Further Experiments in Bilingual Text Alignment

We describe and experimentally evaluate an alternative algorithm for aligning and extracting vocabulary from parallel texts using recency vectors and a similarity measure based on Levenshtein distance. The work is largely inspired by Fung and McKeown 's DK-vec, though we use a simpler algorithm. The technique is tested on two sets of parallel corpora involving English, French, German, Dutch, Spanish, and Japanese. We attempt to evaluate the importance of parameters such as frequency of words chosen as candidates, the effect of different language pairings, and differences between the two corpora.