Supplementary data selection from out-of-domain or related-domain data is a well established technique in domain adaptation of statistical machine translation. The selection criteria for such data are mostly based on measures of similarity with available in-domain data, but not directly in terms of translation quality. In this paper, we present a technique for selecting supplementary data to im...

This is a report on our evaluation of using some language resources for the Indonesian-English bilingual task of the 2007 Cross-Language Evaluation Forum (CLEF). We chose to translate an Indonesian query set into English using machine translation, transitive translation, and parallel corpus-based techniques. We also made an attempt to improve the retrieval effectiveness using a query expansion ...

negligent of the recent findings of translation studies in the past decades, the undergraduate curriculum of english translation in iranian universities has not been updated since over two decades ago. the comparison of this curriculum with its international rival curricula indicates to a substantial discrepancy which cannot be solely due to contextual or cultural reasons. it is also suspected ...

This paper presents the adapting rule based machine translation from English to Bangla. The proposed language translation model relies on rule based methodologies especially fuzzy rules. There are “If Then” basis rules are applied for the English to Bangla language translation. In this language translation, we use rough set technique for Knowledge Representation System. This technique is used t...

Boosting is a general method for improving the accuracy of a given learning algorithm under certain restrictions. In this work, AdaBoost, one of the most popular boosting algorithms, is adapted and applied to statistical machine translation. The appropriateness of this technique in this scenario is evaluated on a real translation task. Results from preliminary experiments confirm that statistic...

In this article, we describe system architecture, training data preparation and experimental results of the EIWA group in the NTCIR-8 Patent Translation Task. Our system is combining rulebased machine translation technique and statistical post-editing technique. Experimental results show 0.344 BLEU score for Japanese to English intrinsic evaluation in the Patent Translation Task.