Structured and Unstructured Cache Models for SMT Domain Adaptation
Annie Louis, Bonnie Webber · 2014
We present a French to English transla-tion system for Wikipedia biography ar-ticles. We use training data from out-of-domain corpora and adapt the system for biographies. We propose two forms of domain adaptation. The first biases the system towards words likely in biogra-phies and encourages repetition of words across the document. Since biographies in Wikipedia follow a regular structure, our second model exploits this structure as a sequence of topic segments, where each segment discusses a narrower subtopic of the biography domain. In this structured model, the system is encouraged to use words likely in the current segment’s topic rather than in biographies as a whole. We implement both systems using cache-based translation techniques. We show that a system trained on Europarl and news can be adapted for biographies with 0.5 BLEU score improvement using our mod-els. Further the structure-aware model out-performs the system which treats the entire document as a single segment. 1