This paper presents an extensive evaluation of five different alignments and investigates their impact on the corresponding MT system output. We introduce new measures for intrinsic evaluations and examine the distribution of phrases and untranslated words during decoding to identify which characteristics of different alignments affect translation. We show that precision-oriented alignments yield better MT output (translating more words and using longer phrases) than recall-oriented alignments.
['Necip Fazil Ayan', 'Bonnie J. Dorr']
Going Beyond AER: An Extensive Analysis of Word Alignments and Their Impact on MT