In this paper we address the following questions from our experience of the last two and a half years in developing a large-scale corpus of Arabic text annotated for morphological information, part-of-speech, English gloss, and syntactic structure: (a) How did we ‘leapfrog’ through the stumbling blocks of both methodology and training in setting up the Penn Arabic Treebank (ATB) annotation? (b)...

We present an approach for automatic verification and augmentation of multilingual lexica. We exploit existing parallel and monolingual corpora to extract multilingual correspondents via triangulation. We demonstrate the efficacy of our approach on two publicly available resources: Tharwa, a three-way lexicon comprising Dialectal Arabic, Modern Standard Arabic and English lemmas among other inf...

_________________________________________________________________________________________________________ Speech clarity and coarticulatory effects in standard and dialectal Arabic This study deals with the co-variation of speech clarity and coarticulatory patterns. Two experiments were conducted to investigate the influence of two parameters, the speech style (formal vs. non formal) and the pr...

In this paper, we address the problem of the morphological analysis of an Arabic dialect. We propose a method to adapt an Arabic morphological analyzer for the Tunisian dialect (TD). In order to do that, we create a lexicon for the TD. The creation of the lexicon is done in two steps. The first step consists in adapting a Modern Standard Arabic (MSA) lexicon. We adapted a list of MSA derivation...

We have developed an experimental Arabic-to-English example-based machine translation (EBMT) system, which exploits a bilingual corpus to find examples that match fragments of the input source-language text--Modern Standard Arabic (MSA), in our case--and imitates its translations. Translation examples were extracted from a collection of parallel, sentencealigned, unvocalized Arabic-English docu...

There is a widely held belief in the natural language and computational linguistics communities that Semantic Role Labeling (SRL) is a significant step toward improving important applications, e.g. question answering and information extraction. In this paper, we present an SRL system for Modern Standard Arabic that exploits many aspects of the rich morphological features of the language. The ex...

Classical Arabic and Modern Standard Arabic have several relativization patterns, including relative clauses with and without relativizers and adjectival modification patterns. Previous generative work has targeted several phenomena, but there is no analysis which covers all relativization patterns in any generative framework. We present an HPSG analysis that covers these phenomena in a uniform...

In this paper we describe a system developed to identify a set of four regional Arabic dialects (Egyptian, Gulf, Levantine, North African) and Modern Standard Arabic (MSA) in a transcribed speech corpus. We competed under the team name MAZA in the Arabic Dialect Identification sub-task of the 2016 Discriminating between Similar Languages (DSL) shared task. Our system achieved an F1-score of 0.5...

This paper introduces a supervised approach for performing sentence level dialect identification between Modern Standard Arabic and Egyptian Dialectal Arabic. We use token level labels to derive sentence-level features. These features are then used with other core and meta features to train a generative classifier that predicts the correct label for each sentence in the given input text. The sy...

Proficiency testing is an important ingredient in successful language teaching. However, repeated testing for course placement, over the course of instruction or for certification can be time-consuming and costly. We present the design and validation of the Versant Arabic Test, a fully automated test of spoken Modern Standard Arabic, that evaluates test-takers' facility in listening and speakin...