to transliteration,
inspired by phrase-based models of machine translation.
We investigate two implementations of substring-based
transliteration: a dynamic programming algorithm,
and a finite-state transducer.
We show that our substring-based transducer not only outperforms
a state-of-the-art letter-based approach by a significant margin,
but is also orders of magnitude faster.