An Arabic name can be written in English with many different spellings. For example, the name Sulayman is written only one way in Arabic. In English, this name is written in as many as forty different ways, such as Salayman, Seleiman, Solomon, Suleiman, and Sylayman. Currently, Arabic linguists manually transliterate these names—a slow, laborious, error-prone, and time-consuming process. We present a hybrid algorithm which automates this process in real time using neural networks and a knowledge-based system to vowelize Arabic. A supervised neural network filters out unreliable names, passing the reliable names on to the knowledge-based system for romanization. This approach, developed at the IBM Federal Systems Company, is applicable to a wide variety of purposes, including visa processing and document processing by border patrols.
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