An Investigation into the English Translation of Persian Homographic Homophones in Google Translate

One of the most commonly used Machine Translation (MT) systems is Google Translate, which supports 64 languages, including Persian. As Google Translate is easily accessible, it is almost always the first MT system to which Iranian users resort to meet their translation needs. This study attempted to investigate how Google translates homographic homophones, in the first place to reach the statistical results about Google translator engine accuracy in translating homographic homophones. Thus, calculating the percentage of successful translation of homographic homophones by Google Translate was one major objective of the study. Also, this study aimed to determine whether Google Translate was trustworthy in translating homographic homophones. To fulfill this objective, descriptive qualitative methods were selected. The corpus was extracted from Mo’in Encyclopedic Dictionary (2015) which consisted of 114 selected homographic homophones. To evaluate the translation quality of the homographic homophones in terms of accuracy and truth worthiness, the translation quality framework proposed by Nababan, Nuraeni and Sumardiono (2012) was adopted. Descriptive statistics containing frequency and percentage were calculated. The results showed out of 114 predetermined cases of the words, only 6% were translated accurately and in complete correspondence with the real translation of the intended words in different contexts. However, 64.9% of the translated words were found to be inaccurate and incompatible with the intended meaning of the given context. Also, among 260 different contexts in which the intended homographic homophones were used, Google Translate could only differentiate between the semantics of 21.15% of homographic homophones.