Incorporating Human Translator Style into English-Turkish Literary Machine Translation

• URL: http://arxiv.org/abs/2307.11457v1
• Date: Fri, 21 Jul 2023 09:39:50 GMT
• Title: Incorporating Human Translator Style into English-Turkish Literary Machine Translation
• Authors: Zeynep Yirmibe\c{s}o\u{g}lu, Olgun Dursun, Harun Dall{\i}, Mehmet \c{S}ahin, Ena Hodzik, Sabri G\"urses, Tunga G\"ung\"or
• Abstract summary: We develop machine translation models that take into account the stylistic features of translators. We show that the human translator style can be highly recreated in the target machine translations.
• Score: 0.26168876987285306
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Although machine translation systems are mostly designed to serve in the general domain, there is a growing tendency to adapt these systems to other domains like literary translation. In this paper, we focus on English-Turkish literary translation and develop machine translation models that take into account the stylistic features of translators. We fine-tune a pre-trained machine translation model by the manually-aligned works of a particular translator. We make a detailed analysis of the effects of manual and automatic alignments, data augmentation methods, and corpus size on the translations. We propose an approach based on stylistic features to evaluate the style of a translator in the output translations. We show that the human translator style can be highly recreated in the target machine translations by adapting the models to the style of the translator.

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