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Remote Sensing (RS) and Geography Information System (GIS) technologies are widely used in ecological analysis and regional planning. With the advantages of large scale monitoring, combination of poin...
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...
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...
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...
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...
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...
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...
This paper illustrates the ICT Statistical Machine Transla-tion system used in the evaluation campaign of the Interna-tional Workshop on Spoken Language Translation 2010. We participate in the DIALOG ...
We propose a structure calleddependency forest for statistical machine translation.A dependency forest compactly represents multiple dependency trees. We develop new algorithms for extracting string-t...
In this paper, we propose a nove dependency-based bracketing transduc-tion grammar for statistical machine translation, which converts a source sen-tence into a target dependency tree. Dif-ferent from...
In statistical machine translation, decod-ing without any reordering constraint is an NP-hard problem. Inversion Transduc-tion Grammars (ITGs) exploit linguistic structure and can well balance the nee...
Traditional 1-best translation pipelines suffer a major drawback: the errors of 1-best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeline. In order to alle...
This paper presents an overall introduction to the CWMT2008 evaluation and focuses on its two new metrics: BLEU-SBP (Chiang et al., 2008) and linguistic check-point me-thod (Zhou et al., 2008). BLEU-S...
Tree-based statistical machine translation models have made significant progress in re-cent years, especially when replacing 1-best trees with packed forests. However, as the parsing accuracy usuall...
Current statistical machine translation sys-tems usually extract rules from bilingual corpora annotated with 1-best alignments.They are prone to learn noisy rules due to alignment mistakes. We propose...

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