A comparative study on google translate: An error analysis of Turkish-to English translations in terms of the text typology of Katherina Reiss

Abstract

Machine Translation (MT) has become one of the
 important topics of public interest especially with the advent of technology
 and the blooming need for translation. Google
 Translate, as an MT, provides quick translations; however, the quality of
 the texts often remains unsatisfactory. This study aims to analyze the
 translation errors of Google Translate
 outputs conducted from Turkish into English. The errors are classified into
 four major categories: Lexical Errors,
 Morphological Errors, Syntactic Errors, Semantic and Pragmatic Errors,
 which include subcategories. In parallel with the aim of the study, a text from
 each of the three text types put forward by Katherina Reiss (1971), was chosen
 to be translated by Google Translate and to be analyzed. These text types are Informative Texts, Expressive Texts, and Operative Texts. In the study, firstly
 it is aimed to explore which of the main text types has more translation
 errors, secondly, whether the translation error types vary by the main text
 types or not. In order to deal with
 this, both quantitative and qualitative analyses are utilized in the study. The
 data analysis revealed that the main text type that has more translation errors
 is the translation of operative text and expressive text,
 respectively. It is also observed that the error pattern between the text types
 was different. The informative text mainly includes lexical errors,
 whereas operative and expressive mainly include semantic and pragmatic
 errors. Summing up the results, it can be concluded that although Google Translate provides
 much quicker translations among a large number of languages, there is still a
 need for human assistance.