Modelling and Optimizing on Syntactic N-Grams for Statistical Machine Translation

TACL 2015 Rico Sennrich

The role of language models in SMT is to promote fluent translation output, but traditional n-gram language models are unable to capture fluency phenomena between distant words, such as some morphological agreement phenomena, subcategorisation, and syntactic collocations with string-level gaps. Syntactic language models have the potential to fill this modelling gap... (read more)

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