Arabic Dialects present many challenges for machine translation, not least of which is the lack of data resources. We use crowdsourcing to cheaply and quickly build LevantineEnglish and Egyptian-English parallel corpora, consisting of 1.1M words and 380k words, respectively. The dialectal sentences are selected from a large corpus of Arabic web text, and translated using Amazon’s Mechanical Tur...

This paper describes the LIG experiments in the context of IWSLT09 evaluation (Arabic to English Statistical Machine Translation task). Arabic is a morphologically rich language, and recent experimentations in our laboratory have shown that the performance of Arabic to English SMT systems varies greatly according to the Arabic morphological segmenters applied. Based on this observation, we prop...

<span>The arabic sign language (ArSL) is the natural of deaf community in Arabic countries. ArSL suffers from a lack resources such as unified dictionaries and corpora. In this work, dictionary to has been constructed part translation system. The words are converted into hamburg notation system (HamNoSys) using eSign editor Software. HamNoSys was used create manual parameters (handshape, ...

We present a limited speech translation system for English and colloquial Levantine Arabic, which we are currently developing as part of the DARPA Babylon program. The system is intended for question/answer communication between an English-speaking operator and an Arabic-speaking subject. It uses speech recognition to convert a spoken English question into text, and plays out a pre-recorded spe...

Arabic Machine Translation (MT) has been widely studied recently. Any Arabic to English Machine Translation (MT) system should be capable of dealing with word order and agreement requirements, agreement rules are crucial for the generation of sentences in the target language. They also serve as rules for the ordering of sentence constituents. Transfer-based technique is currently one of the mos...

Translation of the output of automatic speech recognition (ASR) systems, also known as speech translation, has received a lot of research interest recently. This is especially true for programs such as DARPA BOLT which focus on improving spontaneous human-human conversation across languages. However, this research is hindered by the dearth of datasets developed for this explicit purpose. For Eg...

The Defense Advanced Research Projects Agency (DARPA) Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program has experimented with applying automated metrics to speech translation dialogues. For translations into English, BLEU, TER, and METEOR scores correlate well with human judgments, but scores for translation into Arabic correlate with human judgments less ...

This paper describes the University of Maryland statistical machine translation system used in the IWSLT 2007 evaluation. Our focus was threefold: using hierarchical phrasebased models in spoken language translation, the incorporation of sub-lexical information in model estimation via morphological analysis (Arabic) and word and character segmentation (Chinese), and the use of n-gram sequence m...

Machine Translation (MT) systems are now in active use around the world. This paper investigates the applicability of current and foreseeable MT technology to translation between one or more of modern Western European languages and Arabic. After an introduction in which we briefly sketch the history and current status of MT and comment on the situation vis-a-vis Arabic translation, we present s...

We report the results of our work on automating the transliteration decision of named entities for English to Arabic machine translation. We construct a classification-based framework to automate this decision, evaluate our classifier both in the limited news and the diverse Wikipedia domains, and achieve promising accuracy. Moreover, we demonstrate a reduction of translation error and an impro...