Factored Markov Translation with Robust Modeling
Yang Feng, Trevor Cohn, Xinkai Du · 2014
Phrase-based translation models usually memorize local translation literally and make independent assumption between phrases which makes it neither generalize well on unseen data nor model sentence-level effects between phrases. In this pa-per we present a new method to model correlations between phrases as a Markov model and meanwhile employ a robust smoothing strategy to provide better gen-eralization. This method defines a re-cursive estimation process and backs off in parallel paths to infer richer structures. Our evaluation shows an 1.1–3.2 % BLEU improvement over competitive baselines for Chinese-English and Arabic-English translation. 1