Arabic NLP

Arabic NLP studies how computers can analyze and generate Arabic, including its rich morphology, varied scripts, and relationship between Modern Standard Arabic and regional dialects. Common approaches include Arabic-pretrained encoders, adapted multilingual and generative language models, retrieval and structured prediction, alongside speech recognition, translation, and text-generation systems. Benchmarks and datasets cover tasks such as parsing, question answering, safety, medical and legal reasoning, dialectal dialogue, and speech, with evaluation increasingly attentive to cultural context and fine-grained linguistic abilities. A central challenge is that strong results on standardized written Arabic often do not transfer to dialects, specialized domains, or noisy speech, while data coverage and reliable evaluation remain uneven.