In TREC-10 the Berkeley group participated only in the English-Arabic cross-language retrieval (CLIR) track. One Arabic monolingual run and four English-Arabic cross-language runs were submitted. Our approach to the cross-language retrieval was to translate the English topics into Arabic using online EnglishArabic bilingual dictionaries and machine translation software. The five official runs a...

A comparison between the performance of Latin and Arabic handwritten digits recognition problems is presented. The performance of ten different classifiers is tested on two similar Arabic and Latin handwritten digits databases. The analysis shows that Arabic handwritten digits recognition problem is easier than that of Latin digits. This is because the interclass difference in case of Latin dig...

In this paper, we present a generic Optical Character Recognition system for Arabic script languages called Nabocr. Nabocr uses OCR approaches specific for Arabic script recognition. Performing recognition on Arabic script text is relatively more difficult than Latin text due to the nature of Arabic script, which is cursive and context sensitive. Moreover, Arabic script has different writing st...

As more and more Arabic textual information becomes available through the Web in homes and businesses, via Internet and Intranet services, there is an urgent need for technologies and tools to process the relevant information. Named Entity Recognition (NER) is an Information Extraction task that has become an integral part of many other Natural Language Processing (NLP) tasks, such as Machine T...

This paper presents a novel holistic technique for classifying and retrieving Arabic handwritten text documents. The retrieval of Arabic handwritten documents is performed in several steps. First, the Arabic handwritten document images are segmented into words, and then each word is segmented into its connected parts. Second, several features are extracted from these connected parts and then co...

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 ...

In this paper, we present recognition of handwritten characters of Arabic script. Arabic is now the 6 most spoken language in the world and is spoken by more than 200 million people worldwide. The 7 Century A.D., Arabic started to spread to the Middle East as many people started to convert to Islam. During this time of religious conversions, Arabic replaced many South Arabian languages, most of...

In this paper, Arabic was investigated from the speech recognition problem point of view. We propose a novel approach to build an Arabic automated speech recognition system using Arabic environment. The system, based on the open source CMU Sphinx-4, was trained using Arabic characters.

Developments in Arabic information retrieval did not follow the increasing use of the Arabic Web during the last decade. Semantic indexing in a language with high inflectional morphology, such as Arabic, is not a trivial task and requires a text analysis in the original language. Excepting cross-language retrieval methods or limited studies, the main efforts, for developing semantic analysis me...

Natural language processing technology for the dialects of Arabic is still in its infancy, due to the problem of obtaining large amounts of text data for spoken Arabic. In this paper we describe the development of a part-of-speech (POS) tagger for Egyptian Colloquial Arabic. We adopt a minimally supervised approach that only requires raw text data from several varieties of Arabic and a morpholo...