Paper: Assessing Phrase-Based Translation Models with Oracle Decoding

ACL ID D10-1091
Title Assessing Phrase-Based Translation Models with Oracle Decoding
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010
Authors

Extant Statistical Machine Translation (SMT) sys- tems are very complex softwares, which embed mul- tiple layers of heuristics and embark very large num- bers of numerical parameters. As a result, it is diffi- cult to analyze output translations and there is a real need for tools that could help developers to better understand the various causes of errors. In this study, we make a step in that direction and present an attempt to evaluate the quality of the phrase-based translation model. In order to identify those translation errors that stem from deficiencies in the phrase table (PT), we propose to compute the oracle BLEU-4 score, that is the best score that a system based on this PT can achieve on a reference corpus. By casting the computation of the oracle BLEU-1 as an Integer Linear Pr...