Paper: Transliteration Alignment

ACL ID P09-1016
Title Transliteration Alignment
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

This paper studies transliteration align- ment, its evaluation metrics and applica- tions. We propose a new evaluation met- ric, alignment entropy, grounded on the information theory, to evaluate the align- ment quality without the need for the gold standard reference and compare the metric with F-score. We study the use of phono- logical features and affinity statistics for transliteration alignment at phoneme and grapheme levels. The experiments show that better alignment consistently leads to more accurate transliteration. In transliter- ation modeling application, we achieve a mean reciprocal rate (MRR) of 0.773 on Xinhua personal name corpus, a signifi- cant improvement over other reported re- sults on the same corpus. In transliteration validation application, we achieve 4.48% equal ...