Paper: Unsupervised Structure Prediction with Non-Parallel Multilingual Guidance

ACL ID D11-1005
Title Unsupervised Structure Prediction with Non-Parallel Multilingual Guidance
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

We describe a method for prediction of lin- guistic structure in a language for which only unlabeled data is available, using annotated data from a set of one or more helper lan- guages. Our approach is based on a model that locally mixes between supervised mod- els from the helper languages. Parallel data is not used, allowing the technique to be ap- plied even in domains where human-translated texts are unavailable. We obtain state-of-the- art performance for two tasks of structure pre- diction: unsupervised part-of-speech tagging and unsupervised dependency parsing.