=Paper=
{{Paper
|id=Vol-2433/paper21
|storemode=property
|title=Features of the use of cloud-based translation systems in the process of forming information competence of translators
|pdfUrl=https://ceur-ws.org/Vol-2433/paper21.pdf
|volume=Vol-2433
|authors=Rostyslav O. Tarasenko,Svitlana M. Amelina,Albert A. Azaryan
}}
==Features of the use of cloud-based translation systems in the process of forming information competence of translators==
https://ceur-ws.org/Vol-2433/paper21.pdf
322
Features of the use of cloud-based translation systems in
the process of forming information competence of
translators
Rostyslav O. Tarasenko1[0000-0001-6258-2921], Svitlana M. Amelina1[0000-0002-6008-3122]
and Albert A. Azaryan2[0000-0003-0892-8332]
1 National University of Life and Environmental Sciences of Ukraine,
15, Heroiv Oborony Str., Kyiv, 03041, Ukraine
r_tar@nubip.edu.ua, svetlanaamelina@ukr.net
2 Kryvyi Rih National University, 11, Vitali Matusevich Str., Kryvyi Rih, 50027, Ukraine
azaryan325@gmail.com
Abstract. The current trends in the translator training are shown, which reflect
the orientation towards the use of cloud-based automated translation systems.
The possibilities of studying cloud-based translation systems in the educational
process of training the translator are considered. The role of mastering modern
translation tools for forming information competence of translators, particularly
technological component, was described. The definition of the list and type of
basic translation tools that should be mastered in the studying process was
discussed. These tools should include automated translation systems and
terminological management systems. It is advisable to provide for the study of
both desktop and cloud-based systems. The inclusion in the content of the
training translators the study of cloud-based systems of automated translation
after desktop systems is proposed. A number of advantages of cloud-based
translation systems for the use in the process of training the translators is defined
and substantiated. A comparative analysis of the functional of cloud-based
automated translation systems (Wordfast Anywhere, XTM Cloud, and
MemSource) with the aim of including them in the content of the training
program for translators has been carried out.
Keywords: information competence, computer-assisted translation (CAT),
cloud-based translation system, translation memory database, terminology
database, studying, translator.
1 Introduction
The system of professional training the modern translator should be aimed at the
formation of a number of professionally significant competencies. The list of these
competencies in terms of name and content may vary significantly depending on
various factors, in particular, the characteristics of the educational system of a particular
country, the content of educational programs for the training translators for different
institutions of higher education, etc. This program involves the formation of five core
___________________
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0).
323
competencies [6]. The essence of one of these competencies, technological (tools and
applications), is, among other things, the acquisition of knowledge of the effective use
of automated translation systems (CAT systems) in solving professional problems [2].
A similar aspect of the requirements for the results of professional training of a
translator on the ability to apply innovative technologies in translation based on the use
of information technologies is also reflected in the International standard for providing
translation services ISO 17100:2015 “Translation Services. Requirements for
translation services”. In this standard, this is indicated by the technical competence of
the translator, which means having the knowledge, skills and abilities necessary to
perform technical tasks in the translation process by applying tools and IT systems that
support the entire translation process [11].
2 The purpose of the article
The purpose of the article is to consider the possibilities of studying cloud-based
translation systems in the educational process of training the translator and to determine
their advantages and limitations (on the example of Wordfast Anywhere, XTM Cloud,
and MemSource).
3 Literature review
Today, cloud technologies are developing very rapidly [13; 18]. Translators can choose
from a wide variety of professional cloud-based translation memory products. The
cloud-based translation memory systems are more convenient and easier to use than
traditional desktop systems. The characteristics of cloud-based translation memory
systems are game-changers for freelance translators, as well as for small and medium-
sized language service provider businesses [15]. Translators will still be needed, but
their working conditions into the next decade will be completely different [6].
Ignacio Garcia explores the influence of cloud computing on translation, including
professional translation. He believes that the cloud computing reshapes the
management of labor in ways that unsettle the traditional relations between managers
and workers. It gives managers live control over how a project progresses, and a minute
description of how each worker performs [8; 7]. According to some researchers [5],
cloud technologies allowed to unite translation memory with machine translating, get
access to external databases and introduce more flexible translation management
systems. In turn, this allows you to improve the quality of translation.
Alexandra Kleijn considers, in particular, Wordfast Anywhere and XTM Cloud to
be the most common examples of the new type of CAT systems. She clarifies that some
of cloud-based CAT systems are primarily aimed at translation agencies and provide a
translation environment as well as a number of project management functions. Others,
such as Wordfast Anywhere, XTM Cloud and WordBee, are also great for single
translators. For example, Wordfast Anywhere is provided by the manufacturer
Wordfast as a free SaaS application on the Internet. Here only a registration is
required [12].
324
Rei Morikawa marks among the best CAT systems, in particular, Memsource and
XTM cloud-based CAT systems. The advantages of Memsource include the leading
cloud-based translation management system, accepting 50+ file types and powerful
workflow automation. The author considers XTM features to provide new projects from
common file types [14]. However, as Klaus Hauptfleisch notes, the skills of working
with SDL Trados remain important for the translator. It is the leading CAT system for
German Computer-Aided Translation with integrated Translation Memory System
(TMS), terminology database and much more. In his opinion, in fact, SDL Trados
Studio also convinces with its ease of use and rich features that other CAT tools have
limited [10].
Recently, both scientists and practitioners have compared various CAT systems,
trying to determine the most effective of them. So, Emma Goldsmith compares SDL
Trados Studio and memoQ and concludes that “both systems share almost all the
features that can be considered essential in a CAT tool” [9]. Laura Moreno Sorolla
carried out a comparative study of advantages and disadvantages of OmegaT and
Memsource. At the same time, a predominance of Memsource providing more
functions was noted: “OmegaT works solely as a CAT tool. On the other hand,
Memsource includes features that permit the management of a translation project” [19].
Nikita A. Panasenkov, Larisa I. Korneeva compare the performance capabilities of
working in the computer-assisted translation systems SDL Trados and SmartCat. In
their opinion, SmartCAT can be recommended, most notably, to novice translators who
wish to quickly master and start using the CAT-tool, as well as to learn how to offer
their services in the translation market. SDL Trados is oftentimes chosen by
experienced translators who are engaged in the translation industry on a permanent
basis, work with a variety of document formats and wish to improve their
competitiveness in the translation market [17].
The changing conditions of translators work depending on the rapid development of
information technologies requires the appropriate orientation of the educational process
content. Ukrainian universities that train translators are beginning to pay more attention
to the need to study automated translation systems, including cloud-based translation
systems [4; 16].
4 Results and discussion
It is worth noting that one of the core competencies of the translator, which is close in
essence to the above, reflects the current trends in translator training, and therefore not
only accumulates mentioned properties, but also complements them with other
components in the aspect of mastering modern translation tools, is defined by us as
information competence [3]. In our opinion, the information competence of a translator
should contain the following components: information retrieval competence,
information and technological competence, information and technical competence,
information and analytical competence, information and editorial competence,
information and thematic competence, information and legal competence. These
components differentiate the approach to mastering, first of all, specialized software in
325
various aspects of the preparation and implementation of translation projects.
Confirmation of the multidimensional nature and importance of the process of
mastering modern translator tools is the awareness of the increasing number of higher
educational institutions in Ukraine, which train future translators, the need to study
information technologies, in particular, automated translation systems and
terminological management. Thus, some of them, in addition to traditional courses in
computer science, began teaching special or optional courses aimed at studying the
peculiarities of using CAT systems in translation. In other universities, elements of
information technologies are included in the content of professional courses. However,
educational programs for the training translators in various educational institutions
where such steps have been taken have significant differences in terms of:
─ availability of special courses, modules or sections of academic disciplines;
─ list of modern tools of translator based on information technologies and selected to
study;
─ the time allotted for the study of modern tools and technologies;
─ a place in the schedule of the educational process, determined for the study of special
courses, specialized modules or sections;
─ ensuring the continuity of the study of modern tools and technologies during the
training period;
─ availability of specialized technology translation practices on the skills and abilities
of using specialized translation tools.
In view of the wide range of differences in the content and organizational structure of
educational programs for the training translators in terms of technological competence
formation, in our opinion, the key aspect is the definition of unified approaches to the
list and the type of basic tools to be mastered in the studying process. First of all, we
mean automated translation systems. This issue is ambiguous from the standpoint of
the availability of one or another software, the typicality of performing basic operations,
its prevalence in the translation services market, the possibility of its use in further
professional activities, etc.
An important aspect is the consideration of current trends in the development of the
global translation industry and the strategies of leading companies that are leaders in
the development and provision of modern translation tools. Over the past 10 years, the
essence of the work of a translator, especially in the field of technical translation, has
changed dramatically. This is primarily due to the widespread implementation of
information technologies, in particular, automated translation systems and terminology
management system.
Today, leaders have been identified in the development of such specialized software,
whose products are used by the vast majority of both translation agencies and
freelancers. These include software products such as SDL Trados, MemoQ, STAR
Transit, Wordfast, Across, Atril Déjà Vu and others. Studying one or several such
programs in the process of training translators is a guarantee of the formation of
information competence components that will ensure their competitiveness in the
market of translation services.
326
However, the structure of translation services continues to change and improve.
Despite the dominant position of powerful desktop CAT systems, over the past 5 years
cloud technologies have been actively developing to provide key tools to the translator.
The concept of companies that offer such technologies is not to earn profits through the
sale of software licenses, but through the involvement of as many translators as possible
in their services. At the same time, they receive a free, or at a minimum price, access
to services and tools, and profit is generated by deducting the percentage of orders
executed and the use of additional services. Such a policy is attractive to novice
translators and freelancers who make up a significant percentage of the professionals
involved in the translation industry, due to the possibility of constructing a full cycle of
the production process for the performance of translation projects. Somewhat slower,
such technologies penetrate into the work of powerful translation structures, although
the developers of these technologies also make efforts to meet their needs. Such
changes significantly affect the paradigm of the translation industry, its development
trends, and the content of the translator’s skills, which requires improvement of the
process of their training and largely involves the formation of readiness for the use of
such services. These technologies are currently implemented in such cloud-based CAT
systems as: XTM Cloud, Wordfast Anywhere, MemSource, MateCat, MemoQ,
smartCAT, etc.
Considering the possibility of studying the cloud-based systems of automated
translation in the process of training the translators, it is worth noting that they have a
number of limitations that need to be taken into account when making such a decision.
One of the major limitations is the size of files that can be processed in one or another
program. In particular, the file size that can be downloaded, for example, in XTM
Cloud, should be no larger than 550 MB. This restriction applies to the following
categories of files:
─ project source files;
─ imported translation memory files;
─ imported files of terminology databases;
─ imported files with client information;
─ imported files with user information.
There are a number of similar restrictions in the Wordfast Anywhere system. In
particular, Wordfast servers can store up to ten documents for translation at a time. At
the same time, the maximum volume of one download must not exceed 20 MB. The
range of file sizes to translate can extended a bit by downloading their archived version.
With regard to the file with the translation memory database, it has a restriction in two
categories: either its volume should be up to 200 MB or contain no more than 500 000
segments. In general, Wordfast allows to store up to 100 files with translation memory
databases. For files with terminology databases, the limit is set to the number of entries
in them, which cannot exceed 100,000. And such files, in general, can be downloaded
to 100.
Such restrictions can be a barrier to professional translating in companies with a
large volume of orders. However, as it comes to the choice of cloud-based automated
translation systems for use in the studying process, these constraints make it possible
327
to apply these systems as a means of studying and to work out the main stages of the
performance of translation tasks.
Considering the possibility and expediency of including the study of cloud-based
systems of automated translation, it is necessary to determine the level of unification of
knowledge and skills that can be formed when simultaneously or sequentially studying
desktop and cloud-based systems. In this case, it is advisable to emphasize the logic of
the priority study of the desktop variants of such systems and then demonstrate to
students the transition to cloud solutions, since the combination of both systems in the
production process is logical and confirmed by existing trends in the translation field.
It is advisable to make such a comparison according to the main stages of performing
translation projects using both types of systems. In particular, for comparison, we
distinguish the following main stages:
─ creating a project and setting its parameters;
─ creation and connection of terminology databases;
─ creation and connection of translation memory databases;
─ translation and verification of its quality.
The results of the study indicate that for performing a significant number of operations
within certain stages, both in desktop and in cloud-based systems, the same type of
skills can be formed. However, for the most part, the same type of operations are more
complex and technologically advanced when executed in desktop automated translation
systems compared with cloud-based translation systems, which tend to be fully
automated. On the one hand, it simplifies the use of cloud-based systems, but, on the
other hand, their study does not provide the depth of knowledge that is required to
perform certain stages of translation projects by means of desktop systems. This
confirms the previously expressed opinion on the expediency of the priority study of
desktop automated translation systems. At the same time, the differences between
different cloud-based systems are considerably smaller, which gives grounds for
asserting that it is possible to form skills for performing these stages of translation
projects, for example one of them. This can be confirmed by using most of the MS
Excel office files to create terminology databases, similar tools for automatically
aligning parallel texts, and using them as a translation memory database in .tmx format,
similar tools for checking the quality of translations, etc.
In this aspect, it should be noted that the direct translation work in the overwhelming
majority of both desktop and cloud-based systems is positioned as work on the project
and begins with its creation. Despite some differences, the essence of the main
operations to create a project is common, in particular: the choice of the direction of
translation, the choice of translation files included in the project, the connection of
translation memory databases, the connection of terminology databases, etc.
A positive feature of this process in XTM Cloud is the automatic analysis of the
output file for its structure, the amount of materials to be translated, the repetition of
individual elements of the text, exact and inaccurate coincidence with the translation
memory database, etc. A fairly detailed report on such an analysis is generated in the
form of a .xls spreadsheet and sent to the user on the mailbox. Such information is
important at the initial stage of interaction with the customer in agreeing on the main
328
parameters of the project: terms of execution, definition of cost, conditions for the
creation and transfer of the translation memory database, etc.
A qualitatively new level of translation efficiency with the use of automated
translation systems has been achieved thanks to their use in combination with
translation memory databases, which allowed the use of previously performed and
verified translations. This fact makes one of the priority tasks in the study of САТ
systems to focus on the formation of knowledge and skills for the creation and use of
the translation memory databases basically. One of the common approaches to such
operations is to align parallel texts. About the importance of these operations can be
judged from the fact that in most desktop versions of common automated translation
systems there are separate modules that ensure their performance not only manual but
also automated. An example of such modules can be SDL Trados WinAlign, LogiTerm
Text Aligner, MultiTrans PRISM TextBase Builder, TextAlign, YouAlign, etc. When
choosing cloud-based systems, special attention should also be paid to the availability
and terms of use of such tools.
Aligning parallel texts in order to create translation memory databases using the
Wordfast Anywhere toolkit is done automatically, requiring only downloading files
with target and source text. As a result of alignment an archive is created that contains
at once three files with aligned parallel text in the formats .tmx, .txt, .xls. Student can
download such archive directly to their computer, or send it to their own mailbox.
The highest value among the available files of the specified archive is the aligned
parallel text in the .tmx format, since it is actually a file with a translation memory
database. It can be directly connected to many automated translation systems or,
through simple transformations, transformed into its own format of the translation
memory database of one of the CAT systems. A significant advantage in generating
such a file is that it automatically runs filters that allow to not add repeat segments to
the base, numerical segments, untranslated segments, and so on. In these circumstances,
the need for specialized editors to rearrange aligned segments disappears. However, a
certain disadvantage of creating parallel aligned text in automatic mode is the inability
to influence the established relationships between the segments of the source and target
texts.
A feature of the .xls file in the current archive is the placement in a tabular form of
segmented text, where the compared segments in the source and target languages are
placed within the same line. In addition to each segment in the following columns, the
numerical values of the quality comparison of segments are given. Additionally,
separate segments may be provided with additional information about the identity of
the source and target segments, their repeatability, etc. This form of presentation of
parallel text alignment results is convenient for analyzing the alignment performed,
editing segments in the event of errors, removing segments that contain only the source
or target text, and so on. However, the aligned results processed in this way and saved
in .xls format do not allow them to be used as a complete translation memory database
in combination with automated translation systems. In case of making a decision on the
use of materials stored in this format as a translation memory database, it is necessary
to carry out a number of software transformations in order to save them in the
appropriate format.
329
The MemSource tool for aligning parallel texts and creating, based on them, the
translation memory databases by the nature of the work is similar to that performed in
Wordfast Anywhere. In particular, the user’s algorithm thus reduces to the installation
of source and target languages and downloads of files with target and source text.
Subsequent operations for segmentation of text, matching segments, and loading of
results in the form of .xlsx file on a user’s computer are done automatically. Similarity
of execution of such operations in different cloud-based systems of automated
translation is a positive aspect from the point of view of ease of their mastering in the
availability of the developed skills of such actions in one of the systems. The result of
this operation is automatically segmented and aligned parallel text that can be
downloaded to own computer as two spreadsheet options in various .xls files. The
difference between them is that one of them contains a complete list of segments and
variants of their comparisons, and the other – only those segments, the level of
probability of coincidence exceeding 90%. However, in the version of the program,
which can be given a free term of 30 days and has reliable advantages in this regard for
use in the educational process, the function of parallel texts, as well as the creation of
translation memory databases, is absent at all. All segments that are translated into work
are automatically saved to the connected translation memory database. If necessary,
you can download the database at your computer in .tmx, .txt, .xls, .txlf formats
(Wordfast Anywhere).
An integral part of the process of studying automated translation systems, both
desktop and cloud-based, is the ability to collect, process, structure and store
terminological material in such a way that it can be used as terminology databases
compatible with these systems. The conceptual principles of quality management of
translations are based on this in terms of ensuring the unity of terminology within a
translation project or a separate document.
Depending on the level of information technology acquisition in the process of
professional training of a translator, it is expedient to use a differentiated approach to
mastering the technology of working with the terminology material. In particular, at an
early stage, future translators need to develop the skills of placing terminological
records in the MS Excel table structure. Studying by students of this method of
organizing the terminology will ensure the possibility of constant accumulation of the
developed terminology due to the simplicity and comprehensiveness of the process of
data entry [1]. From the point of view of the organization of the educational process,
this creates additional advantages due to the availability of the specified program as
part of the office package.
It is important to note that a large part of popular automated translation systems
require terminology databases in specialized formats, the technology of their creation
is quite complicated. So in particular, for the SDL Trados system terminology base
should be presented in .sdltb format.
Considering in this context cloud-based automated translation systems, it should be
noted that most of them are capable of working with terminology bases that can be
stored in several formats, one of which is usually .xls format. So in particular, when
working with the MemSource system in order to improve the efficiency of translation,
terminology databases can be imported in the formats .xlsx and .tbx. Wordfast
330
Anywhere supports work with terminology databases stored in .xls, .tbx and .txt
formats. The XTM Cloud system is able to accept a fairly wide range of terminology
database files – .xlsx, .xls, .tbx, .mtf. However, it should be noted that despite the
possibility of these systems operating with terminology databases in .xls format, the
structure of the placement of terminological data in them is different. There are also
differences in the use of character identifier of languages, which denote column
headers, within which the terms and their correspondences in different languages are
placed. This feature requires the inclusion of a separate topic in the structure of the
training material, which allows to master different approaches to the use of character
or numeric identifiers of languages that vary according to the chosen standard or other
features.
The structure of the terminology data placement in Wordfast and XTM Cloud
systems is the simplest and most logical since it involves the organization of
terminological material in such a way that all information relating to one term is placed
sequentially within adjacent columns at the same level. In addition, such a structure
almost coincides with the structure of preliminary preparation of terminological
material for the formation of the terminology database for the SDL Trados system. The
difference lies in the fact that Wordfast does not use any identifiers and codes for
column headings with terms. In XTM Cloud it is necessary to use the combined
language codes and country codes (locale) in accordance with the standards ISO 639-1
and ISO 3166-1 alpha-2 (en_US for English, uk_UA for the Ukrainian language), and
for SDL Trados must be used the Ukrainian and English identifiers respectively.
Instead, the organizational structure of the MS Excel spreadsheet for ordering terms in
the MemSource system involves the presence of not only columns with terms in
different languages, for which the names are used by codes according to ISO 639-1
(uk – Ukrainian language code, en – code of English language), but separate fields for
the placement of special IDs for each term. However, such a structure is the most
complete, and at the initial stage of structuring terminological data in an MS Excel
table, to load them into the terminological base, it is enough to place them in two
adjacent table columns.
Despite these differences, the possibility of structuring terminology in the
spreadsheet format MS Excel creates favorable conditions for the rapid mastery of one
or another cloud-based system implemented in the content of specialized courses or
modules.
After studying the main stages of translation projects using the desktop system SDL
Trados CAT system in the course “Information technologies in translation projects”,
three laboratory works were added to the course content. These labs were aimed at
performing translation projects using cloud-based CAT systems, in particular
MemSource, Wordfast and XTM Cloud. The developers of these systems provide the
opportunity to use them for free for a certain period, sufficient to complete the task.
These systems were chosen for study in view of the fact that they are leaders among the
cloud-based CAT systems [12; 14; 15]. After the completion of these tasks, students
were surveyed to identify their attitude to the use of a particular cloud-based system, as
well as a generalized assessment of desktop and cloud-based CAT systems, the need
and consistency of their study, functional features, and so on. 52 students took part in
331
the survey.
The content of the first questionnaire included questions, in answers to which
students had the opportunity to express their desire to study and their vision of the logic
of studying CAT systems in general and in particular their types. There were five such
questions.
The results of the questionnaire are given in Table 1.
Table 1. The results of student survey about the vision of the logic of studying CAT systems
Answer Answer
Questions “Yes” “No”
Number % Number %
1. Is it reasonable to study desktop CAT systems before studying
34 65.4 18 34.6
cloud-based CAT systems?
2. Is studying cloud-based CAT systems promising for a future
46 88.5 6 11.5
translator?
3. It is advisable to study the desktop and cloud-based CAT
29 55.8 23 44.2
systems in the process of training translators at the same time?
4. It is advisable to study several cloud-based CAT systems in the
12 23.1 40 76.9
process of training translators?
5. Do you think that the key criterion for choosing and studying
the CAT system is its popularity among professional translators, 22 42.3 30 57.7
and not the cost?
According to the results of the survey, after studying both types of CAT systems, the
majority of students (65.4%) realize the need to master the work with both desktop and
cloud-based CAT systems. In addition, the overwhelming majority of students (88.5%)
understand the need to master cloud-based CAT systems at the current stage for
successful further professional activity. However, 76.9% of them believe that in the
learning process it is advisable to concentrate their efforts on studying only one of them.
The content of the second questionnaire included eight questions that reflect the
main aspects of the experience of students using cloud-based CAT systems.
The results of the survey are shown in Table 2 and Figure 1.
Analyzing the students’ answers on the second questionnaire, we can conclude that,
in general, all three cloud-based CAT systems were positively evaluated by them as an
important tool for preparing and carrying-out translation projects. At the same time, it
is worth noting that students expressed the greatest number of positive reviews about
the MemSource cloud-based CAT system, in particular, about the understandability of
the interface (51.9%), the convenience of creating a translation project (53.8%),
supporting the translation process (42.3%).
However, students also praised other CAT systems for individual indicators. So, the
students liked Wordfast most of all by such indicators as the registration process for
using the free version (78.8%) and the preparation of terminology bases (46.2%). When
studying the XTM Cloud system, they made the most of the previously acquired
experience in creating and carrying-out a translation project in the SDL Trados system,
which was noted by 46.2% of students.
332
Table 2. The results of a student survey on the experience of using cloud-based CAT systems
MemSource Wordfast XTM Cloud
Questions
Number % Number % Number %
1. In which of the cloud-based CAT systems is the
8 15.4 41 78.8 3 5.8
easiest to register for using the free version?
2. Which of the cloud-based CAT systems is the
21 40.4 14 26.9 17 32.7
easiest to learn?
3. In which of the cloud-based CAT systems
27 51.9 10 19.2 15 28.8
interface is the most understandable?
4. In which of the cloud-based CAT systems to
create a translation project was the most 28 53.8 15 28.8 9 17.3
convenient?
5. In which of the cloud-based CAT systems the
skills of placing terminological records in the
15 28.8 24 46.2 13 25.0
structure of the MS Excel table most effectively
ensured the creation of terminological databases?
6. Which cloud-based CAT system toolkit
provided the most efficient creation of a translation 20 38.5 15 28.8 17 32.7
memory base?
7. In which of the cloud-based CAT systems the
support of document translation process is better 22 42.3 12 23.1 18 34.6
provided?
8. In which of the cloud-based CAT systems are the
main stages of creating and carrying-out a
17 32.7 11 21.2 24 46.2
translation project as close as possible to the
desktop system SDL Trados?
Fig. 1. Comparison of cloud-based CAT systems based on the results of a student survey
333
5 Conclusions
An important aspect of the process of formation of the information competence of a
translator is to determine the list and type of basic tools of translation activities that
should be mastered in the learning process. First of all, such tools should include
automated translation systems and terminological management systems. The
implementation of the study of cloud-based CAT systems into the content of future
translators training is one of the pressing problems at the present stage of development
of the translation industry, which is promoted by a number of factors.
1. Full functionality of the latest versions of the top cloud-based CAT systems and their
widespread use in the translation industry:
─ availability of basic tools for the carrying-out of all stages of the translation project
(creating a project and setting its parameters; creating and connecting of terminology
databases; creating and connecting of translation memory bases; translating and
quality control);
─ a high level of unification of technologies for creating terminological resources in
various systems greatly simplifies their study.
2. Simplified version of their use in the educational process:
─ availability of free versions on a permanent or temporary basis;
─ no need to install systems on your own computer;
─ ability to work with systems anywhere with an Internet connection.
3. Possible reliance on previous knowledge of students:
─ preparation of terminological databases based on previously obtained knowledge
and skills to use MS Excel office suite for structuring data in tabular form;
─ having skills to use desktop systems, in particular: structuring terminological data
using international standards for the use of symbolic or numeric identifiers of
languages, specialized formats for terminological data, adding records during the
process of translating, importing and exporting terminological databases to the
system.
4. High motivation of students to study them:
─ understanding the prospects of studying cloud-based CAT systems for future
professional activities;
─ awareness of the need to use specialized tools in professional activities with
consideration of cloud systems as an alternative with insufficient financial
opportunities.
Therefore, in order to shape the readiness of future translators to use modern
technologies and tools in translation, it is necessary to improve the process of their
training, focusing on the formation of information competence in terms of its
334
components, in particular technological, including the study of cloud-based CAT
systems.
Prospects for further research may be related to the study of the use of cloud-based
CAT systems not only in independent, but also in the classroom work of students.
References
1. Amelina, S.M., Tarasenko R.O.: Studying technologies for creating electronic
terminological bases in the process of professional training of translators. Information
Technologies and Learning Tools 60(4), 105–115 (2017). doi:10.33407/itlt.v60i4.1738
2. Amelina, S.M., Tarasenko, R.O., Azaryan, A.A.: Information and technology case as an
indicator of information competence level of the translator. In: CEUR Workshop
Proceedings (CEUR-WS.org) (2019, in press)
3. Amelina, S.M., Tarasenko, R.O.: The essence of the stages of forming the information
competence of the translator. Information Technologies and Learning Tools 67(5), 44–55
(2018). doi:10.33407/itlt.v67i5.2276
4. Bondarenko, О.: Computer-aided tools (CAT) literacy at Ukrainian universities: practices
of implementation. Naukovi zapysky KDPU. Seriia: Filolohichni nauky (Movoznavstvo)
146, 648–650 (2016)
5. Civera, J., Cubel, E., Lagarda, A.L., Picó, D., Gonzalez, J., Vidal, E., Casacuberta F., Vilar
J.M., Barrachina S.: From Machine Translation to Computer Assisted Translation using
Finite-State Models. In: Proceedings of the Conference on Empirical Methods in Natural
Language Processing, July 2004, Barcelona, Spain, pp. 349–356.
https://www.aclweb.org/anthology/papers/W/W04/W04-3245/ (2004). Accessed 21 Mar
2018
6. European Master’s in Translation. Competence Framework 2017.
https://ec.europa.eu/info/sites/info/files/emt_competence_fwk_2017_en_web.pdf (2017).
Accessed 21 Mar 2018
7. Garcia, I.: Translating in the Cloud Age: Online Marketplaces. Hermes – Journal of
Language and Communication in Business 56, 59–70 (2017).
doi:10.7146/hjlcb.v0i56.97202
8. Garcia, I.: Beyond Translation Memory: Computers and the Professional Translator. The
Journal of Specialised Translation 12, 199–214.
http://www.jostrans.org/issue12/art_garcia.pdf (2009). Accessed 21 Mar 2018
9. Goldsmith, E.: SDL Trados Studio and memoQ: side by side. Signs & Symptoms of
Translation: a blog by a Spanish to English medical translator.
https://signsandsymptomsoftranslation.com/2014/08/08/memoq (2014). Accessed 21 Mar
2018
10. Hauptfleisch, K.: Übersetzungssoftware: Was die kostenlosen Tools taugen.
https://www.computerwoche.de/a/uebersetzungssoftware-was-die-kostenlosen-tools-
taugen,3215547 (2015). Accessed 21 Mar 2018
11. ISO 17100:2015. Translation Services – Requirements for translation services.
https://www.iso.org/standard/59149.html (2015)
12. Kleijn, A.: Open-Source-Software für Übersetzer. Magazin für Computertechnik.
https://www.heise.de/ct/artikel/Open-Source-fuer-Uebersetzer-1204029.html (2011).
Accessed 21 Mar 2018
335
13. Markova, O.M., Semerikov, S.O., Striuk, A.M., Shalatska, H.M., Nechypurenko, P.P.,
Tron, V.V.: Implementation of cloud service models in training of future information
technology specialists. In: CEUR Workshop Proceedings (CEUR-WS.org) (2019, in press)
14. Morikawa, R.: 16 Best Translation Management Systems. Gengo.
https://gengo.com/translator-product-updates/16-best-translation-management-systems/
(2018). Accessed 31 Dec 2018
15. Muegge, U.: The silent revolution: Cloud-based translation management systems. tcworld.
http://www.tcworld.info/e-magazine/content-strategies/article/the-silent-revolution-cloud-
based-translation-memory-systems (2012). Accessed 21 Mar 2018
16. Olkhovska, A.S.: Introducing modern technologies into Ukrainian translator/interpreter
training curricula: problems and perspectives. Science and Education a New Dimension.
Pedagogy and Psychology IV(43), 88, 34–36 (2016)
17. Panasenkov, N.A., Korneeva, L.I.: Comparing the performance capabilities of working in
the computer-assisted translation systems SDL Trados and SmartCat. In: Iazyk v sfere
professionalnoi kommunikatcii, materialy mezhdunarodnoi nauchno-prakticheskoi
konferentcii prepodavatelei, aspirantov i studentov, 19-20 aprelia 2018 goda, vol. 1, pp.
254–260. Izdatelstvo UMTc-UPI, Ekaterinburg (2018)
18. Semerikov, S.O., Shyshkina, M.P.: Preface. In: Semerikov, S.O., Shyshkina, M.P. (eds.)
Proceedings of the 5th Workshop on Cloud Technologies in Education (CTE 2017), Kryvyi
Rih, Ukraine, April 28, 2017. CEUR Workshop Proceedings 2168. http://ceur-ws.org/Vol-
2168/preface.pdf (2018). Accessed 21 Nov 2018
19. Sorolla, L.M.: A comparative study of OmegaT and Memsource: advantages and
disadvantages of their primary features. Master’s degree in Specialised Translation,
Universitat Oberta de Catalunya (2018)