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...

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...

The rise in Arabic usage within various social media platforms, and notably in Twitter, has led to a growing interest in building Arabic Natural Language Processing (NLP) applications capable of dealing with informal colloquial Arabic, as it is the most commonly used form of Arabic in social media. The unique characteristics of the Arabic language make the extraction of Arabic named entities a ...

This paper describes the process of creating a novel resource, a parallel Arabizi-Arabic script corpus of SMS/Chat data. The language used in social media expresses many differences from other written genres: its vocabulary is informal with intentional deviations from standard orthography such as repeated letters for emphasis; typos and nonstandard abbreviations are common; and nonlinguistic co...

Modern Standard Arabic (MSA) is the formal language in most Arabic countries. Arabic Dialects (AD) or daily language differs from MSA especially in social media communication. However, most Arabic social media texts have mixed forms and many variations especially between MSA and AD. This paper aims to bridge the gap between MSA and AD by providing a framework for AD classification using probabi...

Modern standard Arabic is usually written without diacritics. This makes it difficult for performing Arabic text processing. Diacritization helps clarify the meaning of words and disambiguate any vague spellings or pronunciations, as some Arabic words are spelled the same but differ in meaning. In this paper, we address the issue of adding diacritics to undiacritized Arabic text using a hybrid ...