Phrase Table Training for Precision and Recall: What Makes a Good Phrase and a Good Phrase Pair?

In this work, the problem of extracting phrase translation is formulated as an information re- trieval process implemented with a log-linear model aiming for a balanced precision and re- call. We present a generic phrase training al- gorithm which is parameterized with feature functions and can be optimized jointly with the translation engine to directly maximize the end-to-end system performance. Multiple data-driven feature functions are proposed to capture the quality and confidence of phrases and phrase pairs. Experimental results demon- strate consistent and significant improvement over the widely used method that is based on word alignment matrix only.