Machine Translation-Friendly Language for Improved Machine Translation Output in Academic Writing

Academic writing aims to disseminate scholarly knowledge to a target audience in concise language. During this process, translators sometimes translate academic texts into foreign languages, so that the output of scholarly research can be read by speakers of different languages. In such cases, translators are to translate the source text into the target language in a clear and comprehensible language. This paper discusses how the authors of scholarly texts can structure their writing properly, so that they can help translators compose clear and concise translation output. Although the knowledge and skills of the translator are a key consideration in ensuring the quality of translated texts, the source text itself is highly influential in the quality of the output. Furthermore, although they might partially differ from one language to another, academic writing has some well-established conventions. Therefore, translators might experience some problems when they translate scholarly texts. This study aims to pinpoint such issues and to offer viable strategies that could be used for solving them before the translation process. Commonly encountered problems that impair the quality of the translation output are as follows: wordiness, ambiguous expressions, failing to consider the discourse structure of the target language while organising the source text, using conjunctions carelessly, using the passive voice unnecessarily, using indirect language to express ideas, using synonymous words sequentially, typos, and other similar problems. Though experience in academic translation can help solve some of these issues, it might not be possible to produce good translation output if the source text is poorly written. Success in academic translation can be achieved through collaboration between the author of an academic text and its translator. For this reason, it is necessary to raise the awareness of writers and translators on this issue.