Machine translation post-editing – Current situation and the future of translator training in Bulgaria

The current paper is an attempt to analyse the situation on the market for specialised translation services, and more precisely for Machine Translation in Bulgaria. It provides an overview of some of the generic MT systems and analyses the results coming from the translation of two types of text. The aim of the paper is to raise awareness about the results of Neural Machine Translation and to reveal the need for MT post-editing courses.

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Is automation changing the translation profession?

International Journal of the Sociology of Language ◽

10.1515/ijsl-2020-0015 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Anthony Pym ◽

Ester Torres-Simón

Keyword(s):

Machine Translation ◽

Communication Skills ◽

Service Providers ◽

Time Data ◽

Market Segments ◽

Interactive Communication ◽

Neural Machine Translation ◽

History Of ◽

Translation Services ◽

Translation Systems

Abstract As a language-intensive profession, translation is of frontline interest in the era of language automation. In particular, the development of neural machine translation systems since 2016 has brought with it fears that soon there will be no more human translators. When considered in terms of the history of automation, however, any such direct effect is far from obvious: the translation industry is still growing and machine translation is only one instance of automation. At the same time, data on remuneration indicate structural wage dispersion in professional translation services, with some signs that this dispersion may increase in certain market segments as automated workflows and translation technologies are adopted more by large language-service providers more than by smaller companies and individual freelancers. An analysis of recent changes in discourses on and in the translation profession further indicates conceptual adjustments in the profession that may be attributed to growing automation, particularly with respect to expanding skills set associated with translation, the tendency to combine translation with other forms of communication, and the use of interactive communication skills to authorize and humanize the results of automation.

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POSTEDITING IN MACHINE TRANSLATION

Naukovy Visnyk of South Ukrainian National Pedagogical University named after K D Ushynsky Linguistic Sciences ◽

10.24195/2616-5317-2020-30-7 ◽

2020 ◽

Vol 2020 (30) ◽

pp. 102-119

Author(s):

Tetiana Korolova ◽

Natalya Zhmayeva ◽

Yulia Kolchah

Keyword(s):

Machine Translation ◽

Grammatical Structure ◽

Incorrect Choice ◽

Neural Machine Translation ◽

Translation Quality ◽

Modern Methods ◽

Translation Services ◽

Linguistic Units ◽

Source Message ◽

Language Pair

Modern industry of translation services singles out two translation quality levels that can be reached as a result of machine translation (MT) post-editing: good enough quality foresees rendering the main information of the source message, admitting stylistic, syntactic and morphological flaws while quality similar or equal to human translation is a full dress version of a post-edited text, ready to be published. The overview of MT systems enables us to consider Google Neural Machine Translation (GNMT) which is based on the most modern methods of training to reach maximum improvements the most powerful one. When analyzing texts translated by means of Google Translate the following problems were identified: distortion of the referential meaning of the source message, incorrect choice of variant equivalences, lack of terms harmonization, lack of abbreviations rendering, inconformity of linguistic units in persons, numbers and cases, incorrect choice of functional correspondings when rendering absolute constructions, gerund and participial constructions, literal translation of phrases, lack of transformations of the grammatical structure of the source message (additions, rearrangements). Taking into account the classified issues of machine translation as well as the levels of post-editing quality post-editing of the texts translated by means of MT is carried out, demands and recommendations applicable to post-editing results of MT within the language pair under analysis with respect to peculiarities of the specific MT system and the type of translated texts are provided.

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