Abstract
Recent research has shown clear improvement in translation quality by exploiting linguistic syntax for either the source or target language. However, when using syntax for both languages (“tree-to-tree” translation), there is evidence that syntactic divergence can hamper the extraction of useful rules (Ding and Palmer 2005 ). Smith and Eisner ( 2006 ) introduced quasi-synchronous grammar, a formalism that treats non-isomorphic structure softly using features rather than hard constraints. Although a natural fit for translation modeling, its flexibility has proved challenging for building real-world systems. In this article, we present a tree-to-tree machine translation system inspired by quasi-synchronous grammar. The core of our approach is a new model that combines phrases and dependency syntax, integrating the advantages of phrase-based and syntax-based translation. We report statistically significant improvements over a phrase-based baseline on five of seven test sets across four language pairs. We also present encouraging preliminary results on the use of unsupervised dependency parsing for syntax-based machine translation.
Highlights
Building translation systems for many language pairs requires addressing a wide range of translation divergence phenomena
We present a statistical tree-to-tree machine translation system inspired by quasi-synchronous grammar
All quasi-synchronous phrase dependency (QPD) results are significantly better than all Moses baseline results, but there is no significant difference between the two QPD feature sets
Summary
Building translation systems for many language pairs requires addressing a wide range of translation divergence phenomena. Many have incorporated linguistic syntax into translation model design. The availability of these parsers, and gains in their accuracy, triggered research interest in syntax-based statistical machine translation (Yamada and Knight 2001). We use boldface for vectors and we denote individual elements in vectors using subscripts; for example, the source and target sentences are denoted x = x1, . We denote the set containing the first k positive integers as [k].
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