Legal translation is a type of translation for legal terms and documents from a source language (SL) into a target language (TL). Moreover, it is also a translation from one legal system into another. It involves all the legal texts that are used in different legal settings; in courts, legal reports, contracts, etc. This paper aimed at examining the translatability of Google Translation (GT) fo...

We formulate an original model for statistical machine translation (SMT) inspired by characteristics of the Arabic-English translation task. Our approach incorporates part-of-speech tags and linguistically motivated phrase chunks in a 2-level shallow syntactic model of reordering. We implement and evaluate this model, showing it to have advantageous properties and to be competitive with an exis...

We present a method for incorporating arbitrary context-informed word attributes into statistical machine translation by clustering attribute-quali ed source words, and smoothing their word translation probabilities using binary decision trees. We describe two ways in which the decision trees are used in machine translation: by using the attribute-quali ed source word clusters directly, or by u...

The distortion cost function used in Mosesstyle machine translation systems has two flaws. First, it does not estimate the future cost of known required moves, thus increasing search errors. Second, all distortion is penalized linearly, even when appropriate reorderings are performed. Because the cost function does not effectively constrain search, translation quality decreases at higher distor...

Existing Arabic sentiment lexicons have low coverage—only a few thousand entries. In this paper, we present several large sentiment lexicons that were automatically generated using two different methods: (1) by using distant supervision techniques on Arabic tweets, and (2) by translating English sentiment lexicons into Arabic using a freely available statistical machine translation system. We c...

OBJECTIVE The aim of this study was to cross-culturally adapt the Armando Patient Satisfaction Questionnaire into Arabic and validate its use in the general population. METHODS The translation was conducted based on the principles of the most widely used model in questionnaire translation, namely Brisling's back-translation model. A written authorization allowing translation into Arabic was o...

Arabic dialect classification has been an important and challenging problem for Arabic language processing, especially for social media text analysis and machine translation. In this paper we propose an approach to improving Arabic dialect classification with semi-supervised learning: multiple classifiers are trained with weakly supervised, strongly supervised, and unsupervised data. Their comb...

Searching online information is increasingly a daily activity for many people. The multilinguality of online content is also increasing (e.g. the proportion of English web users, which has been decreasing as a fraction the increasing population of web users, dipped below 50% in the summer of 2001). To improve the ability of an English speaker to search mutlilingual content, we built a system th...

This paper describes the MIRACL statistical Machine Translation system and the improvements that were developed during the IWSLT 2010 evaluation campaign. We participated to the Arabic to English BTEC tasks using a phrase-based statistical machine translation approach. In this paper, we first discuss some challenges in translating from Arabic to English and we explore various techniques to impr...