Translating Names and Technical Terms in Arabic Text

It is challenging to translate names and technical terms from English into Arabic. Translation is usually done phonetically: different alphabets and sound inventories force various compromises. For example, Peter Streams may come out as hr..~ ~ bytr szrymz. This process is called transliteration. We address here the reverse problem: given a foreign name or loanword in Arabic text, we want to recover the original in Roman script. For example, an input like .~..A~ bytr strymz should yield an output like Peter Streams. Arabic presents special challenges due to unwritten vowels and phonetic-context effects. We present results and examples of use in an Arabic-to-English machine translator. Introduction It is not trivial to write an algorithm for turning Translators must deal with many problems, and one of the most frequent is translating proper names and technical terms. For language pairs like Spanish/English, this presents no great challenge: a phrase like Antonio Gil usually gets translated as Antonio Gil. However, the situation is more complicated for language pairs that employ very different alphabets and sound systems, such as Japanese/English and Arabic/English. Phonetic translation across these pairs is called transliteration. (Knight and Graehl, 1997) present a computational treatment of Japanese/English transliteration, which we adapt here to the case in Arabic. Arabic text, like Japanese, frequently contains foreign names and technical terms that are translated phonetically. Here are some examples from newspaper text: a