Text Alignment in the Real World: Improving Alignments of Noisy Translations Using Common Lexical Features, String Matching Strategies and N-Gram Comparisons

Alignment methods based on byte-length comparisons of alignment blocks have been remarkably successful for aligning good translations from legislative transcriptions. For noisy translations in which the parallel text of a document has significant structural differences, byte-alignment methods often do not perform well. The Pan American Health Organization (PAHO) corpus is a series of articles that were first translated by machine methods and then improved by pro-fessional translators. Many of the Spanish PAHO texts do not share formatting conven-tions with the corresponding English docu-ments, refer to tables in stylistically different ways and contain extraneous information. A method based on a dynamic programming framework, but using a decision criterion derived from a combination of byte-length ratio measures, hard matching of numbers, string comparisons and n-gram co-occur-rence matching substantially improves the performance of the alignment process.