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- W1569841287 abstract "We propose a lexicalized syntactic reordering framework for cross-language word aligning and translating researches. In this framework, we first flatten hierarchical source-language parse trees into syntactically-motivated linear string representations, which can easily be input to many feature-like probabilistic models. During model training, these string representations accompanied with target-language word alignment information are leveraged to learn systematic similarities and differences in languages' grammars. At runtime, syntactic constituents of source-language parse trees will be reordered according to automatically acquired lexicalized reordering rules in previous step, to closer match word orientations of the target language. Empirical results show that, as a preprocessing component, bilingual word aligning and translating tasks benefit from our reordering methodology." @default.
- W1569841287 created "2016-06-24" @default.
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- W1569841287 date "2009-01-01" @default.
- W1569841287 modified "2023-09-22" @default.
- W1569841287 title "Lexicalized Syntactic Reordering Framework for Word Alignment and Machine Translation" @default.
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- W1569841287 doi "https://doi.org/10.1007/978-3-642-00831-3_10" @default.
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