The Translation of Metaphors: An MTPE Analysis

Abstract

This research analyzes the machine translations of metaphors from English to Arabic. It aims to identify the translation methods that result from Google Translate of translating metaphors and to determine the extent to which the machine can effectively help in translating metaphors. In addition, the research categorizes the MTPE skills required after using the machine to translate metaphors. The research is analytical descriptive. The study sample consisted of 28 sentences that were carefully selected, then presented to specialists who extracted 20 sentences from them. On the other hand, Google Translate was the MT engine selected for its availability, popularity and continuous improvement. For the purpose of data collection, 20 sentences were entered into Google Translate, corrected and subjected to post editing. The results show that the translations of Google Translate were literal (75%), semantic (10%), and functional (15%). Google Translate failed to translate metaphors effectively. The researchers categorize MTPE skills and analyze metaphors and correct wrong sentences using some translation strategies (omission, addition, substitution, paraphrasing, approximation, and modulation). The research recommends that students do not rely on Google Translate for translating metaphors and that they use other translation engines. It is also recommended that students should focus on MTPE skills to help them correct their translations when they utilize machine translation.