Arabic diacritics are often missed in Arabic scripts. This feature is a handicap for new learner to read َArabic, text to speech conversion systems, reading and semantic analysis of Arabic texts. The automatic diacritization systems are the best solution to handle this issue. But such automation needs resources as diactritized texts to train and evaluate such systems. In this paper, we describe ...

Language Engineering, including Information Retrieval, Machine Translation and other Natural Language-related disciplines, is showing in recent years more interest in the Arabic language. Suitable resources for Arabic are becoming a vital necessity for the progress of this research. Until recently, only two Arabic corpora were commonly available for researchers: the AFP Arabic newswire from LDC...

The written form of Arabic, Modern Standard Arabic (MSA), differs quite a bit from the spoken dialects of Arabic, which are the true “native” languages of Arabic speakers used in daily life. However, due to MSA’s prevalence in written form, almost all Arabic datasets have predominantly MSA content. We present the Arabic Online Commentary Dataset, a 52M-word monolingual dataset rich in dialectal...

This paper presents a multi-dialect, multi-genre, human annotated corpus of dialectal Arabic with data obtained from both online newspaper commentary and Twitter. Most Arabic corpora are small and focus on Modern Standard Arabic (MSA). There has been recent interest, however, in the construction of dialectal Arabic corpora (Zaidan and Callison-Burch, 2011a; Al-Sabbagh and Girju, 2012). This wor...

Parsing of Arabic sentences is a necessary mechanism for many natural language processing applications such as machine translation; question answering, knowledge extraction and information retrieval. In this study, we present a top-down chart parser for parsing simple Arabic sentences, including nominal and verbal sentences within specific domain Arabic grammar. We used the Context Free Grammar...

This paper investigates the unique pharyngeal and uvular consonants of Arabic from the automatic speech recognition (ASR) point of view. Comparisons of the recognition error rates for these phonemes are analyzed in five experiments that involve different combinations of native and non-native Arabic speakers. The most three confusing consonants for every investigated consonant are uncovered and ...

This paper addresses issues related to employing logic-based semantic composition as a meaning representation for Arabic within a unification-based syntax-semantics interface. Since semantic representation has to be compositional on the level of semantic processing λ-calculus based on Discourse Representation Theory can be utilized as a helpful and practical technique for the semantic construct...

We propose an enhanced Part-of-Speech (POS) tagger of Semitic languages that treats Modern Standard Arabic (henceforth Arabic) and Modern Hebrew (henceforth Hebrew) using the same probabilistic model and architectural setting. We start out by porting an existing Hidden Markov Model POS tagger for Hebrew to Arabic by exchanging a morphological analyzer for Hebrew with Buckwalter's (2002) morphol...

This presentation is primarily a demonstration of a working statistical machine translation system which translates Modern Standard Arabic into English.