This paper discusses several issues in Arabic orthography that were encountered in the process of performing morphology analysis and POS tagging of 542,543 Arabic words in three newswire corpora at the LDC during 2002-2004, by means of the Buckwalter Arabic Morphological Analyzer. The most important issues involved variation in the orthography of Modern Standard Arabic that called for specific ...

This paper describes the collect and transcription of a large set of Arabic broadcast news speech data. A total of more than 2000 hours of data was transcribed. The transcription factor for transcribing the broadcast news data has been reduced using a method such as Quick Rich Transcription (QRTR) as well as reducing the number of quality controls performed on the data. The data was collected f...

This paper presents initial results regarding writing activities in the context of the ALADDIN project. The goal of the project is to teach Modern Standard Arabic in 5-year-old kindergarten students in Qatar. A total of 18 students, enrolled in the ‘Arabic Class’, participated for 9 weeks in the activities of the project. All students were native speakers of the Qatari dialect. Learning activit...

This paper investigates the unique pharyngeal and uvular consonants of Arabic from the point of view of automatic speech recognition (ASR). 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 discussed. ...

Segmentation of clitics has been shown to improve accuracy on a variety of Arabic NLP tasks. However, state-of-the-art Arabic word segmenters are either limited to formal Modern Standard Arabic, performing poorly on Arabic text featuring dialectal vocabulary and grammar, or rely on linguistic knowledge that is hand-tuned for each dialect. We extend an existing MSA segmenter with a simple domain...

Most Arabic natural language processing tools and resources are developed to serve Modern Standard Arabic (MSA), which is the official written language in the Arab World. Some Dialectal Arabic varieties, notably Egyptian Arabic, have received some attention lately and have a growing collection of resources that include annotated corpora and morphological analyzers and taggers. Gulf Arabic, howe...

Speakers of widespread languages may encounter problems in information retrieval and document understanding when they access documents in the same language from another country. The work described here focuses on the development of resources to support improved document retrieval and understanding by users of Modern Standard Arabic (MSA). The lexicon of an Egyptian Arabic speaker and the lexico...

The automatic recognition of foreign-accented Arabic speech is a challenging task since it involves a large number of nonnative accents. As well, the nonnative speech data available for training are generally insufficient. Moreover, as compared to other languages, the Arabic language has sparked a relatively small number of research efforts. In this paper, we are concerned with the problem of n...

To date, majority of research for Arabic Named Entity Recognition (NER) addresses the task for Modern Standard Arabic (MSA) and mainly focuses on the newswire genre. Despite some common characteristics between MSA and Dialectal Arabic (DA), the significant differences between the two language varieties hinder such MSA specific systems from solving NER for Dialectal Arabic. In this paper, we pre...

Arabs throughout the Arab world speak different dialects of Arabic in their daily conversations. We envision collecting a data set that maps different Arabic variations and dialects to Modern Standard Arabic (MSA). These mappings can be then used to facilitate the communication among Arabs from different regions. In this work, we developed a Game With A Purpose (GWAP) to collect mappings betwee...