Titlebook: Machine Translation; 12th China Workshop, Muyun Yang,Shujie Liu Conference proceedings 2016 Springer Nature Singapore Pte Ltd. 2016 natural

溫和女人

Re-ranking for Bilingual Lexicon Extraction with Bi-directional Linear Transformation from Comparabra. However, the assumption that the pairs of bilingual word embedding for training this transformation satisfy a linear relationship automatically actually cant be guaranteed absolutely in practice. So the transformation of the source language to the target one is not consistent with the one of the

包裹

Ancestor

Research on Domain Adaptation for SMT Based on Specific Domain Knowledge, not in accordance with the domain of target text to be translated, resulting in domain adaptive problem. The existing adaptive methods for statistical machine translation aim for the target text and focus on the selection of training data and the adjustment of translation models. These approaches h

conceal

GUILT

Building the Vietnamese Phrase Treebank by Improved Probabilistic Context-Free Grammars,bank resources. This paper presents a method to construct the Vietnamese phrase Treebank by fusion of Vietnamese grammatical features and improved PCFG. This method can automatically analyze Vietnamese phrase structure tree and solve the problem of constructing the Vietnamese phrase Treebank. Firstl

Psa617

卵石

BLEUS-syn: Cilin-Based Smoothed BLEU,. As the possible cases that the short translation or English abbreviations in candidate may cause unigram have no matches, this evaluation metric smoothed the traditional BLEUS n-gram. It applied synonym substitution in unigram matching, and calculated the other 2–4-gram. It performed experiments i

細節(jié)

Narrative

送秋波

MinKSR: A Novel MT Evaluation Metric for Coordinating Human Translators with the CAT-Oriented Inputantially reduce the keystrokes of translating process by accurately grasping deep information for the CAT-oriented input method, and it significantly improves the productivity of human translation compared with BLEU and TER.