Applying boosting to statistical machine translation.
Antonio L. Lagarda, Francisco Casacuberta · 2008
Abstract. Boosting is a general method for improving the accuracy of a given learning algorithm under certain restrictions. In this work, AdaBoost, one of the most popular boosting algorithms, is adapted and applied to statistical machine translation. The appropriateness of this technique in this scenario is evaluated on a real translation task. Results from preliminary experiments confirm that statistical machine transla-tion can take advantage from this technique, improving the translation quality. 1