Metadiscourse features are those facets of a text, which make the organization of the text explicit, provide information about the writer's attitude toward the text content, and engage the reader in the interaction. This study interpreted metadiscourse markers in translated and non-translated persuasive texts. To this end, the researcher chose the translated versions of one of the leading newsp...

this study focused on the role of appropriate equivalence selection of colors in the field of advanced pranic healing (aph), based on mona baker’s equivalence, both at word level and above word level. the partici- pants included 40 bachelor’s students studying in the field of english translation. participants received the colors’ translation test (ctt) included in the book “advanced pranic heal...

The purposes of this study were (a) to compare BA and MA students of Translation in terms of their abilities in IT skills, (b) to compare them in terms of their learning of IT related competences in the translator training programs, and (c) to compare their viewpoints about the importance of IT skills in their professional activities. The participants of this research were Iranian male and fema...

Post-Editing of Machine Translation (MT) has become a reality in professional translation workflows. In order to optimize the management of projects that use post-editing and avoid underpayments and mistrust from professional translators, effective tools to assess the quality of Machine Translation (MT) systems need to be put in place. One field of study that could address this problem is Machi...

Increasingly, large bilingual document collections are being made available online, especially in the legal domain. This type of Big Data is a valuable resource that specialized translators exploit to search for informative examples of how domain-specific expressions should be translated. However, general purpose search engines are not optimized to retrieve previous translations that are maxima...

Active learning is a framework that makes it possible to efficiently train statistical models by selecting informative examples from a pool of unlabeled data. Previous work has found this framework effective for machine translation (MT), making it possible to train better translation models with less effort, particularly when annotators translate short phrases instead of full sentences. However...