The Arabic language has a very rich morphology where a word is composed of zero or more prefixes, a stem and zero or more suffixes. This makes Arabic data sparse compared to other languages, such as English, and consequently word segmentation becomes very important for many Natural Language Processing tasks that deal with the Arabic language. We present in this paper two segmentation schemes th...

The cursive and ligature nature of the Arabic language make the segmentation of words into individual characters a difficult task. Despite attempts to apply methods for cursive Latin and other languages to Arabic, it is generally insufficient to segment Arabic text. This paper proposes a new segmentation algorithm for handwritten Arabic text and the main idea consist of segmenting the word into...

The absence of the vowelization marks from the modern Arabic text represents a major obstacle in machine translation and other text understanding applications. In this paper we present a formulation of the problem of automatic generation of the Arabic diacritic marks from unvoweled text using a Hidden Markov Model (HMM) approach. The model considers the word sequence of unvoweled Arabic text as...

In this work we present our expert system of speech synthesis based on a text written in Standard Arabic, our work is carried out in two great stages: the creation of the sound data base, and the transformation of the written text into speech (Text To Speech TTS). This transformation is done firstly by a Phonetic Orthographical Transcription (POT) of any written Standard Arabic text that to tra...

In the present research work, we deal with the problem of authorship attribution of ancient Arabic text documents, which were written by several ancient philosophers. For that purpose, we conducted several authorship attribution experiments applied with different text sizes. A special dataset, called “A4P” (Authorship Attribution for Ancient Arabic Philosophers), has been constructed by extract...

Because of the different characteristics of Arabic language and Romance and Anglo Saxon languages, recognition of documents written in hybrid of these languages requires that the language of the text to be identified priori to the recognition phase. In this paper, three efficient techniques that can be used to discriminate between text written in Arabic script and text written in English script...

This paper addresses the problem of the development of Arabic Natural Language Interface for Information System Design. Most Arabic systems focus on processing Arabic text for machine translation or information retrieval. We present in this paper some aspects for identify Entities and Relationships from a description of the application domain given with a subset of the Arabic Natural Language. ...

This paper describes the development of an Arabic broadcast news transcription system. The presented system is a speaker-independent large vocabulary natural Arabic speech recognition system, and it is intended to be a test bed for further research into the open ended problem of achieving natural language man-machine conversation. The system addresses a number of challenging issues pertaining t...

Text categorization is the process of grouping documents into categories based on their contents. This process is important to make information retrieval easier, and it became more important due to the huge textual information available online. The main problem in text categorization is how to improve the classification accuracy. Although Arabic text categorization is a new promising field, the...

To our knowledge, there are only few systems that are able to automatically translate handwritten text images into another language, in particular, Arabic. Typically, the available systems are based on a concatenation of two systems: a Handwritten Text Recognition (HTR) system and a Machine Translation (MT) system. Roughly speaking, in the case of recognition of Arabic text images, our work has...