Лексикаландырылған қайта реттеу моделі

Statistical phrase-based machine translation requires no linguistic information beyond word-aligned parallel corpora (Zens et al., 2002; Koehn et al., 2003). Unfortunately, this linguistic agnosticism often produces un- grammatical translations. Syntax, …...

We introduce a lexicalized reordering model for hierarchical phrase-based ma- chine translation. The model scores mono- tone, swap, and discontinuous phrase ori- entations in the manner of the one pre- …...

Lexicalized reordering model plays a central role in phrase-based statistical machine translation sys- tems. The reordering model specifies the orientation for each phrase and calculates its probability con- ditioned on …...

While lexicalized reordering models have been widely used in phrase-based translation systems, they suffer from three drawbacks: context insensitivity, ambiguity, and sparsity. We propose a neural reordering model that conditions …...

This paper describes the DCU submis- sion to WMT 2014 on German-English translation task. Our system uses phrase- based translation model with several pop- ular techniques, including Lexicalized Reordering Model, …...

This paper proposes a well-formed depen- dency to string translation model with BTG grammar. By enabling the usage of well- formed sub-structures and allowing flexible reordering of them, our approach …...

AbstractLexicalized and hierarchical reordering models use relative frequencies of fully lexicalized phrase pairs to learn phrase reordering distributions. This results in unreliable estimation for infrequent phrase pairs which also tend …...