Teza andreev alina final

UNIVERSITATEA DE VEST DIN TIMIȘOARA
FACULTATEA DE LITERE, ISTORIE ȘI TEOLOGIE
DEPARTAMENTUL DE LIMBI ȘI LITERATURI MODERNE
SPECIALIZARE: Limbi Moderne Aplicate (Engleză-Spaniolă)
LUCRARE DE LICENȚĂ
COORDONATOR:
ABSOLVENT:
Lect. Univ. Dr. Frențiu Luminița Andreev Alina
TIMIȘOARA
2017

UNIVERSITATEA DE VEST DIN TIMIȘOARA
FACULTATEA DE LITERE, ISTORIE ȘI TEOLOGIE
DEPARTAMENTUL DE LIMBI ȘI LITERATURI MODERNE
SPECIALIZARE: Limbi Moderne Aplicate (Engleză-Spaniolă)
Peculiarities of specialized scientific
translation: English-Romanian translation as
a case study
COORDONATOR:
ABSOLVENT:
Lect. Univ. Dr. Frențiu Luminița Andreev Alina
TIMIȘOARA
2017

1
Table of contents
Table of contents............................................................................................................................. 1
Chapter 1 Introduction .................................................................................................................... 2
Chapter 2. General particularities of scientific translation ............................................................. 4
2.1 Historic and current significance of scientific translation..................................................... 4
2.2 Main particularities of scientific translation and its difference from the literary translation 5
2.3. Human vs. computer based translation. The main differences of translation in both
methods.................................................................................................................................... 7
2.3.1 Translation strategies in human and machine translation............................................... 7
2.3.2 Different computer translation tools............................................................................... 8
2.3.2 Computer-assisted Translation ................................................................................... 11
2.3.3 Translation Memories................................................................................................... 12
Chapter 3. Materials and methods of study .................................................................................. 14
Chapter 4. Human versus machine translations: challenges and perspectives ............................. 18
4.1 Cross-cultural recognized terms and terminology of Greek and Latin origin..................... 18
4.3 Abbreviations and acronyms............................................................................................... 23
4.5 The use of passive voice and verb tenses............................................................................ 26
4.6 The use of graphical representation (tables and graphs)..................................................... 28
4.7 Language requirements of peer reviewed journals ............................................................. 29
Conclusions and recommendations............................................................................................... 30
References:.................................................................................................................................... 32

2
Chapter 1 Introduction
Scientific translation is like many other types of translations. However, this type of
translation is unique, very different from other types; with its own features and continuous study
and research. The scientific translation requires a bigger attention on the exact terms, developing
the same concept from source to target language and a careful attention paid to the language
accuracy. The informative scientific text has its own particular characteristics, which should be
taken into consideration when translating.
The main reasons for the choice of the topic was that generally speaking, quality
translators of scientific texts are in limited numbers. Fearing that the standard translators may not
always understand the meaning or the technical language of their papers, many scientists translate
by themselves or rely on colleagues help. In addition, many applications for the use on the
computers and mobile phones help scientists to translate their works. Nevertheless, their use in
scientific translation is not recommended due to impossibility of covering all specificity of the
scientific style. The language in which scientists communicate their research findings affect their
confidence and their scientific judgments and overall impact. A misplaced preposition or poor
choice of a specific term in a scientific article can ruin a convincing narrative, thus reducing
significantly the probability of publication in a top international journal and therefore, limiting the
impact of the research. That is why professional translators with a science background are required
to be hired and appreciated the same way as statisticians and technical specialists. This is
particularly important for such applied sciences as environmental sciences or biology, which
would allow a rapid accumulation of data, supporting or denying the scientific hypotheses and
increasing the knowledge sharing over a broader area.
The main aim of this thesis was to show the importance of scientific translation, the
difference from the other types of translations, as well as the process in which it is done and the
problems encountered during it. In addition, the most effective methods used in translation,
including the computer translation tools were highlighting and the critical analysis of translation
process for human and machine was given. After explaining the theoretical background, practical
examples on scientific translation are discussed. The practical part offer explanations of the
translated examples in order to show the connection between them and theoretical aspects
discussed in the first part of the thesis as well as the methodology chapter. The specific field

3
chosen for translation is environmental studies and biology. The choice of the subject was driven
by the previous working experience in an NGO, named WiSDOM (Women in Sustainable
Development of Moldova), where specific translation skills on such subjects were earned. As a
member of an environmental organization was truly useful for developing, the right background
and be aware with the latest news in this particular field. The main reason of selecting the scientific
translation field of study was related to real life application of the scientific translation during the
work in NGO. Even though the translation in the beginning was not perfect, lot of lessons were
learned that will be discussed in the practical part of the thesis. The process itself was interesting
and inquiring. Like the other types of translations, scientific translation requires a good planning
before starting the actual translating. For example, one would never start translating without a
close reading, understanding each sentence and then the whole text. Nevertheless, notwithstanding
the similarities of the process in general, there are plenty of differences that make the scientific
translation unique. It is important to study the source text very deeply, to try to understand every
term and new word, and to know not only its general meaning and translation, but also to know its
variety of meanings and many other words that are related to it. Even though this type of translation
is pretty different from the others, it has a lot of similarities. If speaking about the process itself,
like in the other types of translation we have here almost the same actions followed in the same
order. In this thesis, the most relevant differences of scientific translation are presented. In
addition, the main factors that contribute to the formation of scientific translation are examined:
particularly historical, linguistic and communicative factors. Everything that developed science as
an object of study was of a considerable influence for the study of translation. By no means a
translator must be aware of the translated subject a lot, he must know every little detail in
particular. The professional scientific translators may not be experts in the field of science or a
scientist by themselves, but their work must be acknowledged well, since they study a lot the
terminology in order to understand the words and narratives to be send to a scientific audience.

4
Chapter 2. General particularities of scientific translation
2.1 Historic and current significance of scientific translation
The term of translation appeared long ago when people started to translate The Bible in
order to send the God’s message to every corner of the earth. Translation studies have always
focused mainly on translating texts of literature, religion and philosophy and not the scientific
ones. It is stated that even the translation researches are in literary translation, poetry,
Shakespeare’s works of translation, and not in scientific, medical or technical fields. However,
over the time, translation developed in a science of linguistics, it became more and more applicable
and used in almost every field (linguistics, sociology, mathematics, history, literature, biology,
psychology, business, etc.). It is undeniable that translation had a big role in the production and
spread of knowledge and science throughout cultures and times.
In English-speaking countries, the first scientific society was founded in 1660 and
remained until today as an academy of science. Its main aim consisted in communicating science
to everyone. It is pretty hard to write about science, because like in literature it requires creativity,
but in contrast to it, a scientific writer should provide accuracy in his text. There always had been
a strain between the functionality and creativity of scientific text. These characteristics of writing
are the same for translation. Due to the changing of the English language and grammar throughout
the years, the scientific texts have evolved a lot and became more complex and denser in the
containing information as well as terminology. So did the scientific translation and maybe it
wouldn’t be appeared if the science didn’t develop a lot.
When speaking about the history of science, very few scholars focused on the production
and distribution of knowledge in science. They were focused mainly on discovering the science,
developing new ideas and terms that they never experienced in the past. During the modern era of
our existence, many developments in mathematics, astronomy, physics, biology (including
anatomy) and chemistry were stated. Nowadays, when many things are already discovered and
known by the world of science, the exchange of scientific information became crucial. The
translator pays more attention on the target text than on the source text, how did our ancestors

5
2.2 Main particularities of scientific translation and its difference from
the literary translation
When translating a scientific text, there are many important points taken into consideration:
1) the translated text need to provide the same meaning as the original text, so thus the scientific
hypothesis or statement do not differ from scientific truth, 2) ambiguities and unclear constructions
characteristic for literary texts shall be excluded from scientific texts, 3) In literary translation long
sentences are used, while in scientific translation the text is usually formed of short and direct
sentences, 4) in literary translation the figures of speech such as metaphor, personification, irony
are used, whereas in scientific translation such applications are not recommended, 5) literary
translation is usually personal, while scientific - impersonal, 6) there is a limited use of verb tenses,
scientific texts make use of simple, past simple and future, but literary texts - have no limitation
on the use of verb tenses, the choice of these depend on the context.
According to Adams (1967) the main differences between science and literature are
illustrated in Table 1. As reflected in the two different columns of Table 2.1, one of the main
aspects the scientific text on based is the denotative adequacy, while the literary texts - on
unbridled connotation. Denotative equivalence refers to the elements shared by the source text and
the target text in translation or in other words, translation of a sign or word is done precisely
according to its literal meaning and no change shall be made. On the opposite, the unbridled
connotation used in literary texts translates the sign or a word close to its associated meanings.
The scientific content of the text is focused on horizontal structure of the world, while literary
content examines the vertical structure of the world. Therefore, the product of poets expresses the
height and depth of life, they work more with imagination. Instead, the product of scientists lacks
the intuitive complexity and wealth of experience characteristic for poets. Scientists usually write
about familiar and concrete realities of the everyday life. If they need to move for example, their
movement will not go against the accomplishment of new horizons and new perspectives, like
those based on the imagination of the poets, instead they will remain within the concrete, tangible
and objective reality, within the horizontal structure of the world. One should also notice that most
of the elements in scientific texts are clear, not ambiguous or unexpected.
In contrast, the literary texts may deal with potential meaning of the things. Such meanings
may be perceived, conceived, or represented in terms other than their actual appearance or function

6
by the perceivers or to the ‘intention’ of their producers (Weinrich, 1976). One can say that in
scientific translation, the translator personality is not fully exposed, while in literary texts, the
translator's personality is fully exposed giving his communication world views attitudes.
Table 2.1. The main differences between scientific and literary texts (Adams, 1967)
Science Literature
- Denotative adequacy. - Unbridled connotation.
- Logical expository and/or
argumentative progression.
- Lack of argumentative progression.
- Precision. - Vagueness.
- Intellect. - Imagination or intuition.
- Reason. - Emotion.
- Truth to particular truth. - Truth to the ideal and universal.
The scientific texts are also characterized by the logical order of words and sentences, thus
having a clear indication of their interconnectedness and interdependence. Such texts indicate
precision, intellect and reason (Table 2.1). Stylistic operation contains not on aesthetic, but a
pragmatic information. Therefore, scientific translation has a frequent use of specific sentence-
patterns, usually containing a postulatory, an argumentative and a formulative pattern. The
impersonality of this type of writing is highlighted by the frequent use of passive voice
constructions with which scientific experiments are generally described. Despite the fact that the
original text is quite complex, containing a lot of specific terms and definitions, terms of Latin or
Greek origins, the scientific text should be written in a clear and concise way so thus it maintain
its communicative purposes and is comprehensible to a large audience.
The literary texts lack the argumentative progression. In literary translation, language has
more than a communicative, social or connective purpose, it has also an aesthetic one. This is
important since in literary translation a complex process takes place, the so-called "the trans-
expression", the life being captured in the imagination of the person making translation.
Scientific words also differ from ordinary and literary words since they do not accumulate
emotional associations and implications. In scientific works, the reader will not read for any
sensuous pleasure as in the case of the reader of literary work, but tries to understand the essence

7
of the information and data presented. All that is required is the verbal accuracy and lucidity of
expression. That is why the translation of a scientific work is supposed to be more direct, free from
alternatives, and much less artistic than the other kinds of prose. The language of scientific and
technical text is characterized by impersonal style, simpler syntax, use of acronyms, and clarity.
2.3. Human vs. computer based translation. The main differences of translation
in both methods.
2.3.1 Translation strategies in human and machine translation
Technology has developed considerably since its beginnings as a result of the
intensification of communication between countries. The use of technology became crucial
nowadays, since it provides a huge amount of information and a wide variety of possibilities. What
people studied for centuries, with hard work and arduousness, now it is easily available for
everyone and can be found almost in every corner of the earth. Technology is widely used in
translation as well. The development of different software and computer translation instruments,
including online tools opened new opportunities to supplement part of human work by computer
translation.
Ever since the idea of translating via computers appeared, in 1940’s, people have feared
the disappearance of human need of translation. In any translation, whether made by human or
computers, the meaning must be transferred accordingly. The target language should provide the
same meaning as in the original, and should not break its grammatical structure. The process of
translation itself may seem simple on the surface, but it is more complex and demanding. Hereafter,
I will show the main particularities of human vs. machine translation.
In order to understand the differences between and human and machine translation we first
need to understand the strategy in translation used for each case separately. In the first stage of
translation a human translator will make a thorough reading of the source language text for its
general comprehension. In this stage understanding of a text takes place at several levels:
a) semantic level: understanding the meaning of the words out of context, similar as in a
dictionary.

8
b) syntactic level: understanding the words in a sentence.
c) pragmatic level: understanding words in situations and context.
Furthermore, a good translator must possess at least five types of knowledge in order to
perform a quality translation: knowledge of the source language (the scientific field in which the
work is done) this allowing a compresence of the original text. Another type of knowledge is that
of the target language (in our case Romanian). This type of knowledge makes it possible to produce
a coherent text in that language and thus express exactly the scientific statement, which form the
scientific truth. Furthermore, a translator must have knowledge of equivalents between the source
and target languages. Supplementary to that, it is crucial that a translator engaged in scientific
translation has good knowledge of the subject field as well as general knowledge; both of these
will help to understand the source text. Last but not least is the knowledge of socio-cultural aspects;
these include customs and conventions of the source and target cultures. The translation process is
usually divided into two major stages: 1) the rough translation stage - when the translator produces
a preliminary translated version in the target language; 2) the revision stage - in this stage the
translator re-read the whole text and makes minor adjustments and editions. The translator can also
consult with the author to clarify some ambiguities or check for accuracy of translation.
Machine translation has the following translation strategy: each word of the source
language syntagm is directly connected to a similar unit in the target language, with a
unidirectional correlation (binominal). Usually, online translation tools use a bilingual dictionary
from source language to target language. In such a way it produces a document in the target
language on the basis of the linguistic data of the source language and the available vocabulary in
the existing database. Such a document is not a finalized product, it is a text that needs editions or
can be used only as a reference document for the translator to check for general meaning of the
words, rather than the words in context.
2.3.2 Different computer translation tools
Up to now several computer or so called “machine translation” tools were developed. A
brief overview is given in table 2.1, with a short characteristics of the potential for translation (e.g.
pairs of languages employed).

9
Table 2.1. Examples of machine translation tools and their translation potential
Machine translation tool Address Characteristics
Alphaworks http://www.alphaworks.ibm.com
/aw.nsf/html/mt
Translation of English into
seven languages
E-lingo http://www.elingo.com
/text/index/html
Has 20 pairs of languages
Reverso http://trans.voila.fr Includes 13 pairs of
languages
Systran http://www.systransoft.com Comprises 13 pairs of
languages
Transcend http://www.freetranslation.com/ Has 8 pairs of languages
Google Translate https://translate.google.com/ Translation of English into
100 languages
As can be seen from Table 2.1, Google Translate is one of the most widely used machine
translation tool. Everyday a huge amount of people translate with this program billions pieces of
work and it is used not only by the translators, but almost by everyone who needs to translate a
word, sentence or text from an unknown language. It became so popular due to the fact that it is
inexpensive and it gives an instant access to the information in original language and translates
with a moderate quality. Those who invented it had the aim to simplify the process of translation
and with time to replace this work done by the human. This program is widely used in the
translation of scientific and technical texts, because they are easier to translate in comparison with
literary texts. Computer translation should become more and more close to human professional
translation. However, machine translation still fail in the grammatical accuracy, syntax, semantic
and pragmatic structures. Although there is a great progress in the machine translation, fully
automatic translations are far from being perfect.
Often, many scientists use this program to translate their scientific articles from their native
language into English or any other language. Obviously they think that Google translate is enough
to provide the correct meaning, because they are acquainted with the subject, they know the
terminology etc. But, in fact, translation it is a more complex process than it seems. The distortion
of grammatical segments can cause a misunderstanding of meaning. The right order of the words
and sentences, the right use of conjunctions and prepositions and the use of the right synonyms
can provide the best meaning, as well as the use of equivalence of the source language texts.
Human translation is influenced by the characteristics of source to target language transfer, cultural

10
context and translation ability. People are capable to use a wide variety of methods of translation
and they pay attention on the grammatical structure. They learned for centuries how important is
to combine the grammatical, stylistic and syntactical particularities, because a translation without
one of these isn’t perfect, and isn’t finished yet. Unfortunately, computer translation cannot do a
complete version of translation and although it gives a lot of correct terms, the words might not be
placed accordingly and the text needs at least a revision and a thorough correction.
If speaking about scientific texts, there is no better translator than human. This can be explained
by the fact that a person is capable to understand the right meaning of the source text and although
it can use a program of translation for help, he cannot rely totally on it. One of the most common
mistakes made by computers in translating scientific texts is its inability to distinguish the meaning
of a common used word from its scientific meaning. Human will translate in this case by trying to
understand all of the meaning, will assess the surrounding texts, by further reading the paper or by
referring to other papers from the same field (Panter, 2017). Another difference between human
and computer translation is that people are more familiar with the word order from the original
and target language, while in automatic translation this kind of mistakes are very frequent. There
are many scientific articles, books which contain very long sentences and it is not best to break
them, because it can cause a loss in the meaning of the text. Computer programs cope very well
with shorter sentences, but when it tries to translate a long utterance, which contains a couple of
phrases and subordinates, it finds difficult to maintain the course of the sentence. The computer
programs of translation are designed to help and make the job of a translator easier, not to replace
it. There are numerous aspects that computers do not take into account when translating, because
they work automatically by a pattern based on the use of synonymy and some specific grammatical
units. Therefore, basically it uses o formula of working and does not abate from it, while human
can compare his translation with others and can do it by his own rules.
Quoc Le, the person responsible for shaping the Google translation software, together with his
colleagues at Google, rolled out a new translation system. It is designed to use a large amount of
data and has an increased processing power. Due to its effectiveness in working it is considered to
reduce errors of translation up to 87%. This system is best for scientific and technical translations.
It obviously translates better than Google translate and it gives a variety of terminology making
links between words more easily. It works via a vector system, which means that it transforms a
word in a vector value and it shows how related it is to any other words from the dictionary. This

11
process helps to get a more precise meaning of a word from scientific field. The name of this
system of translation is neural translation. In a short period of time the neural translation will
become more helpful in translating scientific texts than Google translate (Matacic, 2016).
There are many other programs in process of development that would become in time, more
and more used. As languages progress with every year, and there are many terms in science that
appear and become more and more used, and known by the ordinary people, the technology
translation is in a continuous progress as well. Translations done by human in this domain are
immeasurable due to the people’s mobility in working and their access to a large amount of
information from much more different sources than a computer is capable to use. A translation in
science must be done by a person who understands the science and is a good linguist at the same
time. If he does it with a computer based machine, it means that it is not finished. A computer has
link to a variety of dictionaries from which it can extract the meaning of words, but it is not a brain
to understand logically the text as a whole. That’s why human translation is still important in the
domain of science.
2.3.2 Computer-assisted Translation
Computer-assisted translation (CAT) involve different specific tools and technologies
which were developed for fulfilling the needs of the translator, who is involved in the whole
process and not only at the editing stage. In this case the computer becomes a workstation where
the translator make use of o a variety of already translated texts, tools and programs: for example,
monolingual and bilingual dictionaries, parallel texts, models texts in source and target languages.
Additional important translation tools are terminology databases. Each translator can create its
personal digital library of translation terminology or translation tips, according to the needs of the
specific task. Therefore, with today technologies, computer-assisted translation offers the
translator an immediate access to a wide range of up-to-date information, which is very important
for scientific translation. In this way, the translator gains enormous time saving. The following
most important computer tools that can be used by a translator: online Dictionaries, Glossaries and
Terminology Databases, Word root data databases etc. Consulting online dictionaries on the
computer does not seems very different on the first sight from using printed dictionaries. However,

12
there are big advantages, since it takes much less time typing a word on the computer and receiving
an answer comparing to the time required to look through a printed dictionary. In addition, it is
possible to use several dictionaries simultaneously and work with multiple documents. Digital
dictionaries are available in different formats: as software that can be installed and used from a
computer; as flash drives and via the Internet. The search engine Google, for example, gives us
access to a great variety of dictionaries in different languages. On-line dictionaries are not simply
a collection of words but also can give the meaning of words related to the key word. For
consulting of specific terminology, for example the terminology of Greek and Latin origin as in
scientific text, there is a wide range of dictionaries, glossaries and databases available online. Root
Word and Prefixes: Quick Reference, for example contain several free of charge resources,
including a rich database of the words of Greek and Latin origin. Another important resource is
EURODICAUTOM. This is a multilingual terminology database, which was established by the
European Union in 1973. It covers a wide range of specialized areas, both scientific and non-
scientific fields (the list begins for example with Agriculture, Arts, Automation...) (Craciunescu et
al., 2004). Supplementary to this, there are web sites containing useful information on terminology
that is also of a great use to translators. One such site is the TERMISTI research center which
belongs to the Higher Institute for Translators and Interpreters (ISTI) in Brussels
(http://www.termisti.refer.org). This website offers the following information: available online
dictionaries, terminology networks, translation Schools Forums and discussion lists.
2.3.3 Translation Memories
Translation memories are important computer applications for bilingual texts, this being
developed in the beginning of the 1980s. This application become more advanced at the beginning
of the 90s by the elaboration of such programs as Translator Manager, Translator's Workbench,
Optimizer, Déjà Vu, Trados and Eurolang. To explain in simple words, a translation memory
contains a database, where a translator stores translated texts for future re-use, either in the same
work or for translation of other texts. A translation memory records pairs of a source-language
segment (in form of a sentence) and a target-language segment. When the translator adds an
identical source-language segment, the translation memory program finds the translated segment
stored and gives automatic suggestions for the given new fragment. The translator can accept it as

13
it unchanged, or edit it to fit into the new context. The translation memory where there is
terminological homogeneity and where the meaning of terms does not vary, for example in the
case of a high percentage of words of Latin and Greek origins.
The program can be used in two different ways:
1. In interactive mode: In this case the text to be translated is placed on the screen and the
translator chooses the fragments of the text to be translated. After each selections, the program
searches its memory to identify similar segments and gives the possible translation fragment in a
separate window. The translator can accepts, change or reject the suggested fragment.
2. In automatic mode: Translation memory automatically processes the whole source-
language text and inserts suitable translations into the target-language text. This is a more useful
in the case of many repetition of words.
A translation memory program contain few important components such as: a) a translation
editor, - protects the target text format. b) an automatic localizer of the texts fragment; c) a
terminological tool d) A text analyser; e) a statistical tool that count the number of words translated
and those that need to be translated. In such ways, translation memory programs accumulate and
store knowledge and recycle it according to the translator need, automating the use of terminology
and access to the dictionaries. In spite of all these advantages, translation memories can only deal
with a text in a simple way; they cannot, have a vision of the text as a whole and comprehend
thoroughly the ideas and concepts or overall message, which is an important part of the scientific
translation. A human translator is able to rearrange the information redistribute it according to the
needs, in order to create coherence and enhance comprehension. Translation memory programs
were developed to increase the quality and efficiency of the translation process, particularly in
relation to specialized texts with rigid grammatical construction, but they were not developed to
replace the human translator.

14
Chapter 3. Materials and methods of study
The thesis consists of theoretical part and practical part. The theoretical part made an
overview of literature on characteristics of scientific translation, its difference with literary
translation and the aspects of human versus machine translation. The practical part consisted of
analysis of specific pieces of scientific works translated from English into Romanian and from
Romanian into English and their critical analysis according to specific criteria based on a number
of studies (Soualmia, 2010) (Table 3.1).
Table 3.1. The main criteria used for analysis of translated articles.
I. Use of terminology
Different terms used Description or example Reference
1) Cross-cultural recognized
terms
Globalization, development,
adaptation, sanitation
Soualmia, 2010
Andreev and Andreev,
2010
2) Terminology of Greek and
Latin origin
Composition, biology LearnThatWord, 2005
3) Acronyms and
abbreviations
Lactic acid bacteria (LAB) Naidu et al., 1999
II. Writing style
1) Impersonal style and
passive voice
Focus on the results of the actions
rather than on agent of the action
Essay UK, 2017
III. Use of verb tenses
1) Simple verb tenses Present simple tense -
introduction,
Past simple tense - abstract and
methodology
Combination of verb tenses -
conclusions.
The University of
Melbourne, 2012
V. Graphical representation
1) Graphs and Tables Draw attention on specific aspects
of research. Not recognized by
computer translation.
Slutz and Hess, 2017.

15
One of these criteria is the use of terminology in scientific translation. Terminology
represents a set of concepts that belongs to a specific field. People use specialized dictionaries, e.g.
in the field of mathematics, physics, biology, linguistics, etc. to define the unknown terms and to
categorize them accordingly. Scientific papers are impossible without the proper use of
terminology. It is undeniable that terminology is very important in scientific translation as well.
The specific terms of this field are difficult words, being more complex and less
understandable than the ordinary ones. Despite the literary texts they do not show emotional states.
They represent the most significant feature in science and they make a text incomprehensible for
most of the lay people. There a few kinds of terms used in scientific translation like cross-cultural
recognized terms and cultural specific terms.
Cross-cultural recognized terms represent universal terms which do not belong to a
specific culture or language. They are of scientific nature and from a translation point of view they
do not impose any linguistic problems. The translation of these words is done easily due to the fact
that there is a very small cultural gap from source to target language. A translator would definitely
find an equivalent in his native language for these kind of terms. Some examples of cross-cultural
recognized terms in scientific articles are: globalization, climate change, development, adaptation,
environment, sanitation and many others. These words often cause serious translation problems in
machine translation, because of the incapacity to find similar word for the target language. An
example would be: the scientific term “sanitation” which in English means management and
treatment of human wastes and wastewater and in Romanian – “sanitație” means cleaning,
disinfection, etc. Because people didn’t find the right equivalent for it, the term was adapted to a
new concept and it is often used with the same meaning as in English (Andreev and Andreev,
2010). An automated translation tends to omit the terms belonging to a specific culture, due to the
fact that there is no equivalence for this word in the system of dictionaries.
Terminology in science has its origins mainly in Greek and Latin words. It is easier to
understand and apply them if the person learns the meaning of their origins. A translator should be
aware of these words and should remember them forever in order to provide a better translation.
There are some common principles that should be applied to scientific terminology. And one of
the most important one is the correct use of roots, suffixes and prefixes of Greek and Latin origin.
For example: “bio” means life and “logos” means science; together combined these sequences
from a total different word – “biology” which means the science of life. Both of these words are

16
of Greek origin. Here also can be exemplified some terms of Latin origin like: “composition”
which means the nature of something’s ingredients or constituents. The word became into use in
English from the late middle era, via old French word “composition”, which as well originated
from the Latin “composition” and “componere” – put together. There are plenty of examples like
that not only in English but in many other languages. A translator should be aware of the origins
of words for both source and target language (LearnThatWord, 2005).
Another important aspect that should not be avoided is the use of acronyms and
abbreviations. Usually a scientific text main contain a large amount of acronyms and abbreviations
because the terms are known to those who write and read the research. Scientific texts may be
written for a large audience, though they are difficult for lay people who are not acknowledged
with the field. For a proper use in translation, they should be studied in both languages (source and
target), because they have different equivalents. In some cases, a translator should insert an
explanation or indicate the long form of the word combination in order to be comprehensible for
everyone who reads. An example of abbreviation in scientific articles of my research is: Probiotic
spectra of Lactic Acid Bacteria (LAB). (Hopkins, 1999; Naidu, et. al., 1999).
Scientific texts belong to academic writing and that’s why they have an impersonal style.
This style is characterized by the highlight of ideas and concepts rather than the emphasis on the
author himself. This style of writing goes together with the right use of tenses and the concise
form of expression. The passive voice is useful to express general beliefs and to focus on the result
of the action rather than the agent that carries it out. For example in a scientific article when
something is researched, the explanation should provide how the information was gathered or how
was conducted the investigation. The same pattern of impersonal style must be used as well in
translation. The right meaning of the original text can be obtained only by following the correct
structure. With the help of passive voice the writer becomes more objective in his ideas and the
facts are separated from opinions. Not knowing the importance of impersonal style and the right
use of passive voice can lead to misunderstanding and losing of source text structure (EssayUK,
n.d).
A continuation to passive voice is the use of tenses in scientific writing and translation.
Verb tenses should represent the relationship between the present moment and another moment or
period of time. They manage time by placing them while writing in particular time frameworks.
So, in science some frameworks are more commonly used than others. For example, present tense

17
is most used in introduction because it has the aim to provide crucial or general information about
the research and the intention of the author. Past simple tense is better used in abstracts and
methodology to describe what actions were done, what are the obtained results, etc. The use of
present perfect tense is not so common but sometimes it is necessary when expressing the currency,
then author refers to previous research or writing. The conclusion is usually formed from a
combination of tenses, due to the fact that it summarizes the findings and implications of the
research. When writing a scientific text, the use of tenses is not a difficult thing, because the author
relies on the use of only one grammar and language. In translation things turn out to be more
complicated. The tenses from source language may not coincide with those from target language.
Each language has its own grammar and rules of the tenses use. Respectively, the job of a translator
is to study very well the syntactical equivalence and to apply it correctly (The University of
Melbourne, 2012).
An important characteristic for scientific texts, which represent at the same time an
impediment for translation is the graphic representation of data and result. The affirmation “an
image worth a thousand words” is true, because in science people deal with very complicated terms
and formulas, which sometimes need to be represented through images, tables, schemes, diagrams,
etc. in order to be better understood. The visual representation of data in science is called Graph.
Graphs are not only an excellent representation of data, but also a good analytical mechanism. The
process of manipulating data into different visual forms has the aim to draw attention on some
specific aspects of research and expands the reader’s thinking about it (Slutz and Hess, 2017).
At first, the translation of graphs seems to be very easy if it is translated by human.
However, this thing is almost impossible if done by computers. A computer does not recognize
the images and tables; it does not have in its formula of working this aspect and it would probably
give a very weak translation and broken from subject. A human is able to understand the visual
representations; one can translate only the most important part of graph, which contains only words
and numbers. Maybe in the future, due to the development of technology, the translation of graphs
will be perfectly done by the computers and there will be no need of human involvement in this
aspect (Slutz and Hess, 2017).

18
Chapter 4. Human versus machine translations: challenges
and perspectives
4.1 Cross-cultural recognized terms and terminology of Greek and
Latin origin
In scientific translation, particularly in medicine, biological and environmental sciences
there is a wide use of words of a Greek and Latin origin. This is because there is a need to allow
an easier communication within a multilingual scientific community, thus the list of species;
anatomical or physiological organs have their roots from these languages (Table 4.1).
Table 4.1 Examples of words with Greek or Latin origin.
Word or root Original
language
Original meaning Notes
Andro- Greek man A particular organ in flowers
of flowering plants.
Gynaec- Greek woman Related to woman sexual
organs
Thorax Greek chest Breast plate
Femur Latin Thighbone Anatomical organ
Hydrology Greek Science on water “Hydro” - water and “logos” -
science
Ambiguous Latin Uncertain, unclear
Ampulla Latin Bottle, flask
Source: Wikipedia
The use of such terminology of Greek and Latin origin is quite often in most of the scientific
papers. For example, a quick overview of only 3 randomly selected scientific papers from google
scholar indicated that the percentage of Latin and Greek words in scientific papers vary between
16-17% to 30-35 (Table 4.2), however for taxonomic or medical research this percentage could be
even higher.
The cross-cultural recognized terms have also Latin and Greek roots. Translation of
scientific words of Greek and Latin origin may create challenges in human translation, since a
translator needs to know well this terminology in order to give a correct translation. Currently there

19
are several online sources for example The Root Word Dictionary (McCarthy, 2013), Online
Etymology Dictionary, or Specialized Root Words for example, the Root Words in Chemistry.
The Root Word Dictionary is the largest online dictionary of word root. Even though there are
many online sources, which make easier the work of a translator, the machine translation services
is still unable to read and comprehend the text, recognize the meaning of words of Latin and Greek
origin, control and check and interact with the author of a scientific work as human translator does.
When dealing with words of Greek or Latin origin, as well as cross-cultural terms, specifically
newly formed words, translators can use terminology databases and translation memories or verify
words in the Root Word Dictionary or other similar online tools that speed up their work
(Craciunescu et al., 2004).
Table 4.2 Examples of the frequency of occurrence of words of Latin and Greek origins in
scientific papers.
The reviewed scientific
papers
Reference Percentage of words of Latin
or Greek origins in relation to
the total number of words, %
Sustainability of wastewater
treatment technologies
Muga and Mihelcic, 2008 16-17
Application of hydroponic
systems for the treatment of
source-separated human
urine
Yang et al., 2015 20-22
The physiology and
biochemistry of the
proteolytic system in lactic
acid bacteria
Pritchard and Coolbear, 1993 30-35
Source text “Biotic invasions constitute only one outcome - indeed, the least likely outcome
- of a multistage process that begins when organisms are transported from their native ranges to
new locales. These immigrant organisms and their descendants have been referred to as “alien,”
“adventive,” “exotic,” “neophytes” (in the case of plants),“introduced,” and most recently,
“nonindigenous” (Salisbury 1961, Mack 1985, Baker 1986, U.S. Congress 1993). These terms
have been used interchangeably and often without careful distinction. We will employ
“nonindigenous” as the most general term for immigrant species, especially where their invasive
status is uncertain” (Mack et al., 2000).

20
Author translation ”Invaziile biotice constituie doar o consecință, într-adevăr, o
consecință cea mai puțin probabilă al unui proces în mai multe etape care începe cînd organismele
sunt transportate din locurile lor native în locații noi. Aceste organisme imigrante și descendenții
lor sunt denumite “specii străine”, “specii adventive”, “specii exotice”, “neofite” (în cazul
plantelor), “introduce” și mai recent „non-indigene” ” (Salisbury 1961, Mack 1985, Baker 1986,
U.S. Congress 1993). Acești termeni au fost utilizați interșanjabil și adesea fără o distincție clară.
Noi vom întrebuința “specii non-indigene” pentru speciile imigrante, în mod particular unde
statutul invaziv al acestora este nesigur”
Google Translate “Invaziile biotice constituie doar un rezultat - într-adevăr, rezultatul cel
mai puțin probabil - al unui proces în mai multe etape, care începe atunci când organismele sunt
transportate de la gama lor nativă la locații noi. Aceste organisme imigrante și descendenții
acestora au fost denumite "străine", "adventive", "exotice", "neofite" (în cazul plantelor),
"introduse" și, recent, "nonindigene" (Salisbury 1961, Mack 1985, Baker 1986, US Congress
1993). Acești termeni au fost folosiți interschimbabil și de multe ori fără o deosebire atentă. Vom
folosi "nonindigenous" drept termenul cel mai general pentru speciile imigrante, în special acolo
unde statutul lor invaziv este incert”.
The current example indicates that in principle, Google Translate translates all of the terms
of Greek or Latin origin such as “biotic”, “invasive” “alien”, “nonindigenous” (Greeek)
“adventive,”,“exotic,” and “neophytes” (Latin) since in principle considering the fact that the
core vocabulary of the Romanian language derives from Latin. The main problems that can be
seen in the piece of the text translated with Google Translate is the incorrect formulation of the
sentences, the text being very rough from the grammar point of view or incorrect choice of the
words (for example “rezultat” instead of “consecință”, “gama lor nativă” instead of “locurile lor
native”). Therefore, a translator can make use of Google translate just similar as translation
memory tool, just for consulting words, but not as much as considering it for producing a target
text. For example, checking separately the words in Google translate gives the synonyms and also
a more accurate translation than the words in context.
Source text “A set of indicators that incorporate environmental, societal and economic
sustainability were developed and used to investigate the sustainability of different wastewater
treatment technologies, for plant capacities of < 5 million gallons per day (MGD) or 18.9x103
cubic meters (m3
/day). The technologies evaluated were mechanical (i.e. activated sludge with

21
secondary treatment), lagoon (facultative, anaerobic and aerobic) and land treatment systems
(e.g. slow rate irrigation, rapid infiltration and overland flow)”.
Author translation “În scopul investigării sustenabilității diferitor tehnologii de tratare
pentru stații de tratare cu capacitatea de < 5 milioane galoane pe zi (MGZ) sau 18.9x103
metri
cubi (m3
/zi). au fost elaborați un set de indicatori privind sustenabilitatea de mediu, societală și
economică. Tehnologiile evaluate au fost mecanice (de exemplu nămolul activat cu tratarea
secundară), tehnologia lagunară (facultativă, anaerobă și aerobă) și sistemele de tratare la sol
(de exemplu irigarea cu viteză mică, infiltrarea rapidă sau fluxul direct pe sol”.
Google translation “S-au dezvoltat și s-au folosit un set the indicatori care au incorporate
durabilitatea ecologică, societală și economică pentru a studia durabilitatea diferitor tehnologii
de tartare a apelor uzate, pentru o capacitate a instalațiilor de 5 milioane de galoane pe zi (MGD)
sau 18,9 x 103
metri cubi. Tehnologiile evaluate au fost mecanice (de exemplu nămol activat cu
tratament secundar), lagună (facultativă, anaerobă și aerobă) și sisteme de tratare a terenurilor
(de exemplu irigarea cu viteză lentă, infiltrarea rapidă și fluxul asupra țării”.
As can be seen from google translation there are many mistakes like the incorrect
formulation of the sentence structure, incorrect translation of the terms (e.g. “durabilitatea
ecologică”, it refers only to ecological aspects, however environmental shall be translated as
“durabilitatea de mediu”, “tratament” which is a medical term, meaning “healing” instead of
“tratare” meaning “cleaning”. Also the word “land” was translated as “country” “’țară”, thus
changing completely the meaning of the text.
Another example given here is the word “sanitation” referring to sewers, water purification
and hygiene. Sanitation comes from sanitary, which also means that something is clean and
healthy, the etymology is of a Latin origin, from “sanus” meaning “healthy”. The second example
is a recently newly formed word “biochar”, which was formed from the combination of two words
“biomass” and “charcoal”.
The translated source text, which is in Romanian, looks like this „Sanitația este definită ca
ansamblu de măsuri pentru protecția sănătății omului și asanarea mediului, legate de asigurarea
igienei și gestionarea eficientă a deșeurilor umane. Măsurile de protecție a sănătății pot fi atît la
nivel de sisteme inginerești complicate (de exemplu rețele de canalizare, stații de tratare, etc.) ori
chiar la nivel de practicare a igienei personale (de ex. spălatul pe mîni cu săpun). Din definiție
reiese că scopurile sanitației cuprind două domenii:

22
1) Protecția sănătății omului prin eliminarea pericolului produs de deșeurile umane;
2) Protectia mediului și a resurselor acvatice prin eliminaraea potențialelor daune cauzate
de gestionarea deșeurilor umane” (Andreev and Andreev, 2010).
Target text, author translation: „Sanitation is defined as a set of measures for the
protection of human health and cleaning of the environment, linked to the hygiene and efficient
management of human waste. Health protection measures can be at the level of complicated
engineering systems (for example sewer networks or treatment stations etc.) or a the level of
practicing of the personal hygiene (e.g. handwashing with soap). From the definition results that
the goal of sanitation covers two areas:
1) Protection of human health through the elimination of the threat produced by human
waste;
2) Protection of the environment and aquatic resources by eliminating the potential
damages caused by human waste management”.
From the translation text we see the term sanitation, which is a culture specific term in
English. In Romanian this term was adjusted. Since in the Dictionary (DEX online1
) the term
sanitație is equivalent to the term cleaning of the environment (salubrizare). However, gradually
this term could become a cross-cultural recognised term.
Google translation:
„Sanitation is defined as a set of measures for the protection of human health and the
environment, related to hygiene and efficient management of human waste. Health protection
measures can be at the level of complicated engineering systems (eg sewer networks, treatment
plants, etc.) or even personal hygiene practice (eg soap-operated handwash). It is clear from the
definition that sanitation purposes include two areas:
1) Protection of human health by eliminating the danger of human waste;
2) Protection of the environment and aquatic resources by eliminating potential damage
caused by human waste management”
As can be seen the text translated into google has few words omissions as follows:
1) the word „asanare” which means cleaning;
This word omission happened because machine translation usually makes simple
substitution of words in one language for words in another, but when it cannot find the closest
1
http://dexonline.net/definitie-sanita%C8%9Bie

23
counterparts in the target language, probable the computer simple omitted the word. If for example
in the case there is a small grammatical errors such as letter omission or misspelling, human
translator will recognize this and correct it, while machine translation will not recognize the word
and will omit it, thus sometimes it can even change the whole sense of the sentence. Also an
inaccurate translation was made in the following sentence: “Din definiție reiese că scopurile
sanitației cuprind două domenii”.Human translation “From the definition results that the goal of
sanitation covers two areas:” Machine translation “It is clear from the definition that sanitation
purposes include two areas”. We found that these two sentences are a bit different in their sense,
for human translation meaning that the goal of sanitation cover two areas (refer to two fields),
while for machine translation „It is clear from the definition that sanitation purposes (here refers
more to the scope of sanitation, what the sanitation does rather than what areas it covers)”. It can
be seen that even a small text passage already can contain few important mistakes such as word
omission or innacurate translation that in scientific translation is inadmissible since the reader does
not need to guess about the results but need to know exactly the meaning. Word omission or
inacurate translation can change a lot the sense of the transmitted knowledge.
4.3 Abbreviations and acronyms
As mentioned in chapter 3, scientific texts make very often use of abbreviations and
acronyms. Among the main reasons for the use of acronyms and abbreviations is to speed up the
reading and ease the understanding of the scientific texts and also sometimes to save space (for
example where there are journal restrictions for this). Acronym is the name for a word made from
the first capital letters of each word, when the article is dealing with series of words. Abbreviations
are used to shorten a word and include not only the first letters (e.g. nm for nanometers). An
acronym is usually pronounced as a single word WHO (World Health Organization), FAO (Food
and Drug Organization), Laser (Light Amplification by Stimulated Emission of Radiation) and
radar (Radio Detection and Ranging) are such words.
The advancement of computer technologies and invention patents allow for an easier
translation and assistance of human translation work. For example, some inventions were made
for automatic recognition of the acronyms in the source text. If an acronym is found in the text,

24
the software register the compound words in the dictionary, thus preventing incorrect translations,
and generating translated texts easy to understand.
In the case of acronym or abbreviation translations, they are reformulated in the target
language, there are cases however, when such words are simply acquired into the target language
as borrowed acronyms: for example “laser” or the word “biochar”. Let’s examine in more details
one of these borrowed acronyms in Romanian language.
Source text Amestecul lacto-fermentat de mase fecale și bio-deșeuri suplimentat de biochar
îmbunătățește creșterea și producția de porumb (Zea mays L.)
Source text “Lacto-fermented mix of faeces and bio-waste supplemented by biochar
improves the growth and yield of corn (Zea mays L.)” (Andreev et al., 2016)
“This study demonstrated that the lacto-fermented mix and biochar had a beneficial effect
on the growth and yield of corn. Although the growth parameters were not consistent for both
production years, the lacto-fermented mix supplemented by biochar contributed to a significant
increase in the key growth parameters such as corn height and leaf length, which probable
influenced the yield. Co-composting nitrogen rich waste such as bio-waste with biochar increases
the nitrate capturing and its delivery to plants as well as stimulates plant growth and biomass
production (Kammann et al., 2015). In spite of the fact that during 2014, the mineral fertilizer had
significantly better effects on the corn height and leaf length than the lacto-fermented mix
supplemented by biochar, it did not have a significantly higher yield during that specific year
(Table 5)”.
Human translation (target text - Romanian) “Acest studiu a demonstrat că amestecul
lacto-fermentat cu biochar a avut un efect benefic asupra creșterii și producției porumbului. Cu
toate că, parametrii de creștere nu au fost uniformi pentru ambii ani de producție, amestecul lacto-
fermentat suplimentat cu biochar a contribuit la sporirea semnificativă a principalilor
parametrilor de creștere, cum ar fi înălțimea porumbului și lungimea frunzelor acestuia, care, se
pare că au influențat și producția lui. Co-compostarea deșeurilor bogate în azot, cum ar fi
deșeurile biodegradabile cu adaos de biochar sporește captarea și livrarea nitraților către plante,
de asemenea stimuleaz creșterea plantelor și producerea de biomasă. În pofida faptului că în 2014
îngrășămintele minerale au avut un efect semnificativ mai bun asupra înălțimii și lungimii
frunzelor la porumb în comparație cu amestecul lacto-fermentat suplimentat cu biochar, acestea
nu am avut o producție semnificativ mai mare de porumb în timpul acelui anumit an”.

25
Machine translation (target text Romanian): “Acest studiu a demonstrat că amestecul
lacto-fermentat și biochimul au avut un efect benefic asupra creșterii și randamentului
porumbului. Deși parametrii de creștere nu au fost consecvenți pentru ambii ani de producție,
amestecul lacto-fermentat suplimentat cu biocar a contribuit la o creștere semnificativă a
parametrilor cheie de creștere cum ar fi înălțimea porumbului și lungimea frunzelor, care probabil
au influențat randamentul. Compostarea deșeurilor bogate în azot, cum ar fi deșeurile biologice,
cu biocarburant, mărește captarea și distribuirea nitratului în plante, stimulează creșterea
plantelor și producția de biomasă (Kammann et al., 2015). În ciuda faptului că în anul 2014,
îngrășământul mineral a avut efecte semnificativ mai bune asupra înălțimii porumbului și a
lungimii frunzelor decât amestecul lacto-fermentat suplimentat cu biochim, nu a avut un
randament semnificativ mai mare în acel an (tabelul 5”).
In this piece of the text we encounter a recently formed scientific term such as “biochar. In
Romanian we found it is acquired as it is, without change (borrowed acronym). According to
Wikipedia2
“biochar is a charcoal used as a soil amendment. We find this term also in other
sources (e.g. Calotescu, 2016), while the machine translates it erroneously as “biochim”, “biocar”
and “biocarburant”. These words practically either are inexistent (e.g. biocar), are used only as
abbreviations, for example the word biochim (abbreviated from biochemistry) or have a
completely different sense in Romanian language (e.g. the word biocarburant, meaning biofuel).
Another error is the use of the term “randament” which means productivity (the amount that was
added compared to a previous one) but not yield, therefore here again we have a change of the
sense, which in scientific papers is not-permissible considering the scientific ethics and the need
to transmit the scientific truth as it is. Another aspect is some cases of the use of prepositional
phrases, which only human understand the subtle differences for example Human translation “în
pofida faptului”, while machine translation uses “in ciuda faptului”. Scientific style, which is more
concrete and more specific usually, make use more often of the formal phrase “în pofida faptului”.
More and more often computer-assisted translation (CAT) is used today to support and
facilitate the work of translators. CAT can accelerate the translation process of humans, by
transforming source text into smaller segments of translated text, so thus the translator consult it
and organize better the text for translation, without the need to spend too much time in finding the
explanations in the printed dictionaries. As a result, the entire process of translating becomes
2
https://en.wikipedia.org/wiki/Biochar

26
more time-efficient. These computer systems support translators, but cannot add to their ability to
edit and manage their own translations, therefore they cannot be treated as independent systems.
That is why CAT can be used as a collaboration between human and computer that results in more
efficient translation process, but not as a completely separated process of whole machine
translation without human intervention.
4.5 The use of passive voice and verb tenses
As I analyzed in chapter 3, passive voice is a very important grammar component to be
taken into consideration when speaking about the writing style of scientific articles. This rules
must be followed in translation too, to obtain the best meaning of the source text. Human can
translate easily according to this criteria. He just follows the grammatical rules and usually doesn’t
abate from them, unless the translation is done by someone who is unacquainted with that. If
speaking about the automated translation big changes in this case won’t be founded. Google
translate follows a certain pattern. It tries to follow the same word order with almost the same verb
tenses, because it translates literally. So, in this case, it should not be considered a problem of
translation. Both humans and computers can cope with this grammatical part. Sometimes, people
can make more mistakes in this case, because they try to combine both types of translations: the
one based on source language and the one based on target language. A human translator can
perceive better the nuances of la language and he would try for sure to put up first the meaning
that the audience receive rather than the grammatical correctness. Unfortunately this thing can be
applied only for literary texts, not for scientific writings, where accuracy is required.
Source text: “In Mexico, coffee is cultivated on the coastal slopes of the central and
southern parts of the country in areas where two or more types of vegetation make contact. Based
on management level and vegetational and structural complexity, it is possible to distinguish five
main coffee production systems in Mexico: two kinds of traditional shaded agroforests (with native
trees), one commercially oriented polyspecific shaded system, and two “modern” systems (shaded
and unshaded monocultures). Traditional shaded coffee is cultivated principally by small-scale,
community-based growers, most of whom belong to some indigenous culture group”(Mogel and
Toledo, 2010).
Human translation: “În Mexic, cafeaua este cultivată pe pantele coastei centrale și de
sud ale țării în locurile unde se întâlnesc două sau mai multe tipuri de vegetație. În baza nivelului

27
de management, complexitatea structurală și cea bazată pe vegetație pot fi deosebite 5 sisteme
importante de producție a cafelei în Mexic: două tipuri de agroforești umbroși tradiționali (cu
copaci nativi), un sistem umbros polispecific orientat către comerț și două sisteme “moderne”
(monoculturi umbroase și neumbroase). Cafeaua tradițională umbrită este cultivată în principal
la scară mică, de către crescătorii comunității, mulți dintre care fac parte din câteva grupuri de
cultură indigene”.
Google translation: “În Mexic, cafeaua este cultivată pe pantele de coastă ale părților
centrale și de sud ale țării, în zone în care două sau mai multe tipuri de vegetație intră în contact.
Pe baza nivelului de management și a complexității vegetale și structurale, este posibil să se facă
distincția între cele cinci sisteme principale de producție a cafelei în Mexic: două tipuri de
agroforești umbroase tradiționale (cu copaci nativi), un sistem polispecific orientat comercial și
două sisteme "moderne" și monoculturi nevăzute). Cafeaua tradițională umbroasă este cultivată
în principal de cultivatori la scară mică, din comunitate, dintre care majoritatea aparțin unor
grupuri de cultură indigene”.
English grammar always was different from many other languages’ grammar, including
Romanian language, which is a case of my study. So, that is why, a human would find it difficult
to translate word-by-word an English text, especially using the same verb tenses as in English. In
the specific piece of article, which follow below, when translated by the author, almost the same
verb tenses as in the original was used, with a small exception: the words “to being a tool” was
changed in the target text with “în devenirea unui instrument”. Sometimes, in order to make it
sound better in Romanian a change in grammatical function of the word is required.
In contrast computers usually do not change a word’s grammatical function, it translates it
the same as in the original. Translators can consult a variety of programs and translation tools to
make a comparison with his translation, so to increase the quality of the final product. Computers
cannot adapt to as many situations as people do, translating with Google translate is not the best
solution for the case of scientific texts. Although scientific texts do not require so much creativity
as literary texts do, it doesn’t mean they should not take into consideration the grammar style.
Source text: “Twenty years ago, land consolidation in some Western European countries
changed from being agricultural/farm-focused to being a tool to cover public demands for access
to land and to resolve the resultant land use conflicts (Thomas, 2004). It has developed from being
commercially focused to being environmentally friendly and more concerned with sustainable land

28
management (Thomas, 1998). A third impetus came from the EU regarding its cohesion policy
within which land consolidation was promoted as an indispensable measure for integrated rural
development (Thomas, 2006a,b)” (Pasakarnis and Maliene, 2010).
Human translation: “Douăzeci de ani în urmă, în unele țări din Europa de Est,
consolidarea terenurilor s-a schimbat din fiind focusată pe agricultură și gospodărie în devenirea
unui instrument care să acopere cererile publicului la accesul terenurilor și în rezolvarea
conflictelor rezultate din folosirea acestora (Thomas, 2004). Aceasta s-a dezvoltat din a fi orientat
către comerț în a fi în armonie cu mediul și mai mult axat pe managemntul durabil al terenurilor
(Thomas, 1998). Un al treilea impuls a venit din partea UE datorită coeziunii sale politice în care
consolidarea terenurilor a fost promovată ca o măsură indispensabilă pentru dezvoltarea rurală
integrată (Thomas, 2006 a,b.)”.
Google translation: “Cu douăzeci de ani în urmă, consolidarea terenurilor în unele țări
din Europa de Vest s-a schimbat de la orientarea agricolă / fermă spre a fi un instrument pentru
a acoperi cererile publice de acces la pământ și pentru a rezolva conflictele de utilizare a
terenurilor (Thomas, 2004). Sa dezvoltat de la a fi orientat comercial spre a fi prietenos cu mediul
și mai preocupat de gestionarea durabilă a terenurilor (Thomas, 1998). Un al treilea impuls a
venit din partea UE în ceea ce privește politica de coeziune în cadrul căreia consolidarea
terenurilor a fost promovată ca o măsură indispensabilă pentru dezvoltarea rurală integrată
(Thomas, 2006a, b)”.
4.6 The use of graphical representation (tables and graphs)
Most of the scientific papers in environmental and biological sciences use graphs and tables
for representing numerical or statistical data in a time- and space-effective manner. Graphical
representation make the readers to perceive better the data, since they are easy-reading, as
compared to reading a long text. At the manuscript screening stage, offer reviewers and journal
editors a quick overview of the most important study findings, and once the paper is published,
these are transmitted to the readers. These visual elements help authors to reflect on the detailed
results and complex relationships between different factors reflected in the paper, patterns, and
trends and enhance readers. When introducing graphs or tables in google translate, it receives it as
a plain text, without formatting. Therefore, most important for an accurate translation is that human

29
performs this task for the visual aids of an article (tables and graphs), however, it can make use of
some computer assisted programs to consult the unknown terms.
4.7 Language requirements of peer reviewed journals
Manuscripts of scientific articles submitted to peer-reviewed journals (for example such as
specialized scientific journals published by Elsevier, Springer or Taylor and Frances) are usually
analyzed critically by the Editor or an Editorial board before it is sent to the peer review process.
Peer review is a rather meticulous process since it is usually performed by at least two or three
referees, who know very well English and are very strong experts on their subject. At the same
time, improving English of an article, the article is getting more chances to be accepted at either
Editorial or peer review stage. According to statistical data offered by Elsevier (Shaik, 2016), 30-
50 % of articles submitted to Elsevier journals are rejected even before they can reach the stage of
peer-review process, and among the main reasons of rejection is poor English. An article that is
properly written, properly edited will create a professional image about the undertaken research
not only for the reviewers but also for the targeted scientific community. That is why translators
and editors of English for academic and scientific writing are more and more required. These
specialists need to have a high level of competence, be in line with up-to-date information in
science and also be familiar with computer assisted tools for translation that can enhance their
work efficiency.
Now it became popular that the journal themselves hire translators and specialists in linguistics
for increasing the quality of the papers. For example, Elsevier3
provide services for English editing
and translation of scientific, technical and medical papers. Edition of the paper is done by native
speakers, selected among PhD or PhD candidates according to the field of study. Since a
specialist in linguistics also know the linguistics aspects it would be good if Faculties would have
their specialized departments or specialization for scientific translation, since the demand for these
specialists is currently increasing.
3
http://webshop.elsevier.com/languageservices

30
Conclusions and recommendations
The thesis reflects an original text based on a compilation of literature studies as well as
translation and critical analysis of pieces of scientific articles from the field of biological and
environmental sciences. Today with an increase in competitiveness for peer review journals with
a recognized impact factor and the need for publication of high quality scientific papers it is
particularly important for correct translation and also assessing the language accuracy and
correctness.
The scientific translation is different from literary translation. In contrast to literary texts,
scientific texts have specific grammar patterns, a clear indication of interconnectedness and
interdependence of the sentences, a specific writing style and terminology. These texts apply
different abbreviations and acronyms and make use of graphical representation of data. The
target text in scientific translation shall maintain the same meaning as the source text, so thus
not to change the scientific hypothesis or statement which form and transmit the scientific truth
and knowledge. A translator of scientific texts from English into Romanian and opposite shall
have not only very good knowledge of English and Romanian and equivalency between these two
languages, but also know very well the subject field.
With the development of computer technologies and online translation tools, the
resources available to the translator has introduced big changes in translation process, including
the scientific works, speeding up the process compared to the conventional use of printed
dictionaries for example. The practical exercise of translating specific scientific texts and
comparing to Google Translate showed that owing to a more simplistic strategy in translation,
machine translation commits big errors in translation of scientific texts, e.g. word omission,
incorrect use of terms and grammar and even replacing with wrong terms. In many cases this led
to a complete changing of the meaning of the transmitted scientific statement, which is non-
acceptable in modern science. Translators need to accept the new translating tools and learn
how to make use of them efficiently in order maximize their potential, quality and work
productivity. This cannot however replace completely human translation since machine
translation should not be treated as an independent translation system, but a tool that helps the

31
translator to be more efficient. In the case of scientific translation, where not only technical and
scientific precision is required but also the nuances of language grammar according to specific
context it is very important to rely on human based translation.
The current thesis is innovative since there is limited research on comparison between
human versus machine translation in scientific translation and concrete examples with specific
pieces of translations are currently lacking. The recommendations as well as the translation
examples presented in chapter 4 are useful for students or young specialists engaged in the
translation process in the field of biological and environmental sciences. Such specialists in the
Republic of Moldova and Romania are very limited. It is important that the Department of
Literature and Languages of West University of Timisoara also considers to include the
specialization on scientific translation.

32
References:
1. Adams, H. 1967. The Interests of Criticism. New York: Harcourt Brace and World Inc.
2. Andreev, N., Ronteltap, M., Lens, P., Boincean, B., Bulat, L., Zubcov, E., 2016. Lacto-fermented
mix of faeces and bio-waste supplemented by biochar improves the growth and yield of corn (Zea
mays L.). Agriculture Ecosystems and Environment, 232, 263-272.
3. Andreev S. and Andreev N., 2010 Sanitatia ecologică, Chisinau, Wisdom.
4. Calotescu T., 2016 Biochar şi gazogen din resturi vegetale. Available from
http://www.agrimedia.ro/articole/biochar-si-gazogen-din-resturi-vegetale on 02.09.2017.
5. Essay UK, n.d. Impersonal style and passive verb construction Available from
http://www.essay.uk.com/guides/essay/impersonal-passive.php on 19 of July, 2017
6. Craciunescu, O., Gerding-Salas, C., Stringer-O'Keeffe, S., 2004 Machine Translation and Computer-Assisted
Translation: a New Way of Translating? Translation Journal, 8, 3. Available from http://www.mt-
archive.info/TranslationJ-2004-Craciunescu.pdf on 05.08.2017.
7. Hopkins, W. 1999 Guidelines for scientific writing. Available from
http://www.sportsci.org/jour/9901/wghstyle.html on 17 of July, 2017.
8. Hutchins, J. International Journal of Translation 13, 1-2 Jan-Dec 2001, pp.5-20. Special theme
issue on machine translation, edited by Michael S. Blekhman]
9. Li, H., A. Graesser, and Z. Cai. 2014. “Comparison of Google translation with human translation.”
In Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research
Society Conference, eds. W. Eberle, and C. Boonthum-Denecke. Palo Alto, CA: AAAI Press, 190–
5.
10. LearnThatWord, 2005 Root Words & Prefixes: Quick Reference
https://www.learnthat.org/pages/view/roots.html
11. Mack, R. N., Simberloff, D., Mark Lonsdale, W., Evans, H., Clout, M. and Bazzaz, F. A. (2000), Biotic
invasions: causes, epidemiology, global consequences and control. Ecological Applications, 10:
689–710.
12. Matacic, C., 2016. Google’s new translation software is powered by brainlike artificial

33
intelligence. Available from http://www.sciencemag.org/news/2016/09/google-s-new-
translation-software-powered-brainlike-artificial-intelligence on 20 of July, 2017.
13. McCarthy, E. 2013. Root Word Dictionary. Available from http://www.macroevolution.net/root-
word-dictionary.html. Access date 05.09.2017
14. Mogel, P. and Toledo, V. Moguel, P. and Toledo, V. M. (1999), Biodiversity Conservation in
Traditional Coffee Systems of Mexico. Conservation Biology, 13: 11–21.
15. Muga, H. and Mihelcic, J. 2008. Sustainability of wastewater treatment technologies. Journal of
Environmental Management, 88, 437-447.
16. Naidu, A. S. Bidlack, W. R, Clemens, R. 1999. A.Probiotic Spectra of Lactic Acid Bacteria (LAB)
Critical Reviews in Food Science and Nutrition Vol. 39 , 113-126.
17. Panter, M. Translating academic writing: human vs. machine translation. American Journal
Experts. Available from http://www.aje.com/en/arc/translating-academic-writing-human-vs-
machine/ on 20 of July, 2017.
18. Pasajarbus and Maliene, 2010. Towards sustainable rural development in Central and Eastern
Europe: applying land consolidation. Land Use Policy, 27 (2), 545-549.
19. Pritchard, G. and Coolbear, T. 1993. The physiology and biochemistry of the proteolytic system
in lactic acid bacteria. FEMS Microbiology Reviews, 12, 179-206.
20. Shaikh, A. 2016 7 steps to publishing in a scientific journal. Available from
https://www.elsevier.com/connect/7-steps-to-publishing-in-a-scientific-journal. Access date:
04.09.2017
21. Soualmia, M. 2010. Third year students difficulties in translating computing terms English into
Arabic, PhD thesis, Mentouri University-Constantine.
22. Slutz, S., Hess, K. Data Analysis for Advanced Science Projects. Available from
https://www.sciencebuddies.org/science-fair-projects/top_research-project_data-
analysis.shtml on 21 of July, 2017.
23. The University of Melbourne, 2012 Using tenses in scientific writing. Available from
http://services.unimelb.edu.au/__data/assets/pdf_file/0009/471294/Using_tenses_in_scientifi
c_writing_Update_051112.pdf on 20 July, 2017
24. Weinrich, H. (1976) “Kommun Ikation, Instruktion, Text”, In Weinrich (ed.), pp. 11-20.

34
25. Yang, L. Giannis, A. Chang, V., Liu, B, Zhang, J., Wang, J. 2015. Application of hydroponic systems
for the treatment of source-separated human urine. Ecological Engineering, 8, 182-191.

Teza andreev alina final

Recommended

Recommended

More Related Content

Similar to Teza andreev alina final

Similar to Teza andreev alina final (20)

Recently uploaded

Recently uploaded (20)

Teza andreev alina final