The E ects of Word Order and Segmentation on TranslationRetrieval

This research looks at the eeects of word order and segmentation on translation retrieval performance for an experimental Japanese-English translation memory system. We implement a number of both bag-of-words and word order-sensitive similarity metrics, and test each over character-based and word-based indexing. The translation retrieval performance of each system connguration is evaluated empirically through the notion of word edit distance between translation candidate outputs and the model translation. Our results indicate that character-based indexing is consistently superior to word-based indexing, suggesting that segmen-tation is an unnecessary luxury in the given domain. Word order-sensitive approaches are demonstrated to generally outperform bag-of-words methods, with source language segment-level edit distance proving the most eeective similarity metric.