Human-Robots And Google Translate: A Case Study Of Translation Accuracy In Translating French-Indonesian Culinary Texts

Abstract

Google Translate (GT) is the most widely used translator application in the world. The function of GT is not merely as tools but has become a means in personal communication, learning and business matters. This paper aims to examine the GT accuracy in translating culinary texts. This paper used a semiotic approach to analyze the equivalence of GT from the source language to the target language. The data source as the object of study is French culinary texts retrieved from the internet. It can be concluded that the accuracy of GT in culinary texts lies in words, phrases and sentences. GT does not yet have good accuracy in translating culture between source and target languages. In the semiotic perspective, the GT translation model is the translation from the source language form to the target language form (signifier) by maintaining the concept (meaning). GT does not yet have a translation feature in a cultural context. The advancement in information technology shows that GT, as a human-robot, can replace human translators.

The Impact of Artificial Intelligence on Language Translation: A Review

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“…The credibility of the test datasets and the validity of both human and machine evaluation standards were investigated. Maintaining the efficacy and legitimacy of MTE techniques requires regular introspection [82].…”