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第十三届全国机器翻译研讨会(CWMT 2017)于2017年9月27-29日在中国大连举行。
全国机器翻译研讨会自2005年召开第一届以来，已连续成功组织召开了十二届，共组织过六次机器翻译评测（2007、2008、2009、2011、2013、2015），一次开源系统模块开发（2006）和两次战略研讨（2010、2012），这些活动对于推动我国机器翻译技术的研究和开发产生了积极而深远的影响。因...
Binary Translation Using Peephole Superoptimizers
Binary Translation Peephole Superoptimizers
2016/5/24
We present a new scheme for performing binary translation that produces code comparable to or better than existing binary translators with much less engineering effort. Instead of hand-coding the tran...
Re-structuring, Re-labeling, and Re-aligning for Syntax-Based Machine Translation
Syntax-Based Machine Translation Re-labeling,
2015/9/8
his article shows that the structure of bilingual material from standard parsing and alignment
tools is not optimal for training syntax-based statistical machine translation (SMT) systems.
We presen...
Segmentation for English-to-Arabic Statistical Machine Translation
English-to-Arabic Machine Translation
2014/11/27
In this paper, we report on a set of initial results for English-to-Arabic Statistical Machine Translation (SMT). We show that morphological decomposition of the Arabic source is beneficial, especiall...
An Investigation on the Effectiveness of Features for Translation Quality Estimation
Investigation Effectiveness Features Translation Quality Estimation
2014/3/20
We describe a systematic analysis on the effectiveness of features commonly exploited for the problem of predicting machine translation quality. Using a feature selection technique based on Gaussian P...
A Markov Model of Machine Translation using Non-parametric Bayesian Inference
Markov Model Machine Translation Non-parametric Bayesian Inference
2014/3/20
Most modern machine translation systems use phrase pairs as translation units, allowing for accurate modelling of phraseinternal translation and reordering. However phrase-based approaches are much le...
An Infinite Hierarchical Bayesian Model of Phrasal Translation
An Infinite Hierarchical Bayesian Model Phrasal Translation
2014/3/20
Modern phrase-based machine translation systems make extensive use of wordbased translation models for inducing alignments from parallel corpora. This is problematic, as the systems are incapable of a...
Modelling Annotator Bias with Multi-task Gaussian Processes: An Application to Machine Translation Quality Estimation
Modelling Annotator Bias Multi-task Gaussian Processes:Machine Translation Quality Estimation
2014/3/20
Annotating linguistic data is often a complex, time consuming and expensive endeavour. Even with strict annotation guidelines, human subjects often deviate in their analyses, each bringing different b...
QuEst - A translation quality estimation framework
QuEst - A translation quality estimation framework
2014/3/20
We describe QUEST, an open source framework for machine translation quality estimation. The framework allows the extraction of several quality indicators from source segments, their translations, exte...
We introduce synchronous tree adjoining grammars (TAG) into tree-to-string transla-tion, which converts a source tree to a target string. Without reconstructing TAG deriva-tions explicitly, our rule e...
Maximum Rank Correlation Training for Statistical Machine Translation
Maximum Rank Correlation Training Statistical Machine Translation
2013/4/22
We propose Maximum Ranking Correlation (MRC) as an objective function in discrimi-native tuning of parameters in a linear model of Statistical Machine Translation (SMT). We try to maximize the ranking...
Rule Markov Models for Fast Tree-to-String Translation
Rule Markov Models Fast Tree-to-String Translation
2013/4/22
Most statistical machine translation systems rely on composed rules (rules that can be formed out of smaller rules in the grammar).Though this practice improves translation by weakening independence a...
A Novel Dependency-to-String Model for Statistical Machine Translation
Novel Dependency-to-String Model Statistical Machine Translation
2013/4/22
Dependency structure, as a first step towards semantics, is believed to be helpful to improve translation quality. However, previous works on dependency structure based models typi-cally resort to ins...
As tokenization is usually ambiguous for many natural languages such as Chinese and Korean, tokenization errors might po-tentially introduce translation mistakes for translation systems that rely on 1...
Dependency-Based Bracketing Transduction Grammar for Statistical Machine Translation
Dependency-Based Bracketing Transduction Grammar Statistical Machine Translation
2013/4/22
In this paper, we propose a novel dependency-based bracketing transduc-tion grammar for statistical machine translation, which converts a source sen-tence into a target dependency tree. Dif-ferent fro...