Revealing Translators' Knowledge: Statistical Methods in Constructing Practical Translation Lexicons for Language and Speech Processing

Abstract

Parallel corpora encode extremely valuable linguistic knowledge about paired languages, both in terms of vocabulary and syntax. A professional translation of a text represents a series of linguistic decisions made by the translator in order to convey as faithfully as possible the meaning of the original text and to produce a “natural” text from the perspective of a native speaker of the target language. The “naturalness” of a translation implies not only the grammaticality of the translated text, but also style and cultural or social specificity. We describe a program that exploits the knowledge embedded in the parallel corpora and produces a set of translation equivalents (a translation lexicon). The program uses almost no linguistic knowledge, relying on statistical evidence and some simplifying assumptions. Our experiments were conducted on the MULTEXT-EAST multilingual parallel corpus (Orwell's “1984”), and the evaluation of the system performance is presented in some detail in terms of precision, recall and processing time. We conclude by briefly mentioning some applications of the automatic extracted lexicons for text and speech processing.