In the Arab world, while Modern Standard Arabic is commonly used in formal written context, on sites like Youtube, people are increasingly using Dialectal Arabic, the language for everyday use to comment on a video and interact with the community. These user-contributed comments along with the video and user attributes, offer a rich source of multi-dialectal Arabic sentences and expressions fro...

We introduce a generic Language Independent Framework for Linguistic Code Switch Point Detection. The system uses the word length, character level (1, 2, 3, 4, and 5)-grams and word level unigram language models to train a conditional random fields (CRF) model for classifying input words into various languages. We test our proposed framework and compare it to the state-of-theart published syste...

In this paper, we present a statistical machine translation system for English to Dialectal Arabic (DA), using Modern Standard Arabic (MSA) as a pivot. We create a core system to translate from English to MSA using a large bilingual parallel corpus. Then, we design two separate pathways for translation from MSA into DA: a two-step domain and dialect adaptation system and a one-step simultaneous...

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...

This paper focuses on a project for building the first International Corpus of Arabic (ICA). It is planned to contain 100 million analyzed tokens with an interface which allows users to interact with the corpus data in a number of ways [ICA website]. ICA is a representative corpus of Arabic that has been initiated in 2006, it is intended to cover the Modern Standard Arabic (MSA) language as bei...

Modern Hebrew and Modern Standard Arabic, both Semitic languages, share many orthographic, lexical, morphological, syntactic and semantic similarities, but they are still not mutually comprehensible. Most native Hebrew speakers in Israel do not speak Arabic, and the vast majority of Arabs (outside Israel) do not speak Hebrew. Machine translation (MT) between these two language has the potential...

The Arabic language is morphologically rich and syntactically complex with many differences from European languages, and this creates a challenge when porting existing annotation tools to Arabic. In this paper, we present an ongoing effort in lexical semantic analysis and annotation of Modern Standard Arabic (MSA) text, a semi automatic annotation tool concerned with the morphologic, syntactic,...

this paper presents an efficient mechanism to convert sana’ani dialect to modern standard arabic. the mechanism is based on morphological rules related to sana’ani dialect as well as modern standard arabic. such rules facilitate the dialect conversion to its corresponding msa. the mechanism tokenizes the input dialect text and divides each token into stem and its affixes; such affixes can be ca...

If unsupervised morphological analyzers could approach the effectiveness of supervised ones, they would be a very attractive choice for improving MT performance on low-resource inflected languages. In this paper, we compare performance gains for state-of-the-art supervised vs. unsupervised morphological analyzers, using a state-of-theart Arabic-to-English MT system. We apply maximum marginal de...