Unification-based constraints for statistical machine translation
Morphology and syntax have both received attention in statistical machine translation research, but they are usually treated independently and the historical emphasis on translation into English has meant that many morphosyntactic issues remain under-researched. Languages with richer morphologies pose additional problems and conventional approaches tend to perform poorly when either source or target language has rich morphology. In both computational and theoretical linguistics, feature structures together with the associated operation of unification have proven a powerful tool for modelling many morphosyntactic aspects of natural language. In this thesis, we propose a framework that extends a state-of-the-art syntax-based model with a feature structure lexicon and unification-based constraints on the target-side of the synchronous grammar. Whilst our framework is language-independent, we focus on problems in the translation of English to German, a language pair that has a high degree of syntactic reordering and rich target-side morphology. We first apply our approach to modelling agreement and case government phenomena. We use the lexicon to link surface form words with grammatical feature values, such as
Williams, Philip James
statistical machine translation ; morphology ; syntactic reordering
Unification-based constraints for statistical machine translation. Morphology and syntax have both received attention in statistical machine translation research, but they are usually treated independently and the historical emphasis on translation into English has meant that many morphosyntactic issues remain under-researched. Languages with richer morphologies pose additional problems and conventional approaches tend to perform poorly when either source or target language has rich morphology. In both computational and theoretical linguistics, feature structures together with the associated operation of unification have proven a powerful tool for modelling many morphosyntactic aspects of natural language. In this thesis, we propose a framework that extends a state-of-the-art syntax-based model with a feature structure lexicon and unification-based constraints on the target-side of the synchronous grammar. Whilst our framework is language-independent, we focus on problems in the translation of English to German, a language pair that has a high degree of syntactic reordering and rich target-side morphology. We first apply our approach to modelling agreement and case government phenomena. We use the lexicon to link surface form words with grammatical feature values, such as
unification based constraint statistical_machine_translation morphology_syntax receive_attention statistical_machine_translation usually treat independently historical emphasis translation_english mean many morphosyntactic issue remain_under researched languages rich morphology pose additional problem conventional_approach tend perform poorly either source_target language rich morphology computational theoretical_linguistics feature structure together associate operation unification proven powerful_tool model many morphosyntactic aspect natural_language propose framework extend state_of_the_art syntax based_model feature structure lexicon unification based constraint target side synchronous grammar whilst framework language independent focus problem translation english_german language_pair high_degree syntactic reordering rich target side morphology first apply model agreement case government phenomenon use lexicon link surface_form word grammatical_feature value