Machine Transliteration

Machine Transliteration Kevin Knight and Jonathan Graehl Information Sciences Institute University of Southern California Marina del Rey, CA 90292 knight~isi, edu, graehl@isi, edu Abstract It is challenging to translate names and technical terms across languages with differ- ent alphabets and sound inventories. These items are commonly transliterated, i.e., re- placed with approximate phonetic equivalents. For example, computer in English comes out as ~ i/l:::'=--~-- (konpyuutaa) in Japanese. Translating such items from Japanese back to English is even more challenging, and of prac- tical interest, as transliterated items make up the bulk of text phrases not found in bilin- gual dictionaries. We describe and evaluate a method for performing backwards translitera- tions by machine. This method uses a gen- erative model, incorporating several distinct stages in the transliteration process. 1 Introduction 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 chal- lenge: a phrase like Antonio Gil usually gets trans- lated 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 translitera- tion. We will look at Japanese/English translitera- tion in this paper. Japanese frequently imports vocabulary from other languages, primarily (but not exclusively) from English. It has a special phonetic alphabet called katakana, which is used primarily (but not exclusively) to write down foreign names and loan- words. To write a word like golf bag in katakana, some compromises must be made. For example, Japanese has no distinct L and R sounds: the two En- glish sounds collapse onto the same Japanese sound. A similar compromise must be struck for English H and F. Also, Japanese generally uses an alter- nating consonant-vowel structure, making it impos- sible to pronounce LFB without intervening vow- els. Katakana writing is a syllabary rather than an alphabet--there is one symbol for ga (~I), another for gi (4e), another for gu (P'), etc. So the way to write gol]bag in katakana is =~'~ 7 ~ ~, ~, roughly pronounced goruhubaggu. Here are a few more ex- amples: Angela Johnson TvzJ~ • "J~ vY v (anj ira jyonson) New York Times (nyuuyooku t aimuzu) ice cream T 4 x ~, ~) -- z, (aisukuriimu) Notice how the transliteration is more phonetic than orthographic; the letter h in Johnson does not pro- duce any katakana. Also, a dot-separator (.) is used to separate words, but not consistently. And transliteration is clearly an information-losing oper- ation: aisukuriimu loses the distinction between ice cream and I scream. Transliteration is not trivial to automate, but we will be concerned with an even more challeng- ing problem--going from katakana back to En- glish, i.e., back-transliteration. Automating back- transliteration has great practical importance in Japanese/English machine translation. Katakana phrases are the largest source of text phrases that do not appear in bilingual dictionaries or training corpora (a.k.a. "not-found words"). However, very …

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