Paper: Transliteration as Constrained Optimization

ACL ID D08-1037
Title Transliteration as Constrained Optimization
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2008

This paper introduces a new method for iden- tifying named-entity (NE) transliterations in bilingual corpora. Recent works have shown the advantage of discriminative approaches to transliteration: given two strings (ws,wt) in the source and target language, a classifier is trained to determine if wt is the translitera- tion of ws. This paper shows that the translit- eration problem can be formulated as a con- strained optimization problem and thus take into account contextual dependencies and con- straints among character bi-grams in the two strings. We further explore several methods for learning the objective function of the opti- mization problem and show the advantage of learning it discriminately. Our experiments show that the new framework results in over 50% improvement in translati...