LIRA, D. G.; http://lattes.cnpq.br/6841858244612470; LIRA, Deivid Gomes.
Resumen:
The use of machine translation systems has been increasingly recurrent in the commercial
field since the late 1990s (CASTELL, 1999; HUTCHINS, 2000). The adoption of these
systems in the academic and domicile sphere has also become more frequent soon after
the arrival of digital societies, achieving more impetus in the 21st century because of the
technological advance and the internet boom (SMITH, 2001; WEININGER 2004;
KOHEN 2010, KUHN, 2013, SANTOS 2017, GOMES, 2018). Taking into account such
an increase in machine translation users, a German researcher called Kohen (2010)
classified the uses of these systems into three categories: a) assimilation, b)
communication and c) publication. Currently, these categories are the ones to rule
wherever and whenever machine translation systems are in use (SANTOS, 2014). In view
of such a categorization, as well as the increasing demand of users of these systems, this
study aimed at investigating the most frequent categories of machine translation use in
the academic sphere at UFCG, followed by the systems in use in such a context and the
kind of users of those systems. For that purpose, two groups of machine translation
potential users in the academic context answered two research questionnaires: teachers
and students. Regarding the results, both groups of respondents chose Google Translate
as the most used system in their academic daily situations, among other systems such as
systran, bing, linguee, babylon, translator and voice translator. On the one hand, text
assimilation from English into Portuguese revealed to be the most frequent use category
among the group of students. On the other hand, among teachers publication was the most
frequent one. In that specific case, publication took place as a means for planning and
documentation of material used along classes. Although some of the respondents
mentioned the communication category, it was not so recurrent among the analyzed data.
