Syntax-Based Translation With Bilingually Lexicalized Synchronous Tree Substitution Grammars

Syntax-based models can significantly improve the translation performance due to their grammatical modeling on one or both language side(s). However, the translation rules such as the non-lexical rule " VP→(x 0 x 1 ,VP:x 1 PP:x 0 )" in string-to-tree models do not consider any lexicalized...

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Vydané v:IEEE transactions on audio, speech, and language processing Ročník 21; číslo 8; s. 1586 - 1597
Hlavní autori: Zhang, Jiajun, Zhai, Feifei, Zong, Chengqing
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway, NJ IEEE 01.08.2013
Institute of Electrical and Electronics Engineers
Predmet:
Adaptation models
Applied sciences
Bilingually lexicalized synchronous tree substitution grammars
Coding, codes
Decoding
discriminative model
Exact sciences and technology
generative model
Grammar
Information, signal and communications theory
Miscellaneous
Reliability
Signal and communications theory
Signal processing
Syntactics
syntax-based statistical machine translation
Telecommunications and information theory
Training
Vegetation
Performance evaluation
Discriminant analysis
Bilingually lexicalized synchronous tree substitution grammars
syntax-based statistical machine translation
Syntactic analysis
Tree structure
Decoding
Formal grammar
Modeling
Case study
Guidance
English
Language processing
Information source
Automatic translation
Chinese
generative model
Syntax
discriminative model
ISSN:1558-7916, 1558-7924
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Popis
Shrnutí:Syntax-based models can significantly improve the translation performance due to their grammatical modeling on one or both language side(s). However, the translation rules such as the non-lexical rule " VP→(x 0 x 1 ,VP:x 1 PP:x 0 )" in string-to-tree models do not consider any lexicalized information on the source or target side. The rule is so generalized that any subtree rooted at VP can substitute for the nonterminal VP:x 1 . Because rules containing nonterminals are frequently used when generating the target-side tree structures, there is a risk that rules of this type will potentially be severely misused in decoding due to a lack of lexicalization guidance. In this article, inspired by lexicalized PCFG, which is widely used in monolingual parsing, we propose to upgrade the STSG (synchronous tree substitution grammars)-based syntax translation model with bilingually lexicalized STSG. Using the string-to-tree translation model as a case study, we present generative and discriminative models to integrate lexicalized STSG into the translation model. Both small- and large-scale experiments on Chinese-to-English translation demonstrate that the proposed lexicalized STSG can provide superior rule selection in decoding and substantially improve the translation quality.
ISSN:1558-7916
1558-7924
DOI:10.1109/TASL.2013.2255283