A Dependency-to-String Model for Chinese-Japanese SMT System
نویسندگان
چکیده
This paper describes the Beijing Jiaotong University Chinese-Japanese machine translation system which participated in the 2st Workshop on Asian Translation (WAT2015). We exploit the syntactic and semantic knowledge encoded in dependency tree to build a dependency-to-string translation model for Chinese-Japanese statistical machine translation (SMT). Our system achieves a BLEU of 34.87 and a RIBES of 79.25 on the Chinese-Japanese translation task in the official evaluation.
منابع مشابه
Part-of-Speech Induction in Dependency Trees for Statistical Machine Translation
This paper proposes a nonparametric Bayesian method for inducing Part-ofSpeech (POS) tags in dependency trees to improve the performance of statistical machine translation (SMT). In particular, we extend the monolingual infinite tree model (Finkel et al., 2007) to a bilingual scenario: each hidden state (POS tag) of a source-side dependency tree emits a source word together with its aligned tar...
متن کاملSystem Description: Dependency-based Pre-ordering for Japanese-Chinese Machine Translation
This paper describes the Beijing Jiaotong University Japanese-Chinese machine translation system which participated in the 1st Workshop on Asian Translation (WAT 2014). We propose a preordering approach based on dependency parsing for Japanese-Chinese statistical machine translation (SMT). Our system achieves a BLEU of 24.12 and a RIBES of 79.48 on the Japanese-Chinese translation task in the o...
متن کاملWord Order Does NOT Differ Significantly Between Chinese and Japanese
We propose a pre-reordering approach for Japanese-to-Chinese statistical machine translation (SMT). The approach uses dependency structure and manually designed reordering rules to arrange morphemes of Japanese sentences into Chinese-like word order, before a baseline phrase-based (PB) SMT system applied. Experimental results on the ASPEC-JC data show that the improvement of the proposed pre-re...
متن کاملTransformation and Decomposition for Efficiently Implementing and Improving Dependency-to-String Model In Moses
Dependency structure provides grammatical relations between words, which have shown to be effective in Statistical Machine Translation (SMT). In this paper, we present an open source module in Moses which implements a dependency-to-string model. We propose a method to transform the input dependency tree into a corresponding constituent tree for reusing the tree-based decoder in Moses. In our ex...
متن کاملEmpirical Dependency-Based Head Finalization for Statistical Chinese-, English-, and French-to-Myanmar (Burmese) Machine Translation
We conduct dependency-based head finalization for statistical machine translation (SMT) for Myanmar (Burmese). Although Myanmar is an understudied language, linguistically it is a head-final language with similar syntax to Japanese and Korean. So, applying the efficient techniques of Japanese and Korean processing to Myanmar is a natural idea. Our approach is a combination of two approaches. Th...
متن کامل