Agent Based Arabic Language Understanding

Arabic Language understanding (ALU) computing is considered an AI-hard task. In this paper, we propose an Agent model for ALU problem. This agent is detailed in this paper. An ALU system is developed for 'Voice Activated Drawing Interface'. Our experiment shows that agent-based ALU can be very robust and reliable in comparison to text analysis by using rules of Arabic language, parts of speech and structure of sentence. Keywords Language understanding, Hidden Markov Model (HMM), Semantic, and Tagging.

• Type: Conference
• Year: 2007
• Where: IAT
• Authors: Muhammad Taha, Tarek Helmy, Reda Abo Alez
• Keywords: Agent-based Alu, ALU Problem, Arabic Language, IAT 2007, Intelligent Agent