Post-editing strategies in automatic translation of proverbs by FFL and translation learners

Abstract

This research aims to analyze the strategies used in the post-editing of proverbs translated automatically from French into Arabic by French as a Foreign Language (FFL) learners. We will first present the theoretical foundations of machine translation of proverbs as well as the state of the art. The study uses a mixed methodological approach. The quantitative method includes a questionnaire distributed for FFL students to find out the most used translation tool in machine translation. The qualitative method focuses on collecting data on translation errors as well as on directly observing the strategies implemented in the post-editing of proverbs translated by Google Translate. The results of the study show that Google Translate is the most widely used tool in translation and that errors in machine translation are syntactic, lexical, semantic, and stylistic. The strategies implemented in the post-edition are varied such as splitting proverbs into linguistic units for the search of their meanings, using a pivot language, namely English to know the meaning of proverbs and searching for equivalents in reference resources. The study concludes that although the automatic translation of proverbs into distant language pairs such as the French-Arabic pair appears complex, Google Translate has been a tool to help an FFL learner to understand the meaning of proverbial expressions, to find their equivalents and to post-edit them.

Keywords:
Strategies; Proverbs; Machine translation; French as a foreign language; Post-edition