Arabic Language Learning (ALL) for Kids

Supervised learning model for parsing Arabic language

Parsing the Arabic language is a difficult task given the specificities of this language and given the scarcity of digital resources (grammars and annotated corpora). In this paper, we suggest a method for Arabic parsing based on supervised machine learning. We used the SVMs algorithm to select the syntactic labels of the sentence. Furthermore, we evaluated our parser following the cross valida...

An Intelligent Computer Assisted Language Learning System for Arabic Learners

This paper describes the development of an intelligent computer-assisted language learning (ICALL) system for learning Arabic. This system could be used for learning Arabic by students at primary schools or by learners of Arabic as a second or foreign language. It explores the use of Natural Language Processing (NLP) techniques for learning Arabic. The learners are encouraged to produce sentenc...

SSML for Arabic Language

This paper introduces SSML for using with Arabic language. SSML is part of a larger set of markup specifications for voice browsers developed through the open processes of the W3C. The essential role of the markup language is to give authors of synthesizable content a standard way to control aspects of speech output such as pronunciation, volume, pitch, rate, etc. across different synthesis-cap...

The Kids Aren't All Right.

Sentiment Analysis in the Arabic Language Using Machine Learning

Sentiment Analysis in the Arabic Language Using Machine Learning Sentiment analysis has recently become one of the growing areas of research related to natural language processing and machine learning. Much opinion and sentiment about specific topics are available online, which allows several parties such as customers, companies and even governments, to explore these opinions. The first task is...