TRACING THE FOOTPRINT OF WORLD ENGLISHES ON MACHINE TRANSLATION TOOLS

Abstract

With the rise in the population who uses English as a Foreign or Second lan- guage, World Englishes has become more focus of English language teaching field specialists. As a consequence, English varieties which are present in supplementary tools used in the process of language teaching and learning took on a new mea- ning. As one of the commonly used supplementary tools is machine translation tools, the current study aims to explore the machine translation outputs tendency considering grammar-based, spelling-based, and lexical variations between varie- ties of Englishes regarding Google Translate outputs. Source texts were extracted from Turkish National Corpus. A total of seventy-three Turkish to English machi- ne translation outputs were examined regarding two dominant varieties, American English and British English, with the aim of figuring out the machine translation tendency of translation outputs. The analysis of the research showed that Google Translate provides users with mostly American English compared to British English.