Ministry of Higher Education and Scientific Research

Kasdi Merbah Ouargla University

Faculty of Letters and Languages
Department of Letters and English Language

Dissertation submitted in partial fulfilment of the requirement for the Master’s Degree in
field of
Specialty: Translation

English-Arabic-English-

Investigating Accuracy of Translating and Interpreting into Arabic of Scan

Translator
( Scan Translator) Quality and Accuracy
Submitted and publicly defended by

Mohammed Oussama LABED/Abderrahman TABBOUCHA

Supervised by
Prof. Djamel GOUI
Board of Examiners
Dr. Oualid MESSAOUDI UNIV.OUARGLA Chairman

Prof. Djamel GOUI UNIV.OUARGLA Supervisor

Dr. Sief Eddine GUENDOUZ UNIV.OUARGLA Examiner

Academic Year: 2023 –2024

 ‫ﻛﻠﯿﺔ اﻵداب واﻟﻠﻐﺎت‬
‫ﻗﺴﻢ اﻟﻠﻐﺔ اﻻﻧﺠﻠﯿﺰﯾﺔ‬

‫ﻣﺬﻛﺮة ﻣﻘﺪﻣﺔ ﻻﺳﺘﻜﻤﺎل ﻣﺘﻄﻠﺒﺎت ﻧﯿﻞ ﺷﮭﺎدة اﻟﻤﺎﺳﺘﺮ‬

‫اﻟﺘﺨﺼﺺ‪ :‬ﺗﺮﺟﻤﺔ‬
‫إﻧﺠﻠﯿﺰﯾﺔ‪-‬ﻋﺮﺑﯿﺔ‪-‬إﻧﺠﻠﯿﺰﯾﺔ‬
‫اﺳﺘﻘﺼﺎء دﻗﺔ اﻟﺘﺮﺟﻤﺔ اﻟﺘﺤﺮﯾﺮﯾﺔ واﻟﺘﺮﺟﻤﺔ اﻟﻔﻮرﯾﺔ إﻟﻰ اﻟﻠﻐﺔ اﻟﻌﺮﺑﯿﺔ ﺑﺎﺳﺘﺨﺪام‬
‫ﺳﻜﺎن ﺗﺮاﻧﺰﻟﯿﺘﺮ‬
‫ﺟﻮدة ﺳﻜﺎن ﺗﺮاﻧﺰﻟﯿﺘﺮ ودﻗﺘﮫ ﻓﻲ اﻟﺘﺮﺟﻤﺔ‬
‫إﻋﺪاد اﻟﻄﺎﻟﺐ‬

‫اﻟﻌﺎﺑﺪ ﻣﺤﻤﺪ أﺳﺎﻣﺔ‪ /‬ﻋﺒﺪ اﻟﺮﺣﻤﺎن طﺒﻮﺷﺔ‬

‫ﺗﺤﺖ إﺷﺮاف‬

‫اﻟﺒﺮوﻓﯿﺴﻮر اﻟﺪﻛﺘﻮر ﺟﻤﺎل ﻗﻮي‬

‫ﺟﺪول اﻟﻠﺠﻨﺔ اﻟﻤﺸﺮﻓﺔ‬
‫اﻟﺮﺋﯿﺲ‬ ‫ﺟﺎﻣﻌﺔ ورﻗﻠﺔ‬ ‫اﻟﺪﻛﺘﻮر وﻟﯿﺪ ﻣﺴﻌﻮدي‬

‫اﻟﻤﺸﺮف‬ ‫ﺟﺎﻣﻌﺔ ورﻗﻠﺔ‬ ‫اﻟﺒﺮوﻓﯿﺴﻮر ﺟﻤﺎل ﻗﻮي‬

‫اﻟﻤﻨﺎﻗﺶ‬ ‫ﺟﺎﻣﻌﺔ ورﻗﻠﺔ‬ ‫اﻟﺪﻛﺘﻮر ﺳﯿﻒ اﻟﺪﯾﻦ ﻗﻨﺪوز‬

‫اﻟﺴﻨﺔ اﻷﻛﺎدﯾﻤﯿﺔ ‪2024-2023:‬‬

 I

Dedication

I dedicate this modest work to my beloved Father and Mother for their, patience,
care, and continuous support during the five years of my study

Thank you for everything.

To all my family.

Mohammed Oussama LABED

 II

Dedication

I dedicate this modest work to my beloved Father and Mother for their, patience,
care, and continuous support during the five years of my study

Thank you for everything.

To all my family.

Abderrahman TABBOUCHA
 III

Acknowledgments
First and foremost, we would like to express my deepest appreciation to my

supervisor, PROF Djamel GOUI, for whom we find it futile to complain.

Professor GOUI gave us a lot of inspiration for our academic career and gave us

countless support including personal support. Without him, we feel uncertain if

I can reach my master's degree, and we would also like to thank other members

in thesis committee While we were writing these lines of recognition, it struck

me that 5 years had already passed, very quickly but really rewarding. At the

beginning of the baccalaureate degree, we thought it would be a long and

painful multi-year period of my life (yes, there were fluctuations!), But by the

time we were about to finish, my study duration was surprisingly short as we

kept wondering: Would we have the opportunity to live again in such a

stimulating, inspiring and caring environment with little pressure and complete

freedom for academic and personal development offered by the University of

KASDI MARBAHOUARGLA. All these won't be possible without the help of a

lot of people. And our Examiners for all their efforts that help us to

deposited our dissertation

 IV

List of abbreviations
AI : Artificial Intelligence

ANI : Artificial Narrow Intelligence

AGI Artificial General Intelligence

ASI: Artificial Super Intelligence

CAGR: Compound Annually Growth Rate

DOD: Department of Defence

ESL: English as A Second Language

IELTS: International English Language Testing System

MT: Machine Translation

ML: Machine Learning

MTPE: Machine Translation Post-Editing

MTQE: Machine Translation Quality Estimation

NLP: Natural Language Processing

OOP: Object-Oriented Programming

ST: Source Text

TT: Target Text

TOEFL: Test of English as a Foreign Language

 V

Table of contents

Dedication................................................................................................................................ II

Acknowledgments..................................................................................................................... III
List of abbreviations .................................................................................................................IV
Table of contents ........................................................................................................................V
Abstract ...................................................................................................................................VIII
1. Purpose................................................................................................................................. 2
.2 Literature Review................................................................................................................. 3
3. Research Question ............................................................................................................... 5
3.1. Hypotheses............................................................................................................... 7
3.2. Aims......................................................................................................................... 7
3.3. Objectives and subjective reasons ........................................................................... 7
4. Methodology ...................................................................................................................... 10
5. Structure of the study ......................................................................................................... 11
6. Significance of the study .................................................................................................... 11
7. The Limitation of the Study ............................................................................................... 12

Chapter one:
The Theoretical:
Part one: Artificial Intelligence

Introduction.............................................................................................................................14

1.Translation in the past…………………………………………………………………….14

2.Translation and interpreting in Algeria...............................................................................14

3.Difficulties in translation and interpreting..........................................................................15
4.Objectives of Translation and the Death of the Truth ........................................................15
4.1 Translate to Introduce the Other..................................................................................... 16
4.2Translate To Influence the Other In this second objective...............................................16
 VI

5. Historical Development of Artificial Intelligence .......................................................... 176.

6. Types of Artificial Intelligence: ......................................................................................... 18
6.1. Artificial Narrow Intelligence (ANI):.................................................................... 18
6.2. Artificial General Intelligence (AGI): ................................................................... 19
6.3. Artificial Super Intelligence (ASI): ....................................................................... 19
7. The main areas of research and development in AI? ......................................................... 20
8. Definition of robotics? ....................................................................................................... 20
9. Themes of Artificial Intelligence ....................................................................................... 21
10. The AI Environment: ......................................................................................................... 21
conclusion

Part Two:
Quality of (AI) scan Translator in translation & interpretation
Introduction .............................................................................................................................. 21
1.Difficulties of translation into Arabic...................................................................................22

2. Definition of Machine Translation..................................................................................... 23

3. Problems in machine Translation....................................................................................... 24
4. Machine translation evaluation .......................................................................................... 24
5. MT quality assessment ....................................................................................................... 25
6. Neural network machine translation .................................................................................. 25
7. The limitations of machine translation .............................................................................. 26
8. AI in interpreting................................................................................................................ 26
8. Machine Translation Quality Estimation ........................................................................... 27
conclusion

Chapter Two:
The Practical Part
Introduction .............................................................................................................................. 29
1. Vormor-x2 Translation Pen Scanner ................................................................................. 30
2. Product Description ........................................................................................................... 30
 VII

2.1. Power on / off Power on: ....................................................................................... 30

2.2. Connect Wi-Fi ....................................................................................................... 30
2.3. Scan translation...................................................................................................... 31
2.4. Voice translation .................................................................................................... 31
2.5. Photo translation .................................................................................................... 31
2.6. Text excerpt Click ................................................................................................. 31
2.7. Smart record Click ................................................................................................. 31
2.8. Vocabulary Click “ ................................................................................................ 31
2.9. 112 languages voice translator .............................................................................. 32
2.10. Two-way Speech Translation–Scan and edit on the go! ....................................... 32
2.11. Smart Recording & File Transfer .......................................................................... 32
2.12. Reliable After-Sales Guarantee & Online Software Update– ............................... 32
2.13. Translation pen scanner with 3.5-inch Capacitive Touch Screen Our dictionary
scanner pen support 112 language translations,................................................................. 32
3. Definition of the corpus ..................................................................................................... 33
4. Patterns ............................................................................................................................... 34
.5 Observations: ..................................................................................................................... 37
6. Findings: ............................................................................................................................ 39
Conclusion ............................................................................................................................... 40
References ................................................................................................................................ 47
Appendices ............................................................................................................................... 49
‫ﻣﻠﺨﺺ اﻟﺪراﺳﺔ‬
 VIII

Abstract
Artificial intelligence has significantly improved the translation process, making it more
efficient, accurate and accessible. Machine translation systems and computer-assisted translation
tools (such as Scan Translator) provide instant translation and real-time interpretation, allowing
for faster task management. AI-powered CAT technology also automatically recommends
translations based on context and memory. This paper studies translation and provides an in-
depth study of Scan Translator. discussing the role of artificial intelligence in translation and its
importance to the way translators (scan translator) work and the quality of translations. My
contributions include analysis and research on devices, explaining the importance of devices in
translation from both pros and cons, and improving attention mechanisms for contextual
translation from text to target text, we discuss how to use data from a variety of tasks such as
analysis And generating a photo caption, I conclude with how my work influences subsequent
research as well as providing in-depth coverage of translation study, and speculating on the
future elements needed to enhance MT in translation. We noticed that the scan translator
provided a lot of facilities for the user, however, when we use it, we found some errors, therefore,
it cannot be reliable in translation and it cannot be compared to the translator( human)

Keywords: Artificial Intelligence- Machine Translation -Scan Translator-Translations-

‫ﻣ�خﺺ‬
‫ ﺗﻮﻓﺮ أﻧﻈﻤﺔ اﻟ��ﺟﻤﺔ‬.‫ ﻣﻤﺎ ﺟﻌﻠهﺎ أﻛ�� ﻛﻔﺎءة ودﻗﺔ وﺳهﻮﻟﺔ �� اﻟﻮﺻﻮل إﻟ��ﺎ‬،��‫ﻟﻘﺪ أدى اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� إ�� ﺗﺤﺴ�ن ﻋﻤﻠﻴﺔ اﻟ��ﺟﻤﺔ �ﺸ�ﻞ ﻛﺒ‬
‫ ﻣﻤﺎ �ﺴﻤﺢ ﺑﺈدارة اﳌهﺎم �ﺸ�ﻞ‬،��‫اﻵﻟﻴﺔ وأدوات اﻟ��ﺟﻤﺔ ﺑﻤﺴﺎﻋﺪة ا�حﺎﺳﻮب )ﺳ�ﺎن ﺗﺮاﻧﺰﻟﻴ��( ﺗﺮﺟﻤﺔ ﻓﻮر�ﺔ وﺗﺮﺟﻤﺔ ﻓﻮر�ﺔ �� اﻟﻮﻗﺖ اﻟﻔﻌ‬
.‫ﺑﻨﺎء ﻋ�� اﻟﺴﻴﺎق واﻟﺬاﻛﺮة‬ ً
ً ‫ﺗﻠﻘﺎﺋﻴﺎ ﺑﺎﻟ��ﺟﻤﺎت‬ ‫ ﻛﻤﺎ ﺗﻮ�ىي ﺗﻘﻨﻴﺔ اﻟ��ﺟﻤﺔ ﺑﻤﺴﺎﻋﺪة ا�حﺎﺳﻮب اﳌﺪﻋﻮﻣﺔ ﺑﺎﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� ﺑﺎﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ‬.‫أﺳﺮع‬
‫ وﺗﻨﺎﻗﺶ دور اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� �� اﻟ��ﺟﻤﺔ‬.��‫ﺗﺪرس هﺬﻩ اﻟﻮرﻗﺔ اﻟﺒﺤﺜﻴﺔ اﻟ��ﺟﻤﺔ وﺗﻮﻓﺮ دراﺳﺔ ﻣﺘﻌﻤﻘﺔ ﻟﻠ��ﺟﻤﺔ ﻋﻦ ﻃﺮ�ﻖ ﺳ�ﺎن ﺗﺮاﻧﺰﻟﻴ‬
‫ وﺷﺮح أهﻤﻴﺔ‬،‫ وﺗﺘﻀﻤﻦ ﻣﺴﺎهﻤﺎ�ﻲ ﺗﺤﻠﻴﻞ و�ﺤﺚ ﻋﻦ اﻷﺟهﺰة‬.‫وأهﻤﻴﺘﮫ ﺑﺎﻟنﺴﺒﺔ ﻟﻄﺮ�ﻘﺔ ﻋﻤﻞ اﳌ��ﺟﻤ�ن )ﺳ�ﺎن ﺗﺮاﻧﺰﻟﻴ��( وﺟﻮدة اﻟ��ﺟﻤﺎت‬
‫ وأﻧﺎﻗﺶ ﻛﻴﻔﻴﺔ‬،‫ وﺗﺤﺴ�ن آﻟﻴﺎت اﻻﻧتﺒﺎﻩ ﻟﻠ��ﺟﻤﺔ اﻟﺴﻴﺎﻗﻴﺔ ﻣﻦ اﻟﻨﺺ إ�� اﻟﻨﺺ اﻟهﺪف‬،‫اﻷﺟهﺰة �� اﻟ��ﺟﻤﺔ ﻣﻦ ﺣﻴﺚ اﻹﻳﺠﺎﺑﻴﺎت واﻟﺴﻠﺒﻴﺎت‬
‫ وأﺧﺘﺘﻢ ﺑﻜﻴﻔﻴﺔ ﺗﺄﺛ�� ﻋﻤ�� ﻋ�� اﻷﺑﺤﺎث اﻟﻼﺣﻘﺔ ﺑﺎﻹﺿﺎﻓﺔ‬،‫اﺳﺘﺨﺪام اﻟﺒﻴﺎﻧﺎت ﻣﻦ ﻣﺠﻤﻮﻋﺔ ﻣﺘﻨﻮﻋﺔ ﻣﻦ اﳌهﺎم ﻣﺜﻞ ﺗﺤﻠﻴﻞ وﺗﻮﻟﻴﺪ �ﻌﻠﻴﻖ اﻟﺼﻮرة‬
�� ‫ واﻟﺘﻜهﻦ ﺑﺎﻟﻌﻨﺎﺻﺮ اﳌﺴﺘﻘﺒﻠﻴﺔ اﻟﻼزﻣﺔ ﻟﺘﻌﺰ�ﺰ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ‬،‫إ�� ﺗﻘﺪﻳﻢ �ﻐﻄﻴﺔ ﻣﺘﻌﻤﻘﺔ ﻟﺪراﺳﺔ اﻟ��ﺟﻤﺔ‬
‫ﻻﻳﻤﻜﻨﺎﻻع‬،��‫و�ﺎﻟﺘﺎ‬،‫وﺟﺪﻧﺎ�ﻌﻀﺎﻷﺧﻄﺎء‬،‫ﻋﻨﺪﻣﺎاﺳﺘﺨﺪﻣﻨﺎﻩ‬،‫وﻣﻌﺬﻟﻚ‬،‫ﻻﺣﻈﻨﺎأﻧﻤ��ﺟﻤﺎﳌ�حﺎﻟﻀﻮﺋﻴﻘﺪﻣﺎﻟﻜﺜ��ﻣﻨﺎﻟتﺴهﻴﻼﺗﻠﻠﻤﺴﺘﺨﺪم‬.‫اﻟ��ﺟﻤﺔ‬
(‫ﺗﻤﺎدﻋﻠﻴﮫ �� اﻟ��ﺟﻤﺔ وﻻ ﻳﻤﻜﻦ ﻣﻘﺎرﻧﺘﮫ ﺑﺎﳌ��ﺟﻢ( اﻟبﺸﺮي‬
‫اﻟ��ﺟﻤﺔ‬-- ��‫ﺳ�ﺎن ﺗﺮاﻧﺰﻟﻴ‬-��‫اﻟ��ﺟﻤﺔ اﻵ‬-��‫اﻟ�ﻠﻤﺎت اﳌﻔﺘﺎﺣﻴﺔ اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ‬
Résumé
L'intelligence artificielle a considérablement amélioré le processus de traduction, le rendant
plus efficace, plus précis et plus accessible. Les systèmes de traduction automatique et les outils
de traduction assistée par ordinateur (tels que les Scan Translator) fournissent une traduction
instantanée et une interprétation en temps réel, ce qui permet une gestion plus rapide des tâches.
La technologie de TAO alimentée par l'IA recommande également automatiquement des
traductions basées sur le contexte et la mémoire. Cet article étudie la traduction et fournit une
étude approfondie de la traduction par balayage. Il discute du rôle de l'intelligence artificielle
dans la traduction et de son importance pour la façon dont les traducteurs Scan Translator)
travaillent et pour la qualité des traductions. Mes contributions incluent l'analyse et la recherche
sur les dispositifs, expliquant l'importance des dispositifs dans la traduction à la fois pour et
contre, et améliorant les mécanismes d'attention pour la traduction contextuelle du texte au
texte cible, je discute de la façon d'utiliser les données à partir d'une variété de tâches telles que
l'analyse et la génération d'une légende de photo, je conclus sur la façon dont mon travail
influence la recherche ultérieure ainsi qu'en fournissant une couverture en profondeur de l'étude
 IX

de la traduction, et en spéculant sur les éléments futurs nécessaires pour améliorer la traduction
automatique en traduction. Nous avons remarqué que le traducteur par balayage offrait de
nombreuses facilités à l'utilisateur, cependant, lorsque nous l'avons utilisé, nous avons trouvé
quelques erreurs, par conséquent, il ne peut pas être fiable dans la traduction et il ne peut pas
être comparé au traducteur) humain)
Mots clés Intelligence artificielle -Traduction automatique - Scan Translator-Traductions
Introduction
 1

Statement of the Problem:

Exploring the precision of translation and interpretation into Arabic using Scan
Translator reveals a diverse world in which human and artificial intelligence
intersect. This study delves into the relationship between traditional language
knowledge and the advances brought forth by AI technology. By evaluating Scan
Translator's accuracy, the intricate dynamics driving communication in the digital
age are uncovered, where AI functions as both a facilitator and a challenger to
traditional translation approaches. The enormous global development has led to
technological innovations reaching various spheres of life, including translation.
Numerous computer translation applications have emerged, increasing in quality
alongside their evolution through artificial intelligence-based software systems.
These applications play an important role in assisting humans in various areas of
linguistic work that require translation. With rapid advances in science and
technology, artificial intelligence techniques have evolved significantly. As a
result of this development, there have been dramatic transformations in the area
of translation in recent decades. Owing to the increasing demand for translation
services due to increasing global connectivity, various translation tools have
emerged and automated translation technology has evolved rapidly. The accuracy
of artificial intelligence translation is an exciting area of rapid development in
information technology. This area is aimed at developing artificial intelligence
systems capable of translating texts into different languages in a way that
approaches human thinking. The accuracy of artificial intelligence translation
involves the use of advanced techniques from areas such as computer-language
science, machine learning, and artificial nerve networks. Translation and
interpretation using a scanner are modern applications of auto-translation
technology that are of interest to many, especially in an era of global connectivity
and the growing need to understand different languages
 2

Artificial translation does not aim to eliminate the need for human translators, but
rather to support them and simplify the process from one thousand to the next.
More specifically, artificial intelligence is used to help you work smarter, not
harder, with better translation quality throughout the process. Translation of
Arabic, which is one of the most widely spoken languages and contains a large
number of vocabularies, and translation is not only a translation of words, through
words and sentences, but also a transfer of traditions and likes that inevitably
affect the translation of texts that convey the meanings of a text from one
language to another, taking into account accuracy and style. This requires
understanding the original text and expressing content and style in another
language. Translator must master both languages. Translator and translator.
Therefore, some scholars and translation specialists believe that it is not only the
transmission of language content, but also the transfer of cultural concepts, values
and norms to the reader or listener of the language.

1. Purpose

The purpose of the study is to evaluate machine translation's precision and

quality in the context of translation and interpreting services. Even with these
developments, there are still concerns regarding their dependability in producing
precise and excellent translations. The goal of the study is to provide important
insights into the following areas: the degree to which machine translation systems
can equal or exceed human competence; the precision with which they can
convey nuances and cultural subtleties; the obstacles and constraints associated
with obtaining high accuracy; and the ways in which these aspects affect the
practice of interpreting in real-time situations. The study also aims to comprehend
end users', interpreters', and translators' viewpoints on the application of machine
translation technologies in the workplace. The study adds to the current
conversation on the function of technology in language services.
 3

2. Literature Review

The study of Wesam Mohsen Tahseen1 and Shifa’a Hadi Hussein 2024
under the title Investigating Machine Translation Errors in Rendering English
Literary Texts into Arabic the study ends with the conclusions that all machine
translation programs (Google Translate (GT), Reverso Translation (Reverso. T),
Bing Microsoft Translation (Bing. M.T) in rendering English literary texts from
English into Arabic are unacceptable and have more problems because these
programs are just machines and cannot think or feel as well as all these machines’
renderings are meaningless and ambiguous. So Human translation is better than
Machine Translation because the first uses communicative translation while the
other uses semantic translation.

The study of( Hamad Abdullah H. Al-Dosari 2023)under the title

Comparing the performance of Google Translate and SYSTRAN in the Arabic
dictionary This study attempted to examine how two MT systems deal with
Arabic lexical ambiguity when translating from Arabic into English. Evaluation
of the results shows that both MT systems (Google Translate and SYSTRAN)
struggled with the three chosen linguistic features (homonyms, heteronyms, and
polysemes. Between the two systems, Google Translate was the clear winner,
with a better translation of almost every sentence in the test suite. Still, both
systems are far from perfect when dealing with lexical ambiguity. Overall, both
systems scored better in intelligibility than in accuracy.

The study of effects of pre-editing operations on audio-visual translation using

TRADOS: an experimental analysis of Saudi students’ translations( Chaouki
Bounaas Bahia Zemni, Fadiah Al Shehri and Mimouna Zitoun)2023 Neural
Machine Translation (NMT) is a revolutionary innovation that has had a
significant impact not only on the translation industry but also on translation
studies. This technology is creating new opportunities for shaping identities and
 4

generating new knowledge and perspectives. This led researchers to undeniably

and increasingly conduct studies to improve NMT performance. These studies
involve assessing the quality of the output, determining the extent to which
humans can be involved in the machine-based process, and proposing solutions
to redress the deficiencies. In this regard, the paper focuses on the impact of pre-
editing (PE) operations on the translation of audio-visual children’s literary texts
(subtitles) from English to Arabic using TRADOS. The work seeks to accomplish
a number of pre-editing-related research goals in the context of Arabic NMT
systems. Initially, it aims to define and clarify the idea of PE and its function in
enhancing Arabic NMT systems’ performance. Second, it looks at PE
mechanisms and methods and how they might improve the appropriateness and
accuracy of Arabic machine translation. Additionally, the study attempts to
investigate the value of PE in enhancing the Arabic translation of audio-visual
children’s literature. The study also seeks to list the difficulties and restrictions
related to PE and suggest viable strategies to get over them. Finally, the paper
offers suggestions for further investigation into NMT systems using Arabic and
PE. To achieve these goals, the researchers conducted a human evaluation of
NMT for two animated movie subtitles and determined the necessary PE
operations. The findings revealed that PE has the potential to improve the quality
of literary translations and enhance their comprehensibility and acceptability.

The study of Investigating Machine Translation of Technical Texts, A

Comparative Study between Bing and Index Translation Machines,) Hiame Hizi
2020)first by comparing translations of texts. The technology using the Bing and
Yandex systems to translate from Arabic to English and how can that Translations
must be close to the correct equivalents in the English language. How translation
systems translate and the difficulties encountered Yandex Translation was the
weakest system because when I translated the three technical texts, it translated a
 5

large number It contained grammatical, semantic, and morphological errors, and

its translation was generally incomprehensible, and the meaning could not be
reached. The correct original text. This is due to the difficulty of the Arabic
language and the difficulty of understanding it in the Yandex system. While it
was Bing Translation program is the best in translating technical texts because it
is able to translate understandable sentences, He reached the intended meaning of
the original text because he did not face many difficulties in translating the Arabic
language into English.

Quality and Machine Translation: An Evaluation of online Machine Translation

of English into Arabic Texts Mohammed Abdulmalik Ali.2020

This study compares the translation outputs of an English into Arabic text using
the three machine translators of Google Translate, Microsoft Bing, and Ginger.
To carry this evaluation of the machine translation (MT) outputs, an English text
and its Arabic counterpart were selected from the UN records. The English source
text was segmented into 84 semantic chunks. Depending on the Arabic
counterpart model text, each chunk was rated as “correct or incorrect” at the two
levels of the translation attributes: fidelity and intelligibility. To perform the
quantitative description of the evaluation process, the numbers of fidelity and
intelligibility errors and their percentages were calculated. Results of this
evaluation process revealed that none of the three translated versions of the source
text was perfectly translated. Although the translation of Microsoft Bing was
rated the best, Google’s translation was found the least accurate due to the high
percentage of fidelity and intelligibility errors detected in its translation output.
However, the quality of Ginger’s translation was found slightly less accurate than
that of Microsoft Bing, but remarkably better than Google’s translation. The
findings of this study imply that these MT applications can be implemented to
perform English into Arabic translation to get the broad gist of a source text, but
 6

a deep and thorough post-editing process looks essential for a full and accurate
understanding of an English into Arabic MT output. The study recommends that
more studies are encouraged to continue to assess the quality of MT that will
further highlight its weaknesses and the strategies that should be adopted to over
comet hem.

Machine Translation in the Arab World: Saudi Arabia as a Case Study,( Faten
Almutawa & Sattar Izwaini 2015). There has been an increasing interest recently
in machine translation technology in the Arab world, especially with the growing
demand for translation. The aim of this paper is to investigate how widely
machine translation systems are used and researched in the Arab world and what
can be done to achieve real progress in this field by taking one country as a case
study. A survey was carried out in Saudi Arabia to collect the necessary data to
assess how many Arabic machine translation systems are used by Saudi
organizations, how much interest exists in machine translation in Saudi
universities and research centres, and how much research is being conducted on
issues of machine translation. The findings of this study indicate that most Saudi
organizations and translation agencies do not trust or are not interested in machine
translation. Only a few universities have conducted research in this field. It is
recommended that more attention be paid and more research be conducted to get
the most use out of this technology and that more efficient Arabic machine
translation systems be developed.

3. Research Question

The research Attempts to answer the following:

How does the Scan Translator system impact the quality and the accuracy
of translation and interpretation?
 7

1. How Quality and Accuracy of Scan Translator in Translation and

interpretation?

2. Which of Scan Translator and Human translation is more reliable in

translation?

3.1. Hypotheses

It is hypothesized that:

1. Scan Translator is satisfactory in rendering Arabic English translation.

2. The outcomes of Scan Translator is less resource intensive

compered to human Translation.

3. Scan Translator outcomes between Arabic and English are often

said to be humorous.

3.2. Aims

This study sets four main aims:

1. To explain how Scan Translator functions.

2. To show how Scan Translator may assist humans in translation.

3. To prove that translation needs human assistance.

4. To identify the errors of the Scan Translator in the target text.

3.3. Objectives and subjective reasons

The emergence of technology such as Scan Translator has revolutionized cross-

linguistic communication in the ever-evolving world of technical innovation.
Scan Translator is a state-of-the-art application that combines objective
functionality with subjective user incentive to enable real-time translation of
printed text through scanning. This introduction explores the dual nature of Scan
Translator, looking at the subjective incentives that drive users to embrace and
 8

engage with this transforming tool in addition to its inherent goals as a

technological solution.

Objective Reasons:

1. Assurance of Quality: In order to confirm the dependability and credibility of

the translation tool, it is essential to look at how accurate Scan Translatoris while
translating and interpreting into Arabic. Finding any possible mistakes or
inconsistencies that might lower the quality of the translation is made easier with
the use of objective analysis.

2. User Satisfaction: It is crucial to comprehend SCAN Translator's accuracy

levels while translating and interpreting into Arabic in order to satisfy users and
meet their expectations. It is crucial to evaluate the tool's performance objectively
since users depend on correct translations to convey their messages or
comprehend foreign information.

3. Improvement Opportunities: Objective examination gives significant insights into

areas where Scan Translator could be improved. By detecting inconsistencies or
common translation problems, engineers may improve the tool's algorithms and
overall efficiency, resulting in improved translation results.

4. Ethical Considerations: Ensuring the correctness of Arabic translations is

critical to maintaining ethical communication standards. Misinterpretations or
mistranslations can cause misunderstandings, miscommunications, and even
cultural insensitivity, emphasizing the significance of objective evaluation in
mitigating such dangers.

5. Competitive Advantage: By objectively evaluating Scan Translator's accuracy in

translating and interpreting into Arabic, engineers may compare its performance to
 9

that of competitors. By proving higher accuracy and dependability, the tool can obtain
a competitive advantage in the market, attracting new users and stakeholders.

Subjective Reasons:

1. User Experience: Subjective evaluation of SCAN Translator's accuracy in

translating and interpreting into Arabic is based on the whole user experience,
which includes simplicity of use, fluency, and naturalness of translation. Users'
subjective perceptions have a significant impact on their pleasure and inclination
to continue using the product.

2. Cultural Sensitivity: Subjective evaluation takes into account the tool's ability
to effectively portray cultural subtleties and context-specific meanings in Arabic
translations. A subjective assessment considers the translator's awareness of
cultural nuance, colloquial idioms, and local customs, resulting in culturally
sensitive and contextually suitable translations.

3. Personalization: Subjective analysis investigates the extent to which Scan

Translator can accommodate individual preferences and linguistic styles in Arabic
translations. Users may have specific preferences for tone, style, and formality, and
subjective assessment helps establish the tool's adaptability to such variances.

4. Trustworthiness and reliability: Users' confidence in the validity of Scan

Translator is heavily influenced by their subjective impressions of trustworthiness
and reliability. Self-ratings take into account users' past experiences, word-of-
mouth recommendations, and brand reputation when determining their subjective
confidence in the tool's ability to consistently deliver correct translations

5. Emotional impact: Subjective assessment also considers translations' emotional

impact on users, such as clarity, resonance, and empathy. Translations that elicit
good emotions and connect with users on a human level are seen as more accurate
 10

and effective, resulting in increased user satisfaction and loyalty. In conclusion,

determining the correctness of translating and interpreting into Arabic using Scan
Translator necessitates a mix of objective analysis to measure technical
performance and subjective evaluation to judge user experience, cultural
sensitivity, trust, and emotional effect. Balancing objective and subjective
viewpoints give a thorough knowledge of the tool's success and guides continuing
improvement efforts.

4. Methodology

This research adopts interviews methods and it explores the role of artificial
intelligence (AI) in translation, specifically the Scan Translator. The research
aims to understand its impact on translation processes through in-depth
interviews and observations. The study uses a literature review to examine
existing research on AI in translation, focusing on its features, effectiveness, and
potential impact. Key research questions include how translators perceive AI's
role in their workflow, perceived benefits and limitations, and how AI
technology affects traditional translation processes and professional identity.
The study uses a planned sampling strategy and data collection methods, with
ethical considerations such as informed permission and participant anonymity.

This in-depth investigation examines how AI Scan Translator affects

translation procedures. Understanding the significance and impact of AI Scan
Translator on translation procedures is the study problem. Using a qualitative
technique, the study looks at the body of research on AI in translation and
pinpoints areas in need of further investigation. The research is guided by
theoretical frameworks like the Technology Acceptance Model and User
Experience Design. Important research topics include how translators view AI
 11

Scan Translator's place in their workflow, as well as the benefits and

drawbacks of the tool and how it affects translation conventions and
professional identities. Data analysis, observation, and semi-structured
interviews are all part of the research technique. A number of ethical issues are
covered, such as participant anonymity, informed permission, and
confidentiality.

5. Structure of the study

The study "Investigating Accuracy of Translating and Interpreting into Arabic of

Scan Translator" examines the impact of AI and Scan translation on translation
devices. It reviews existing literature, examines the role of AI and machine
translation applications, and outlines the tools used for evaluation, data collection,
and analysis. The study also evaluates the quality of scan translators and
translation pens, focusing on accuracy, speed, and user experience. The findings
include a comparison between AI-assisted and conventional translation tools,
quantitative evaluation of translation accuracy, determination of translation
quality, and identification of factors contributing to enhanced accuracy in
translating and interpreting into Arabic using scan translators.
This study is made of two parts; Theoretical and practical. The Theoretical part
is made of two chapters, the first is entitled Artificial Intelligence, and the seconds
is entitled Quality of (AI) scan Translator in translation & interpretation. The
practical part is made of one chapter in an attempt to analyse Scan Translator and
examples of it including research and introduction and conclusion. in addition,
appendix which hold a photo of the Scan translator and how it works and glossary.

6. Significance of the study

 12

The importance of this research lies in the study of translation machines, their
history, and their effective role in this era, all thanks to artificial intelligence and
its integration into the world of translation. This study focused on examining
translation tools in general and the Scan Translator in particular. An in-depth
study and complete analysis were conducted on how the Scan Translatorworks,
as well as the quality and effectiveness of translation within it. The study
addressed both the negative and positive aspects of its operation and its impact
on the life of the translator. The pen underwent testing, leading to several
conclusions, including the significant role played by artificial intelligence in the
translation processes. Thanks to algorithms related to this field, the pen
demonstrated greater effectiveness, challenging human speed and accuracy at
times. However, it is essential to acknowledge the limitations of the pen,
indicating that it cannot currently surpass human capabilities. This study serves
to enlighten researchers or learners about the hidden aspects of machine
translation tools and their potential effectiveness in the future. It also raises
important questions regarding reliance on these tools and the potential
displacement of human intellect within the translation world.

7. The Limitation of the Study

The study's limitations are apparent in several of aspects. First off, the results
have limited relevance because they can't be expanded to include additional
translation devices outside the one under study. Second, although surveys of the
literature on machine translation (MT) tools show certain commonalities, they
could not fully capture the subtle differences and distinctive characteristics of
each tool, which could restrict the scope of the research. Furthermore, the use of
different resources in AI research highlights the difficulties in verifying the
authenticity and coherence of ideas gathered and emphasizes the complexity of
synthesizing varied sources. Last but not least, a significant drawback is that the
 13

gadget under study does not support Arabic. This limits the scope of its features
and could make it less useful to consumers who need Arabic translation. These
restrictions highlight the necessity of exercising caution and interpreting the
study's results in light of the surrounding circumstances, acknowledging the
natural limitations of the research's scope.
 1

chapter one:
Theoretical Part
 Part one:
Artificial Intelligence
 14

Introduction
Modern artificial intelligence is a system capable of perceiving its environment
and taking actions to maximize the chance of successfully achieving its goals as
well as interpreting and analysing data in a way that learns and adapts over time.
this chapter discusses Artificial Intelligence. One of the Top Most Important
Topics in the IT sector right now is artificial intelligence. It is the mechanical
imitation of human intellect, particularly in computer systems. Additionally, it
is the capacity of a machine to think and learn similarly to a human. It is related
to many fields of study with the goal of creating methods and instruments for
problem solving that people can effectively handle. AI is also software that
thinks intelligently, in a way that is comparable to that of intelligent humans. it
is developed by researching how people think, learn, make decisions, and
collaborate to solve problems. AI has the potential to be extremely important in
a variety of industries, including healthcare, agriculture, robotics, e-commerce,
and transportation.

Translation in the past

Translation has been an important technique since ancient times, promoting

worldwide contact and understanding among people. The tale of Babel, in which
Noah's descendants were punished for building a tall structure, emphasizes the
necessity of translation in early civilizations. Hieroglyphic pharaoh
civilizations, Sumer, Mesopotamia, and the Arabs all used translation to
establish their presence. The Gilgamesh epic was the earliest translation in the
Middle East, including versions in Hittite and Hurrian. In Mesopotamia, the
Hammurabi code was written in Akkadian and Hurrian languages. Translation
was also employed to communicate in ancient Egypt, as evidenced by the
Rosetta Stone. Arabs also translated into Arabic, mostly for medicinal purposes,
 15

astrology, mathematics, physics, and science. Since ancient times, translation

has served as a tool for organization and progress. (Goui D. , 2023)

1-Translation and interpreting in Algeria:

Translation is the process of interpreting the meaning of a written word from

one language to another. Interpretation translates the meaning of a spoken
phrase from one language to another. Algeria, like most other countries, has
placed a high value on translation and interpretation since its independence for
a variety of reasons. Algeria received the French language from its colonizer
while also seeking to maintain its Arab character. For a while, French and Arabic
coexisted, and there was a high need for translation because most official papers
were written in both languages. The necessity to open up to the rest of the world
drove Algeria to absorb many other global languages, particularly English, and
the need for translation and interpretation expanded substantially as a result.
Algeria understood this and had to establish a translation and interpreting facility
in Algiers to satisfy demand. Over time, Algeria established translation
institutions and departments around the country. Algeria has also attempted to
control the translation and interpretation professions. Some interpreters are even
members of the judiciary in Algeria. (GOUI, 2019)

2-Difficulties in translation and interpreting:

Translation involves addressing various challenges such as word order, false

cognates, dialects, and idioms to avoid misunderstandings or mistranslations.
Immigration translation and interpreting encounter several challenges as a result
of Algeria's circumstances. In actuality, certain problems or challenges are
associated with lawful migration, whereas others are primarily associated with
irregular migration. Gender is one factor that is often associated to language
ability, but there are other concerns that are related to practice and migration
 16

(Djamel GOUI 2017). Successful communication between Algerians and

migrants—or, more often, between Algerian authorities and migrants—may be
hampered by these problems. The challenges covered in this work are
illustrative rather than complete, and there may be many more challenges that
have gone unmentioned since there is insufficient scientific data. (GOUI,
2019)(Opt Cite, p.98)

3-Objectives of Translation and the Death of the Truth:

Nations translate just to exist. It is unnecessary to go back to the beginning to
emphasize the importance of translation in permitting or facilitating contact
across nations. Translation has now been changed, as previously said in this
work, to non-classical functions, not restricted to the creation of knowledge and
power alone. Nations translate to stay current and, as a result, be able to remain
in today's globe, which is growing and changing too quickly and transforming
into a little room rather than a small hamlet In these circumstances, the goals of
translation varies from one translator to the next, as well as from one group,
community, or nation to another. Translation aims are often established in
advance, whether in literary translation or otherwise, and none of those purposes
intends from the start to achieve the death of the truth in the target text. (Goui,
2024)
3.1 Translate to Introduce the Other
Translators sometimes try to present another culture without neutralizing or
disguising indicators, which might produce culture shock in the receiver. They
leave unique components and indicators for the reader to uncover. This
technique does not destroy the truth inherent in the original. To establish
equivalency, it is crucial to determine whether literal translation is useful or
unimportant. Translating to introduce the other can assist offer the other the
opportunity to respond, particularly across cultures, civilizations, and faiths.
 17

However, literal translation may produce translationese and language

interference. (Goui, 2024)(Opt Cite, p.49)
3.2Translate To Influence the Other In this second objective,
The translator aims to provide the same impression as the source material. As a
result, the translator may choose for natural equivalence according to Anthony
Pym, in which he or she can modify the form while preserving the content and
carefully select a term that preserves the same impact and will be readily
understood by the receiver/reader. Thus, precise translation is avoided on
purpose, and formal truth telling is explored as well, as the viewer may perceive
the process as a sort of misrepresenting truths that leads to the death of truth.
Again, one may return to the very early disputes over form and content in
establishing equivalence, as articulated primarily by Eugine Nida (1964), J.C
Catford (1965), and many other translation studies major academics.(Goui,
2024)(Ibid, p.49)

4-Historical Development of Artificial Intelligence

The history of artificial intelligence (AI) is a fascinating journey spanning decade,
defined by key milestones, breakthroughs, setbacks, and renewed enthusiasm.
Here is a short summary: Artificial intelligence (AI) has made significant
advances in recent years, leading us into an era where machines can not only learn
but also make informed decisions. The integration of multiple factors promotes
the rapid development of artificial intelligence, starting a journey of
transformation in various industries, a concept originating from ancient
civilizations, gained formal recognition in the mid-20th century with Alan
Turing's "universal machine" concept. The Dartmouth Conference in 1956,
organized by computer scientists, marked the birth of AI research, focusing on
problem-solving, language processing, and symbolic reasoning. The 1950s and
1960s saw significant efforts to build intelligent systems, leading to the
 18

development of symbolic AI, which emulated human intelligence in specific

domains. (TEJAN, 2022)
5- Definition of Artificial Intelligence
Artificial intelligence, or AI, refers to how technology, specifically computer
systems, may replicate human intelligence processes. This includes perception,
learning, thinking, problem-solving, and decision-making. As a result, this study
presents an understandable introduction of artificial intelligence (AI),
emphasizing its capabilities, relevance, and problems. Artificial intelligence
refers to systems that demonstrate intelligent behaviour by analysing their
surroundings and acting autonomously to achieve certain goals. The phrase
"artificial intelligence" refers to any technology that is utilized in any situation
and possesses qualities that some people see as intelligent. This inclusivity
makes it difficult to estimate the impact of AI breakthroughs, since various
advantages and concerns may be recognized depending on the sector of AI.
Greater accuracy is required to have meaningful and productive discourse,
distinguishing between basic "expert systems" and complicated data-driven
algorithms. (Boucher, 2020)
6- Types of Artificial Intelligence:
Artificial intelligence can be categorized into many sorts based on its functions
and capabilities. These are a few common varieties. The science and engineering
of creating intelligent machines, particularly intelligent computer programs, is
known as artificial intelligence." Alan Turing In order to engage in the current
conversation around artificial intelligence and comprehend the implications it
will have for humanity's future; we must first familiarize ourselves with three
categories of foundational information.

6.1 Artificial Narrow Intelligence (ANI):

 19

AI systems that are created and educated for a single task or a limited set of tasks
are referred to as artificial narrow intelligence, or ANI. These systems lack the
general cognitive capacities of human intelligence, yet they are excellent at
completing predetermined tasks within a narrow domain. Narrow artificial
intelligence (ANI), also known as narrow artificial intelligence or weak artificial
intelligence, is a type of artificial intelligence that focuses on a single narrow task.
Her abilities are limited. Artificial intelligence systems used in medicine for
accurate disease diagnosis (Fourtané, 2019)
6-2Artificial General Intelligence (AGI):

Artificial General Intelligence (AGI) is a type of AI that is comparable to human

cognitive capacities in that it can comprehend, acquire, and apply information to
a variety of activities. As opposed to narrow it, which is intended for specialized
jobs, so when we talk about artificial general intelligence (AGI), we are referring
to an artificial intelligence that is comparable to human abilities. However, AGI
is still an emerging field. Since the human brain is the model for creating general
intelligence, it does not appear that this will happen anytime soon due to the lack
of a complete understanding of human brain function. But history often shows
that people tend to develop technologies that pose an existential danger to
humanity. Why would trying to create an algorithm that replicates brain function
be any different? If this happens, people will have to accept the consequences it
may bring. (Fourtané, 2019)(Opt Cite, p.49)

6-3 Artificial Super Intelligence (ASI):

To human A hypothetical intelligence known as Artificial Super Intelligence

(ASI) is said to be superior intelligence in all domains, including creativity,
problem-solving, and social abilities. Artificial Super intelligence (ASI) would
surpass human cognition and perhaps demonstrate talents well beyond human
comprehension, in contrast to Artificial General Intelligence (AGI), which would
 20

be able to comprehend and learn any intellectual work that a human being can.
And also, Artificial Super Intelligence (ASI) is predicted to outperform humans
in many areas, such as arts, decision-making, and emotional relationships. This
type of AI will excel in these areas, which are considered essential for
distinguishing a machine from a human. However, some argue that humans have
not yet mastered these areas. (Fourtané, 2019)(Ibid, p.49)
7-The main areas of research and development in AI?
The field of artificial intelligence research and development is diverse and active,
Artificial intelligence work is often organized into various subfields that solve
frequent, but difficult, practical problems or require unique tools or expertise.
Some of the most well-known subfields include robotics, computer vision, speech
recognition, and natural language processing (KAPLAN, 2016)
8. Definition of robotics?

Robotics is a multidisciplinary science that encompasses robot design,

construction, usage, and operations. A robot is a machine that can execute
complex tasks autonomously. These devices are typically designed by computers
to do hazardous, dull, filthy, or repetitive tasks that people find unpleasant or
tiresome. Robotics also include creating machines capable of doing physical
activities, which are frequently modeled after humans. AI research is centered on
creating lighter, more flexible, and stronger materials and control systems, as well
as creative designs inspired by nature. The main challenge is adjusting to
changing circumstances, with the goal of building autonomous cars that navigate
highways and places. (KAPLAN, 2016)(Opt Cite, p.49)
 21

9-Themes of Artificial Intelligence

Since Artificial intelligence (is multidisciplinary and has an impact on many
facets of society, it covers a broad variety of issues and topics. The following are
some well-known AI-related themes:AI has made significant advancements in
search algorithms, machine learning, and statistical analysis throughout the past
60 years. Most of these breakthroughs are inconspicuous, such as examining
purchase histories and influencing marketing decisions. Foundational problems
have often been underestimated by the field, with the promise of significant
breakthroughs in 10 years. Despite progress, no computer has passed the Turing
Test, Expert Systems have grown, and open-ended games remain far from
mastery. (Smith, 2006)
10. The AI Environment:
The ecosystem in which artificial intelligence functions, develops, and influences
many facets of society and human existence is referred to as the AI environment.
This ecosystem is made up of many different components, such as the economic
dynamics, ethical considerations, legal frameworks, technological infrastructure,
and public attitudes regarding it so the AI environment consists of five main
components: machines, human intelligence, machine learning (ML) algorithms,
IoT, the Internet of Everything, and data science and engineering. Machines are
critical in both non-AI and AI environments because they have the intelligence
to distinguish humans from animals and other humans. its developers use
machine learning algorithms to create intelligent coding that enables self-learning
and prediction of events based on data. These algorithms also help predict future
trends (Kaliraj, 2022)
 22

Translation in ESP Context

In the context of English for Specific Purposes (ESP), teachers use a combination
of methodologies, procedures, and materials to teach context-specific language.
Translation is a technique that helps learners understand the communicative value
of their language by referencing their own language's functioning. This approach
is not just about language usage, but also engages them in understanding real-life
communication functions. Scientific discourse is a universal mode of
communication realized by textualizing scientific texts in different languages.
Widdowson (1979) recommends that teachers use L1 and non-verbal methods to
manifest this process, as scientific discourse is a universal mode of
communication. This approach helps teachers engage in the learning process and
promotes a deeper understanding of the language. (Fethiza-T, 2016)

CLT in EST: Meaning and Prospects

Since its debut in the 1980s, communicative language teaching (CLT) has been
the most successful way to build English as a Foreign Language (EL) fluency in
EFL programs. CLT addresses typical concerns in EFL didactics, such as learners'
difficulty utilizing language outside of the classroom and the importance of a
communicative repertoire for effective EL communication. It also emphasizes EL
communicative competence (CC) as the ultimate objective of ELT, addressing
learners' requirements for developing English oral fluency. CLT has collaborated
with English as a Second Language (EST) to meet these communicative
opportunities, emphasizing English speaking abilities rather than EL linguistic
proficiency. This method incorporates EST practices, factual accuracy, and
interpretations into communicative teaching theory, assumptions, and
consequences. (GOUI.D, 2021)
 23

Conclusion
Artificial intelligence (AI) has revolutionized various sectors, increasing
productivity, efficiency, revenue, job roles, innovation, and reducing human
error. However, challenges such as layoffs, labour market disruptions, privacy
issues, and gender-based inequalities require attention. AI technologies must be
created ethically and address social issues. AI holds immense potential in
enhancing productivity, decision-making, and driving economic growth.
Consequently, with such power comes great responsibility. navigate ethical
dilemmas must uphold principles of fairness, transparency, and accountability,
and remain vigilant against unintended consequences like job displacement and
privacy breaches. Establishing robust regulatory frameworks and ethical
guidelines is crucial for AI systems' development and deployment. Fostering
interdisciplinary collaboration and promoting diversity within it is essential to
unlock its full potential and mitigate bias and discrimination risks. The future of
AI lies in our hands, and we must harness its power responsibly to build a more
equitable, sustainable, and prosperous world. The true measure of AI's success
lies in its ability to enrich and empower the lives of every individual on this
planet.
 Chapter Two:
Quality of (AI) scan Translator in
translation &interpretation
 21

Introduction

Translating using computers is beneficial for various reasons, including

handling large volumes of text, maintaining terminology consistency,
enhancing speed and volume, and reducing costs. Human translators may find
technical topics tedious and uninteresting, while machines can provide
consistent translations. They also cater to immediate delivery preferences,
making them ideal for businesses. While some may view computers as
ineffective, they can be used in situations where high-quality human translation
is not necessary. Translation has become a growing economic activity due to
globalization and multinational corporations. The development of the Internet
has led to a demand for product information, software, and manuals, prompting
translation services to be rendered on time.

Machine Translation (MT) has become more popular among professional

translators, and Machine Translation Post-Editing (MTPE) is becoming more
widely used. Assessing the quality of MT suggestions can prevent frustration
and reduce the time it takes for post-editors to decide if a suggestion is worth
post-editing. Machine Translation Quality Estimation (MTQE) can help
provide good-quality sentences for post-editing. Translation is crucial for
recognizing democratic potential and reducing inequalities associated with
ethnic, linguistic, gender, race, or class. Countries like Canada, Spain, Belgium,
Romania, and Yugoslavia promote free interlingual communication and statute
publication. The North-South gap requires developing countries to assert their
languages and determine their role. Issues like language barriers in Nigeria,
Malaysia, and India highlight the importance of translation in international
organizations like Amnesty International.
 22

Ideology

Ideology and ethnocentrism are closely connected yet have different viewpoints.
Ideology covers political, economic, religious, and cultural convictions, which
can result in disputes between states and groups. Translators frequently act
strategically to ameliorate the negative consequences of these issues on their
communities, nations, or organizations, using neutralization, omission, change,
or opposition. This method enables their society to present themselves as victors
and right-holders, while others are positioned as losers or non-right holders.
Ideology clarifies issues in translation, functioning as a soft weapon in the game.
Ideological attitudes in language or translation can arouse the message receiver's
emotions, resulting in reactions that could be deemed war-like soft signals or
even physical violence. Killing truth in translation is viewed as a sort of war
from both an impact and truth dying standpoint, as well as from the translator's
and translational perspectives. Is the translator obligated to murder the truth,
which is not part of their work, resulting in the death of the truth in translation
and transforming them into liars rather than effective mediators? In some
situations, the goals of translation may allow for the suppression of truth

1.Difficulties of translation into Arabic:

The intricacy of the Arabic language combined with cultural variations can make
translation into Arabic difficult in many ways. Arabic is rich in cultural allusions,
idioms, and context, making direct translation challenging. Creating new terms
or coining old ones in order to find an equivalent has long been a major challenge
in Arabic translation. The sciences and new knowledge in general were translated
into Arabic during this time, and many new concepts were introduced. Since there
were no coined terms to express these concepts with the same charge, translators
 23

had to use the closest term that already existed in Arabic or, more likely,
transliteration, which they state is only temporary used to produce a full
translation before the term is reviewed or changed by those in charge of term
generation and coinage. If translation is not closely watched, it could be a major
cause of lexicon turmoil in the Arab world. Language coordination offices must
be established and activated to greatly attend to the transliteral and translational
process, language, and ultimately the Arab Nation. On the one hand, translation
needs to be closely regulated by policies in order to reduce the risks associated
with its practice without coordination or organization. (Goui, 2023)

2.1 Nowadays translation into Arabic problems.

Translating into Arabic can indeed present some challenges, as with any language
translation. Here are a few common issues that translators may face Arabic is
viewed as a single, cohesive language, in contrast to other languages like English.
For example, there are several dialects of English, including American, British,
Australian, and others; in theory, this is not the case in Arabic. However, in
actuality, the Arabic phenomena is entirely present, The Arabic spoken
throughout the Maghreb and the Middle East, and occasionally even in
neighbouring nations, differs due to translation. The remarkably developed west
is a large and rich source of translations from French and other languages into
Arabic. In English. While Middle Eastern and Gulf countries translate primarily
from English, Maghreb countries translate primarily from French. This causes
some variations, if not divergences, in the terms, words, or expressions coined
between the east and west of the Arab world, and in these cases, translation—
which is meant to be a source of organization becomes a source of chaos. (Goui,
2023)(Opt Cite, p.49)

Definition of Machine Translation

 24

Machine translation is the use of artificial intelligence to automatically translate

text from one language to another without human involvement. Modern MT goes
beyond simple word-for-word translation, conveying the whole meaning of the
source text in the target language. Controlled language criticism systems may
significantly reduce the time required to post-edit machine translated documents,
as well as validate and revise input text. However, if the MT and critiquing
systems are totally separate, the same text must be reviewed twice: once by the
critiquing system and then by the MT system. This distinction raises the expense
of modifying or changing the regulated wording. As a result, MT system makers
should attempt to integrate controlled language critique with MT as closely as
possible. In reality, not all content fed into MT systems follows strict writing
criteria, and the less a text does, the worse the raw translation result. In some
cases, it may be possible to reword troublesome sentences or conduct the full
procedure manually. (Arnold, 1994)

7- Problems in machine Translation

MT can cause errors and omissions that affect the meaning and intelligibility of
your message, especially if the languages involved are complex or distant. MT
may also fail to understand the nuances, circumstances, and styles of human
discourse, resulting in incorrect or misleading translations.MT has improved
translation quality, but not all language pairs are equally effective.
Morphologically rich languages, such as highly inflected languages, are difficult
to translate due to data sparsity and incorrect statistical estimations. Technique’s
address this by modelling units like stems, ends, lemmas, and morphosyntactic
tags. Inflectional languages also face issues with relaxed word order and improper
pronoun translations. Pre-ordering techniques help address these issues by
bringing words closer to their final placements on the target side. (Donaj, 2019)

8- Machine translation evaluation

 25

There are two primary techniques to evaluating machine translation systems:

human evaluation and automated evaluation. Human review is a useful approach
to measure translation quality, but it is costly and takes significant human work,
in addition to the problem of locating dependable multilingual annotators.
Machine translation (MT) is a crucial technique in the translation field, and its
quality is increasingly important. Machine translation evaluation is an algorithm
that can be built into a program and performed by a computer to produce an
evaluation score. However, automatic MT evaluation often counts word- and
sentence-based faults, neglecting general text-level features. Despite criticisms,
progress in automatic MT evaluation has been made in the last decade. MT
quality can be measured using two approaches: Glass-box evaluation and black-
box evaluation. Black-box evaluation focuses on the objective behaviour of the
system on a predetermined evaluation set. (Donaj, 2019)(Opt Cite, p.49)

9- MT quality assessment
Translation quality assessment is crucial for improving MT systems, but there
is a lack of consensus and standardization due to the complex cognitive,
linguistic, social, cultural, and technical processes involved. Approaches can
range from macro-analytic to micro-analytic, depending on the context. Industry
quality assessment focuses on the final product, while research aims to
demonstrate improvements over previous studies or different translation
processes. Distinguishing between human and automated metrics is necessary.
(Tregueros, 2021)

10- Neural network machine translation

Neural machine translation (NMT) is a method of machine translation that use
an artificial neural network to predict the likelihood of a sequence of words,
usually modelling full sentences in a single integrated model. NMT outperforms
 26

statistical machine translation. (The latter essentially predicted the most likely
translation of words by using statistical probability instead of context.)
However, despite its capacity to take context into account, neural machine
translation is not impervious to errors. Artificial intelligence (AI) has
revolutionized machine translation by allowing translation robots to directly
face whole phrases like humans. Google's 2016 study showed a 60% reduction
in error rate and high quality of neural network translation technology. This
technology has replaced statistical machine translation as the core technology
for commercial online translation, with Google's system supporting over 100
languages. (Yutao, 2022)
11- The limitations of machine translation
Machine translation technologies often struggle to maintain consistency over
enormous amounts of material. They may translate comparable lines differently,
or employ a different style or tone throughout the piece. This might lead to a
disconnected and confused end product. The expansion of technology in machine
translation faces limitations, with human translation remaining subjective.
Current neural network machine translation technology falls under the category
of "poor artificial intelligence." The debate over the effectiveness of AI is
significant, with "strong AI" arguing that a string of binary numbers can represent
anything, while "weak AI" argues that the human mind is semantic and cannot be
programmed due to its fundamental nature. Current AI translations rely on
standardized texts, making them limited in applicability and creativity (Lin, 2023).
12- AI in interpreting
AI supports interpreters in several ways when it comes to data analysis. It can
assist in finding the employee who is most suited for a certain position. It could
also assist you in determining how to book interpreters on an as-needed basis.AI
and ML technologies have significantly impacted the interpretation market,
 27

enabling automated speech translation and computer-assisted interpreting tools.

Initially developed in the 1980s and 1990s, these devices aim to fully automate
the interpreting process in specific contexts, such as travel, humanitarian
missions, medical care, university lectures, and military situations where human
interpreters are unavailable. (Horváth, 2022)
13- Machine Translation Quality Estimation
The job of measuring the quality of machine-translated text in real time without
requiring reference translations is known as machine translation quality
estimation (MTQE), and it is crucial to the advancement of machine translation
(MT). Following two decades of development, QE has produced an abundance
of findings. This work uses the FMS as a quality indicator for machine
translation output, since editing effort and FMS are correlated. Without ever
having access to the accurate translation, the MTQE system is taught to
anticipate FMS. The MTQE technique was assessed for performance using the
Autodesk dataset, which was utilized for training (Béchara, 2021)

The importance of corrective feedback

Corrective feedback is a valuable technique for improving language learning
and writing skills, helping students create better results. Precise texts with
clear and well-organized concepts. Straub (1996) emphasizes the importance
of feedback and error correction in teaching, stating that "how we receive and
respond to student writing speaks loudest" (p. 26). According to Penaflorida
(2002), receiving criticism helps students understand their strengths and flaws,
allowing them to improve and become good writers (p. 346). Effective use of
this educational tool by teachers can help pupils acquire foreign languages.
(GOUI.D, 2023)
 28

Conclusion
This Study investigates the function of machine translation technologies in
translation and quality evaluation, focusing on philosophical questions and the
complexities of human language and language mediation. It employs a literature
review approach to investigate the history, technical concerns, and future of
human and machine translation. this study reveals that while there are limitations
in machine translation progress, a balanced interaction between people and
technology is predicted, with translators employing technology to discover truth
while keeping their own subjectivity. AI technology can help interpreters operate
more efficiently by reducing cognitive load and delivering services in remote
places or languages with few native interpreters. However, unexpected increases
in AI utilization and cloud-based internet platforms pose significant ethical
challenges, notably in terms of maintaining anonymity and trust in client-
interpreter interactions. These hazards must be addressed in order to maintain
ethical standards in the translating profession. Translators need such tools to give
assistance to our self and to gain extra time when it comes to deal with
interpretation and translation.
 Part two:
The Practical Part
Chapter three
 29

Introduction
Communicative Translation is a vital tool in bridging communication barriers
between different cultures and languages. It allows people from diverse
backgrounds to understand each other's thoughts, ideas, and emotions while
maintaining the integrity of the original message. In today's globalized world,
cross-cultural interactions have become increasingly common, making it
essential to overcome language barriers. Scan translation is an indispensable tool
for this purpose, as it converts written text from one language to another, enabling
effective communication and promoting cultural exchange.

Scan translation tools provide an efficient and accurate way to convert written
content, allowing individuals from diverse linguistic backgrounds to access
information. They also enable real-time communication through instant
translation services. Advancements in technology have made multilingual
chatbots and mobile apps that incorporate scan translation widely available,
further facilitating global language exchange.

Scan translation not only helps in overcoming language barriers but also plays a
significant role in facilitating cultural exchange. By providing access to literary
works, articles, and other written materials in different languages, it allows
individuals to gain insights into other cultures and preserves and promotes
cultural diversity. It also enables the exchange of ideas and perspectives through
translated books, research papers, and discussions, promoting a richer
understanding of different cultures. In an increasingly interconnected world,
global communication is vital for collaboration, business transactions, and
international relations. Scan translation enables smooth business negotiations by
translating contracts, proposals, and communication in real-time. Governments,
 30

organizations, and individuals can use scan translation to bridge communication

gaps during international conferences, events, and collaborations. By breaking
down language barriers, scan translation fosters mutual understanding and
harmony among diverse communities.

1. Vormor-x2 Translation Pen Scanner

This is a portable multi-functional translation dictionary pen that can be used to

scan translation, voice intercom translation and find words. Scanning translation
function can scan, translate and pronounce different languages; Voice translation
can be used for real-time voice intercom translation in different languages.

1. Hold the translation pen so that the head of the pen and the book are 60 °
Angle, the translation effect will be better.
2. Point the pen to the beginning of the text.
3. Press the pen gently.
4. Parallel backward sliding scanning at uniform speed.

14- Product Description

a. Power on / off Power on:

in the off state, long press the power key for about 3 seconds to start the device.
Power off: in the power on state, long press the power button for about 3
seconds, and “restart / shut down” will appear. Click the power off icon to shut
down the device.

b. Connect Wi-Fi

After power on, you can connect with Wi-Fi in the setting interface to get more
learning materials. You can also use this product offline.
 31

c. Scan translation

After power on, hold the translation pen, gently press the scanning pen to align
with the text, then scan and translate different languages, and click on a single
text to enhance understanding and learning.

d. Voice translation

Click the “Voice translation” in the main interface, set the two languages to be
translated at the top first, and then press and hold the blue (or red) button on the
right side to carry out voice intercom to the translation pen device to realize the
voice translation of the two selected languages. There are more than 100 kinds
of languages, which can be freely selected according to your needs.

e. Photo translation

(optional) 500W pixel photo taking function, one clicks photo, real-time
translation, adjustable translation area, automatic translation of different
languages, applicable to the translation of shopping labels, user manual, menu,
road signs, etc.

f. Text excerpt Click

“Text excerpt” in the main interface to scan the text content to be extracted. After
scanning, click “Finish” to save it to the machine and view it from the history; Or
click upload to email address, then download and save from email. You can extract
the text you need in real time.

g. Smart record Click

“Smart record” in the main interface, then click build record in the upper right
corner, chick the recording button to start recording. After recording, save the
recorded content in the device to make notes of important information.

Dictionary Click “Dictionary” in the main interface to select a dictionary for

quick word search and interpretation. There are several different dictionaries to
choose from.

h. Vocabulary Click “

Vocabulary” in the main interface, there are several kinds of thesaurus for
learning and using.
 32

Text to Speech - The scan translator can scan 3000 characters per minute, scan
and translate the entire line of text within one second, and output the original text
and the translated documents by voice. The accuracy rate is up to 98% which is
convenient and fast! Very suitable for people with dyslexia or other reading
difficulties.

i. 112 languages voice translator

Professional Document Scanner suitable for students and professionals. Supports

multinational accents and can adjust the speed of speech output. It is the best
choice for you to take notes, record conferences, travel abroad, take TOEFL,
IELTS, ESL test, and give as a gift.

j. Two-way Speech Translation–Scan and edit on the go!

Translations are instantly played via the built-in speaker and shown on the pen,
for example, translation from Spanish into English, or translated English into
Spanish

k. Smart Recording & File Transfer

Translator Voice Translator can be used as a convenient recorder to record and

save all your important interviews, meetings and conversations.

l. Reliable After-Sales Guarantee & Online Software Update–

This instant voice translation device uses a 3.5-inch touch screen and an eye-
protecting UI design. A more comfortable operating system, no additional
applications, no additional costs. The system is updated online for life and
includes two years of free replacement and warranty, as well as 24/7 customer
service.

m. Translation pen scanner with 3.5-inch Capacitive Touch

Screen Our dictionary scanner pen support 112 language
translations,

Translator’s voice translation accuracy rate is high, and it can easily meet your
multi-language translation needs
 33

15- Definition of the corpus

The Scan Translator has a massive reservoir of linguistic materials that have been
rigorously selected to facilitate cross-lingual translation and interpretation. This
enormous collection includes a complex tapestry of written texts and spoken
dialogues drawn from a variety of linguistic landscapes, guaranteeing full
coverage across several language pairings and disciplines. This corpus contains
the building blocks of language, such as subtle idioms, idiomatic phrases, and
cultural allusions, which improve the translation experience and deepen cross-
cultural understanding.

As the foundation of the Scan Translator system, this corpus is constantly refined
and expanded to keep up with the dynamic nature of language evolution and
cultural shifts. Linguistic patterns, word use, and contextual subtleties are
thoroughly examined and incorporated to provide the highest accuracy and
fidelity in translation outputs. The Scan Translator adapts effortlessly to evolving
language trends and cultural sensitivities via continual updates and modifications,
increasing its efficacy and dependability over time.

By using the communal wisdom inherent in this vast corpus, the Scan Translator
system shines as a beacon of language skill and cultural competence. It provides
users with high-quality translations that not only transmit the text's literal
meaning but also retain the nuances, complexities, and cultural context of the
original conversation. Whether analysing complicated legal papers, interacting
with literary masterpieces, or facilitating cross-border contact, the Scan
Translator system is a reliable ally, overcoming linguistic gaps and building
meaningful relationships across cultures and languages.
 34

16- Patterns
The Scan Translatoris a portable device that uses advanced language translation
technology and a pen-like instrument to convert printed text into digital data using
optical character recognition (OCR) technology. It can be audible through audio
output or displayed on a screen. Some models also have voice recognition built in
for quick translations. However, the translator has limitations due to handwriting
styles, typefaces, and text, and may struggle with complex words or idiomatic
expressions. Advances in artificial intelligence and machine learning are being
made to improve the accuracy and comprehension of the Scan translator. Future
improvements may include improved handwriting recognition, language
compatibility, and contextual comprehension. Based on the in-depth analysis in the
pen, an applied and practical study was conducted using different texts as follows:
The translation and degradation process of the scan translator were examined,
and the following observations were made:

Example:1

-There were several suggestions ،more or less happy but, challengers were
final.

Translation

‫ﻛﺎﻧﺖ ھﻨﺎك ﻋﺪت اﻗﺘﺮاﺣﺎت ﺳﻌﯿﺪة إﻟﻰ ﺣﺪ ﻣﺎ ﻟﻜﻦ اﻗﺘﺮاح ﺗﺸﺎﻟﻨﺠﺮ ﻛﺎن ﻧﮭﺎﺋﯿﺎ‬

The analysis:

Noticed that the word "challengers" has been mistranslated from its Arabic
equivalent (Challengers), but noticed that the pen translated it as(‫)ﺗﺸﺎﻟﻨﺠﺮ‬

Identifying the mistake

 35

observed that when translating by voice, the word in Arabic was translated
, however, when using scanning, the word translated as Challenger, (‫)ﺗﺸﺎﻟﻨﺠﺮ‬as
which is one of the mistakes committed by the Scan Translator.

Figures. 1

Example:2

We therefore blocked the entrance to our zareba by filling it up with several

thorny bushes

Translation:

.‫ﻟﺬﻟﻚ ﻗﻤﻨﺎ ﺑﺴﺪ ﻣﺪﺧﻞ اﻟﺰرﯾﺒﺔ ﻟﺪﯾﻨﺎ ﻋﻦ طﺮﯾﻖ ﻣﻠﺌﮭﺎ ﺑﻌﺪة ﺷﺠﯿﺮات ﺷﺎﺋﻜﺔ‬

The analysis:

You can see that the translation in this sentence is correct and uses the
borrowing technique

(Borrowing) ‫( ﻓﻲ ﻛﻠﻤﺔ‬zareba)(‫)زرﯾﺒﺔ‬

Meaning of zareba in English: A stockade or enclosure of thorn bushes

Identifying the mistake

 36

noted that the Scan Translator works with the word (zareba) as a term that does
not exist in the original text (English language) and its equivalent in the English
culture, so it treats the

word in a borrowing style (from one culture to another).

Figures. 2

Example:3

The most wonderful things have happened and are continually happening to us.
all the paper that I possess consist of five old not-books and a lot of scraps.

Translation:

‫ ﻛﻞ اﻷوراق اﻟﺘﻲ أﻣﻠﻜﮭﺎ ﺗﺘﻜﻮن ﻣﻦ ﺧﻤﺴﺔ دﻓﺎﺗﺮ‬.‫ﻟﻘﺪ ﺣﺪﺛﺖ اﻷﺷﯿﺎء اﻟﺮاﺋﻌﺔ وﺗﺤﺪث ﻟﻨﺎ ﺑﺎﺳﺘﻤﺮار‬
‫وﻣﻼﺣﻈﺎت ﻗﺪﯾﻤﺔ واﻟﻜﺜﯿﺮ ﻣﻦ اﻟﻔﻀﻼت‬

Identifying the mistake:

The word scraps as a singular are translated as scraps, but when the word is
translated into a paragraph, the translation is different and translated as rubbish.
 37

In other words, the pen translates according to the context) from one word,
sentence and paragraph.

Figures. 3

17- Observations:
Noticed that the translation process from one foreign language to another
translates effectively. However, from Arabic to another language, the pen fails to
translate in both voice and scanning translations.

1. For instance: The Scan Translator cannot translate religious texts (the
Quran) in Arabic
2. The pen has difficulty when it comes to translating from the target language
(Arabic) to the source language (English), while the reverse is easier.
 38

3. When using voice translation, the pen is good at finding the correct
translation of common vocabulary

Example:

- hello everyone

‫ﻣﺮﺣﺒﺎ ﺟﻤﯿﻌﺎ‬

On the other hand, when it comes to an unfamiliar word that is unable:

- In the word stylographic pencil is a is a printing pen, the Scan translator

faced Difficulties of finding the correct concept and the correct translation
into ‫ﻗﻠﻢ رﺻﺎص‬
- The scan translator or Scan Translator can only read and translate from
written contexts (books, articles, papers.). in the other hand, cannot deal
with digital screens
- Such as (laptops, mobiles…)

Example:

This pilgrimage, known as the Hajj, is one of the five Pillars of Islam (the others
are the profession of Allah as the only God and Mohammed as his Prophet;
Fasting during Ramadan charitable giving and ritual prayer) by which every
practicing Muslim must abide. this year the hajjStarts Nov. 25it takes place on
only between the 8thand12th days of Dhu-al-Hijjah, the final month of the lunar
Islamic calendar, a Time One God's spirit is believed to be closest to earth.

Translation:

‫ھﺬا اﻟﺤﺞ اﻟﻤﻌﺮوف ﺑﺎﻟﺤﺞ ھﻮ أﺣﺪ أرﻛﺎن اﻹﺳﻼم اﻟﺨﻤﺴﺔ )ھﻲ إﻗﺮار ﷲ ﺑﺄﻧﮫ اﻹﻟﮫ اﻟﻮﺣﯿﺪ وﻣﺤﻤﺪ ورﺳﻮﻟﮫ‬
‫وﺻﯿﺎم ﺷﮭﺮ رﻣﻀﺎن واﻟﺰﻛﺎة واﻟﺼﻼة( اﻟﺘﻲ ﯾﺠﺐ ﻋﻠﻰ ﻛﻞ ﻣﺴﻠﻢ اﻟﻤﻠﺘﺰم أن ﯾﻠﺘﺰم ﺑﮭﺎ ھﺬا اﻟﻌﺎم ﯾﺒﺪأ اﻟﺤﺞ‬
 39

‫ﻧﻮﻓﻤﺒﺮ وﯾﻘﺎم ﺳﻨﻮﯾﺎ ﺑﯿﻦ اﻟﺜﺎﻣﻦ واﻟﺜﺎﻧﻲ ﻋﺸﺮ ﻣﻦ ذي اﻟﺤﺠﺔ اﻟﺸﮭﺮ اﻷﺧﯿﺮ ﻓﻲ‬/ ‫ ﺗﺸﺮﯾﻦ اﻟﺜﺎﻧﻲ‬25 ‫ﻓﻲ‬
.‫اﻟﺘﻘﻮﯾﻢ اﻹﺳﻼﻣﻲ اﻟﻘﻤﺮي وھﻮ اﻟﻮﻗﺖ اﻟﺬي ﯾﻌﺘﻘﺪ ان روح ﷲ ﻓﯿﮫ ھﻮ اﻷﻗﺮب إﻟﻰ اﻷرض‬

Analysis

- In the translation of the above paragraph, it is observed that the accuracy

of the device in recognizing translation styles was not high enough to
prevent the occurrence of poor translations as in the following:
- The device leaves the same word pilgrimage and Hajj, which have the
same meaning (pilgrimage), as the translation does not carry two words
with the same meaning consecutively. In this case, it is necessary to use
the method of deletion for the integrity of the translation deleting one of
the two words (ellipsis /omission)
- You cannot rely on the Scan Translator to translate texts related to religion,
hadiths, etc. as in the following example:
- the profession of Allah as the only God translated to ((‫)إﻗﺮار ﷲ ﺑﺎﻧﮫ اﻹﻟﮫ اﻟﻮﺣﯿﺪ‬
- Correct translation is (‫)ان ﺗﺸﮭﺪ ﺑﺎن ﷲ اﻟﻮاﺣﺪ‬

18- Findings:
Human translators have a deep understanding of source and target languages,
allowing them to accurately convey meaning and context. They can decipher
complex sentence structures, idiomatic expressions, and cultural nuances that
machine translation systems struggle to understand. Despite neural machine
translation, it is difficult to match the accuracy achieved by human translators.
Human translators also capture subtlety, such as sarcasm, irony, and cultural
allusions, which machine translation cannot reproduce. Translation involves
understanding cultural context, and human translators can modify wording to be
appropriate for the intended context. Machine translation lacks the cultural
 40

knowledge and sensitivity required for correct translations, and relying solely on
it reduces the complexity and richness of communication.

Conclusion
Technology for language translation stands out as a vital tool for removing
linguistic and cultural obstacles in successful communication. Scan Translator
technology has advanced significantly over time, having a dramatic effect on the
dynamics of cross-cultural communication and enriching cultural landscapes by
providing more access to textual materials in a variety of language domains. A
transformative era in language acquisition and comprehension has begun with the
introduction of cutting-edge devices with a plethora of features, including
extensive word repositories, seamless scanning functionalities, and advanced
speech and photo translation capabilities.
Among the novel tools supplied, the Scan Translator stands out as a critical tool,
alongside the language translator, electronic dictionary pen, and scan reader pen,
all specifically designed to improve the language acquisition trip. Consider the
Scan Translator, a stunning display of technical genius. It has a full suite of seven
dynamic features, including the exceptional potential for multilingual voice
translation in 113 languages, exact scanning translation, quick access to
electronic dictionaries, and seamless online or offline image translation. This set
of elements not only simplifies language learning efforts, but also considerably
improves their efficacy. Similarly, the Vormor X2 pen scanner is a revolutionary
combination of technology and language learning, capable of reading 3,000
characters per minute in less than a second. This extraordinary power, along with
its exceptional text-to-speech and translation characteristics, improves both
language learning and translation processes, resulting in unprecedented
efficiency and accuracy. Furthermore, as natural language processing and
artificial intelligence advance, the area of translation systems increases, bringing
 41

solutions that not only supplement but greatly increase the productivity of human
translators.
As technology advances, the importance of Scan Translator technology in the
translation industry grows, empowering skilled translators and enabling seamless
cross-cultural communication on a global scale, fostering harmony and mutual
understanding among diverse communities
Conclusion
 42

The use of AI in translation has transformed linguistic communication by

increasing accuracy, speed, and accessibility. AI-powered translation solutions
provide more precise translations and continual development over time by
leveraging advanced machine learning algorithms and large multilingual datasets.
In a continuously changing digital landscape, quicker translation speeds allow for
real-time communication and promote globalization. Furthermore, the
accessibility given by AI translation services reduces language barriers, allowing
individuals and organizations to interact and collaborate across languages and
cultures. As AI advances, the future of translation has enormous potential for
further enhancing the power of linguistic communication So Scan translator
technology has transformed communication by giving real-time translations of
printed text. Its benefits include immediate translation, portability, and the
preservation of layout and formatting. However, restrictions like language
complexity, accuracy, and reliance on internet connectivity remain. Despite these
limitations, recent improvements and future prospects hold considerable promise
for the further development and improvement of scan translator technology. By
overcoming these obstacles, scan translator technology has the ability to break
down language borders, enhance global understanding, and enable seamless
communication in an increasingly interconnected world.
Although scan translators play an important role in overcoming linguistic divides,
their accuracy and cultural sensitivity face obstacles. As technology advances, it
is critical to address these difficulties and aim for development in order to
maximize the benefits of scan translator in promoting cross-cultural
communication, However One of the most significant contributions of AI to
translation is its capacity to improve accuracy, Traditional translation
technologies frequently rely on manual input, which can lead to human errors.
However, AI-powered translation systems use advanced algorithms and machine
 43

learning techniques to improve accuracy. These systems can analyse large

volumes of language data, resulting in more accurate translations. For example,
neural machine translation (NMT) employs deep learning approaches to
understand the context and nuances of language, resulting in improved accuracy
in translating complicated sentences and idiomatic idioms. Furthermore, AI
systems may learn from user comments and continuously improve their
translation abilities, Furthermore The accuracy of translations is one of the most
important aspects in determining the quality of a scan translator while translating
and interpreting, despite advances in machine learning and natural language
processing algorithms, scan translators may face difficulties when dealing with
complex linguistic constructions, idiomatic idioms, and cultural references. For
example, idiomatic idioms frequently have figurative connotations that do not
directly transfer into other languages. Inaccurate translations can cause confusion
or misconceptions among the persons concerned. To offer dependable and
relevant translations, scan translators must demonstrate a high level of
accuracy,to save cost, effort, and time, we can decrease the advantages of scan
translation. scan translation enables us to translate the text immediately, which
we often need to understand content quickly. Viewed from a broader perspective,
it can be used in projects where time is the most important factor, because the
speed with which automated translation gives us enables us to understand a
particular document in another language in minutes and perhaps just seconds.
Even though a professional translator will surely provide you with a higher
quality, there are times when machine translation is sufficient for what we need
to translate, which can save us time.
‫ﻣﻠﺨﺺ اﻟﺪراﺳﺔ‬
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‫أدى اﺳﺘﺨﺪام اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� �� اﻟ��ﺟﻤﺔ إ�� �ﻐﻴ�� اﻻﺗﺼﺎل اﻟﻠﻐﻮي ﻣﻦ ﺧﻼل ز�ﺎدة اﻟﺪﻗﺔ واﻟﺴﺮﻋﺔ و�ﻣ�ﺎﻧﻴﺔ اﻟﻮﺻﻮل‪.‬‬
‫ً‬
‫ﻣﺴﺘﻤﺮا ﺑﻤﺮور اﻟﻮﻗﺖ ﻣﻦ ﺧﻼل اﻻﺳﺘﻔﺎدة‬ ‫ً‬
‫وﺗﻄﻮ�ﺮا‬ ‫ﺗﻮﻓﺮ ﺣﻠﻮل اﻟ��ﺟﻤﺔ اﻟ�ي �ﻌﻤﻞ ﺑﺎﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� ﺗﺮﺟﻤﺎت أﻛ�� دﻗﺔ‬

‫ﻣﻦ ﺧﻮارزﻣﻴﺎت اﻟﺘﻌﻠﻢ اﻵ�� اﳌﺘﻘﺪﻣﺔ وﻣﺠﻤﻮﻋﺎت اﻟﺒﻴﺎﻧﺎت اﻟﻜﺒ��ة ﻣﺘﻌﺪدة اﻟﻠﻐﺎت‪ �� .‬اﳌﺸهﺪ اﻟﺮﻗ�ي اﳌﺘﻐ�� ﺑﺎﺳﺘﻤﺮار‪،‬‬

‫�ﺴﻤﺢ ﺳﺮﻋﺎت اﻟ��ﺟﻤﺔ اﻷﺳﺮع ﺑﺎﻻﺗﺼﺎل �� اﻟﻮﻗﺖ اﻟﻔﻌ�� و�ﻌﺰ�ﺰ اﻟﻌﻮﳌﺔ‪ .‬ﻋﻼوة ﻋ�� ذﻟﻚ‪ ،‬ﻓﺈن إﻣ�ﺎﻧﻴﺔ اﻟﻮﺻﻮل اﻟ�ي‬

‫ﺗﻮﻓﺮهﺎ ﺧﺪﻣﺎت اﻟ��ﺟﻤﺔ اﻟﺘﺤﺮ�ﺮ�ﺔ ﻟﻠﺬ�ﺎء اﻻﺻﻄﻨﺎ�� ﺗﻘﻠﻞ ﻣﻦ ا�حﻮاﺟﺰ اﻟﻠﻐﻮ�ﺔ‪ ،‬ﻣﻤﺎ �ﺴﻤﺢ ﻟﻸﻓﺮاد واﳌﻨﻈﻤﺎت ﺑﺎﻟﺘﻔﺎﻋﻞ‬

‫واﻟﺘﻌﺎون ﻋ�� اﻟﻠﻐﺎت واﻟﺜﻘﺎﻓﺎت‪ .‬ﻣﻊ ﺗﻘﺪم اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ��‪ ،‬ﻳﺘﻤﺘﻊ ﻣﺴﺘﻘﺒﻞ اﻟ��ﺟﻤﺔ ﺑﺈﻣ�ﺎﻧﺎت هﺎﺋﻠﺔ ﻟﺰ�ﺎدة �ﻌﺰ�ﺰ ﻗﻮة‬

‫اﻻﺗﺼﺎل اﻟﻠﻐﻮي‪.‬‬

‫ﻏ��ت ﺗﻘﻨﻴﺔ ﻣ��ﺟﻢ اﳌ�ح اﻻﺗﺼﺎل ﻣﻦ ﺧﻼل إﻋﻄﺎء ﺗﺮﺟﻤﺎت �� اﻟﻮﻗﺖ اﻟﻔﻌ�� ﻟﻠﻨﺺ اﳌﻄﺒﻮع‪� .‬ﺸﻤﻞ ﻓﻮاﺋﺪﻩ اﻟ��ﺟﻤﺔ‬

‫اﻟﻔﻮر�ﺔ و�ﻣ�ﺎﻧﻴﺔ اﻟﻨﻘﻞ وا�حﻔﺎظ ﻋ�� اﻟﺘﺨﻄﻴﻂ واﻟﺘنﺴﻴﻖ‪ .‬وﻣﻊ ذﻟﻚ‪ ،‬ﻻ ﺗﺰال هﻨﺎك ﻗﻴﻮد ﻣﺜﻞ �ﻌﻘﻴﺪ اﻟﻠﻐﺔ واﻟﺪﻗﺔ‬

‫واﻻﻋﺘﻤﺎد ﻋ�� اﻻﺗﺼﺎل ﺑﺎﻹﻧ��ﻧﺖ‪ .‬ﻋ�� اﻟﺮﻏﻢ ﻣﻦ هﺬﻩ اﻟﻘﻴﻮد‪ ،‬ﻓﺈن اﻟﺘﺤﺴيﻨﺎت اﻷﺧ��ة واﻵﻓﺎق اﳌﺴﺘﻘﺒﻠﻴﺔ ﺗبﺸﺮ ﺑﻘﺪر ﻛﺒ��‬

‫ﺑﻤﻮاﺻﻠﺔ ﺗﻄﻮ�ﺮ وﺗﺤﺴ�ن ﺗﻜﻨﻮﻟﻮﺟﻴﺎ ﺳ�ﺎن ﺗﺮاﻧﺰﻟﻴ��‪ .‬ﻣﻦ ﺧﻼل اﻟﺘﻐﻠﺐ ﻋ�� هﺬﻩ اﻟﻌﻘﺒﺎت‪ ،‬ﻓﺈن ﺗﻘﻨﻴﺔ ﺳ�ﺎن ﺗﺮاﻧﺰﻟﻴ�� ﻟﺪ��ﺎ‬

‫اﻟﻘﺪرة ﻋ�� ﻛﺴﺮ ﺣﺪود اﻟﻠﻐﺔ‪ ،‬و�ﻌﺰ�ﺰ اﻟﻔهﻢ اﻟﻌﺎﳌﻲ‪ ،‬وﺗﻤﻜ�ن اﻟﺘﻮاﺻﻞ اﻟﺴﻠﺲ �� ﻋﺎﻟﻢ ﻣ��اﺑﻂ �ﺸ�ﻞ ﻣ��اﻳﺪ‪.‬‬
‫ﻋ�� اﻟﺮﻏﻢ ﻣﻦ أن ﻣ��ﺟ�ي اﻟﻔﺤﺺ ﻳﻠﻌﺒﻮن ً‬
‫دورا ً‬
‫ﻣهﻤﺎ �� اﻟﺘﻐﻠﺐ ﻋ�� اﻻﻧﻘﺴﺎﻣﺎت اﻟﻠﻐﻮ�ﺔ‪ ،‬إﻻ أن دﻗ��ﺎ وﺣﺴﺎﺳﻴ��ﺎ اﻟﺜﻘﺎﻓﻴﺔ‬

‫ﺗﻮاﺟﮫ ﻋﻘﺒﺎت‪ .‬ﻣﻊ ﺗﻘﺪم اﻟﺘﻜﻨﻮﻟﻮﺟﻴﺎ‪ ،‬ﻣﻦ اﻷهﻤﻴﺔ ﺑﻤ�ﺎن ﻣﻌﺎ�جﺔ هﺬﻩ اﻟﺼﻌﻮ�ﺎت واﻟﺴ�� إ�� اﻟﺘﻨﻤﻴﺔ ﻣﻦ أﺟﻞ �ﻌﻈﻴﻢ‬

‫ﻓﻮاﺋﺪ ﻣ��ﺟﻢ اﻟﻔﺤﺺ �� �ﻌﺰ�ﺰ اﻟﺘﻮاﺻﻞ ﺑ�ن اﻟﺜﻘﺎﻓﺎت ‪.‬ﻣﻦ أهﻢ ﻣﺴﺎهﻤﺎت اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� �� اﻟ��ﺟﻤﺔ ﻗﺪر��ﺎ ﻋ��‬
‫ﺗﺤﺴ�ن اﻟﺪﻗﺔ‪ً .‬‬
‫ﻏﺎﻟﺒﺎ ﻣﺎ �ﻌﺘﻤﺪ ﺗﻘﻨﻴﺎت اﻟ��ﺟﻤﺔ اﻟﺘﻘﻠﻴﺪﻳﺔ ﻋ�� اﳌﺪﺧﻼت اﻟﻴﺪو�ﺔ‪ ،‬ﻣﻤﺎ ﻗﺪ ﻳﺆدي إ�� أﺧﻄﺎء �ﺸﺮ�ﺔ‪ .‬وﻣﻊ ذﻟﻚ‪،‬‬

‫�ﺴﺘﺨﺪم أﻧﻈﻤﺔ اﻟ��ﺟﻤﺔ اﻟ�ي �ﻌﻤﻞ ﺑﺎﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� ﺧﻮارزﻣﻴﺎت ﻣﺘﻘﺪﻣﺔ وﺗﻘﻨﻴﺎت اﻟﺘﻌﻠﻢ اﻵ�� ﻟﺘﺤﺴ�ن اﻟﺪﻗﺔ‪ .‬ﻳﻤﻜﻦ‬

‫ﻟهﺬﻩ اﻷﻧﻈﻤﺔ ﺗﺤﻠﻴﻞ ﻛﻤﻴﺎت ﻛﺒ��ة ﻣﻦ ﺑﻴﺎﻧﺎت اﻟﻠﻐﺔ‪ ،‬ﻣﻤﺎ ﻳﺆدي إ�� ﺗﺮﺟﻤﺎت أﻛ�� دﻗﺔ‪ .‬ﻋ�� ﺳبﻴﻞ اﳌﺜﺎل‪� ،‬ﺴﺘﺨﺪم اﻟ��ﺟﻤﺔ‬

‫اﻵﻟﻴﺔ اﻟﻌﺼبﻴﺔ )‪ (NMT‬أﺳﺎﻟﻴﺐ اﻟﺘﻌﻠﻢ اﻟﻌﻤﻴﻖ ﻟﻔهﻢ ﺳﻴﺎق اﻟﻠﻐﺔ وﻓﺮوﻗهﺎ اﻟﺪﻗﻴﻘﺔ‪ ،‬ﻣﻤﺎ ﻳﺆدي إ�� ﺗﺤﺴ�ن اﻟﺪﻗﺔ �� ﺗﺮﺟﻤﺔ‬

‫ا�جﻤﻞ اﳌﻌﻘﺪة واﳌﺼﻄ�حﺎت اﻻﺻﻄﻼﺣﻴﺔ‪ .‬ﻋﻼوة ﻋ�� ذﻟﻚ‪ ،‬ﻗﺪ ﺗﺘﻌﻠﻢ أﻧﻈﻤﺔ اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� ﻣﻦ �ﻌﻠﻴﻘﺎت اﳌﺴﺘﺨﺪم‬

‫وﺗﺤﺴﻦ ﺑﺎﺳﺘﻤﺮار ﻗﺪرا��ﺎ ﻋ�� اﻟ��ﺟﻤﺔ‪.‬‬

‫�ﻌﺪ دﻗﺔ اﻟ��ﺟﻤﺎت أﺣﺪ أهﻢ ا�جﻮاﻧﺐ �� ﺗﺤﺪﻳﺪ ﺟﻮدة ﻣ��ﺟﻢ اﻟﻔﺤﺺ أﺛﻨﺎء اﻟ��ﺟﻤﺔ واﻟ��ﺟﻤﺔ اﻟﺸﻔﻮ�ﺔ‪ .‬ﻋ�� اﻟﺮﻏﻢ ﻣﻦ‬

‫اﻟﺘﻘﺪم �� اﻟﺘﻌﻠﻢ اﻵ�� وﺧﻮارزﻣﻴﺎت ﻣﻌﺎ�جﺔ اﻟﻠﻐﺔ اﻟﻄﺒﻴﻌﻴﺔ‪ ،‬ﻗﺪ ﻳﻮاﺟﮫ ﻣ��ﺟﻤﻮ اﻟﻔﺤﺺ ﺻﻌﻮ�ﺎت ﻋﻨﺪ اﻟﺘﻌﺎﻣﻞ ﻣﻊ‬
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‫اﻹ�ﺸﺎءات اﻟﻠﻐﻮ�ﺔ اﳌﻌﻘﺪة‪ ،‬واﳌﺼﻄ�حﺎت اﻻﺻﻄﻼﺣﻴﺔ‪ ،‬واﳌﺮاﺟﻊ اﻟﺜﻘﺎﻓﻴﺔ‪ .‬ﻋ�� ﺳبﻴﻞ اﳌﺜﺎل‪ً ،‬‬
‫ﻏﺎﻟﺒﺎ ﻣﺎ ﺗﺤﺘﻮي اﳌﺼﻄ�حﺎت‬

‫اﻻﺻﻄﻼﺣﻴﺔ ﻋ�� دﻻﻻت ﻣﺠﺎز�ﺔ ﻻ ﺗنﺘﻘﻞ ﻣﺒﺎﺷﺮة إ�� ﻟﻐﺎت أﺧﺮى‪ .‬و�ﻤﻜﻦ ﻟﻠ��ﺟﻤﺎت ﻏ�� اﻟﺪﻗﻴﻘﺔ أن �ﺴبﺐ ارﺗﺒﺎ�ﺎ أو‬

‫ﺗﺼﻮرات ﺧﺎﻃﺌﺔ ﻟﺪى اﻷ�خﺎص اﳌﻌﻨﻴ�ن‪ .‬ﻟﺘﻘﺪﻳﻢ ﺗﺮﺟﻤﺎت ﻳﻤﻜﻦ اﻻﻋﺘﻤﺎد ﻋﻠ��ﺎ وذات ﺻﻠﺔ‪ ،‬ﻳﺠﺐ ﻋ�� ﻣ��ﺟ�ي اﻟﻔﺤﺺ‬

‫إﻇهﺎر ﻣﺴﺘﻮى ٍ‬
‫ﻋﺎل ﻣﻦ اﻟﺪﻗﺔ‪.‬‬

‫هﻨﺎك ﻋﺎﻣﻞ رﺋي�ىي آﺧﺮ ﻳﺆﺛﺮ ﻋ�� ﺟﻮدة ﻣ��ﺟ�ي اﻟﻔﺤﺺ �� اﻟ��ﺟﻤﺔ اﻟﺘﺤﺮ�ﺮ�ﺔ واﻟ��ﺟﻤﺔ اﻟﺸﻔﻮ�ﺔ وهﻮ إﺗﻘﺎن اﳌ��ﺟﻢ ﻟﻠﻐﺔ‪.‬‬

‫�ﺴﺘﺨﺪم ﻣ��ﺟﻤﻮ اﳌ�ح ا�خﻮارزﻣﻴﺎت اﳌﻌﻘﺪة ﳌﻌﺎ�جﺔ اﻟ��ﺟﻤﺎت و�ﺴﻠﻴﻤهﺎ‪ .‬وﻣﻊ ذﻟﻚ‪ ،‬ﻓﺈن هﺬﻩ ا�خﻮارزﻣﻴﺎت ﻓﻌﺎﻟﺔ ﻓﻘﻂ‬

‫ﻣﺜﻞ اﻟﺒﻴﺎﻧﺎت اﻟ�ي ﺗﺘﻠﻘﺎهﺎ‪ .‬ﻗﺪ ﻳﻮاﺟﮫ ﻣ��ﺟﻢ اﻟﻔﺤﺺ ﺻﻌﻮ�ﺔ �� ﺗﺮﺟﻤﺔ اﻟﻨﺺ ﺑﺪﻗﺔ إذا �ﺎﻧﺖ ﻣﻌﻠﻮﻣﺎت اﳌﺼﺪر ﻣﻜﺘﻮ�ﺔ‬

‫�ﺸ�ﻞ ﺳيئ أو ﺗﺤﺘﻮي ﻋ�� ﻣﺸﺎ�ﻞ ﻧﺤﻮ�ﺔ‪ .‬اﻟﻜﻔﺎءة اﻟﻠﻐﻮ�ﺔ ﻣﻄﻠﻮ�ﺔ ﻟﻠﻤ��ﺟﻢ ﻟﻔهﻢ �ﻌﻘﻴﺪات اﻟﻨﺺ اﳌﺼﺪر و�ﻧﺘﺎج ﺗﺮﺟﻤﺎت‬

‫وا�حﺔ ودﻗﻴﻘﺔ‪ .‬ﻋﻼوة ﻋ�� ذﻟﻚ‪ ،‬ﻓﺈن اﳌ��ﺟﻢ ا�جﻴﺪ ﻟﺪﻳﮫ إﺗﻘﺎن ﻗﻮي ﻟ�ﻞ ﻣﻦ اﳌﺼﺪر واﻟﻠﻐﺎت اﳌﺴ��ﺪﻓﺔ‪ ،‬ﻣﻤﺎ �ﺴﻤﺢ ﻟﮫ‬

‫ﺑﺎﺧﺘﻴﺎر اﻟ��ﺟﻤﺎت اﳌﻨﺎﺳﺒﺔ �� ﺳﻴﺎﻗﺎت ﻣﺨﺘﻠﻔﺔ‪.‬‬

‫واﻟﻔهﻢ اﻟﺜﻘﺎ�� ﻋﻨﺼﺮ أﺳﺎ��ي �� اﻟ��ﺟﻤﺔ اﻟﺘﺤﺮ�ﺮ�ﺔ واﻟ��ﺟﻤﺔ اﻟﺸﻔﻮ�ﺔ‪ .‬ﻳﺠﺐ أﻻ ﻳ�ﻮن اﳌ��ﺟﻤﻮن ﻣﺆهﻠ�ن ﻓﻘﻂ ﺑﺎﻟﻠﻐﺎت‬
‫اﻟ�ي �ﻌﻤﻠﻮن ��ﺎ‪ ،‬وﻟﻜﻦ ً‬
‫أﻳﻀﺎ ﻟﺪ��ﻢ و�� ﺷﺎﻣﻞ ﺑﺎﻟﺘﻔﺎﺻﻴﻞ اﻟﺜﻘﺎﻓﻴﺔ اﻟﺪﻗﻴﻘﺔ اﳌﺮﺗﺒﻄﺔ ﺑ�ﻞ ﻣ��ﺎ‪ .‬ﺑﺪون ا�خ��ة اﻟﺜﻘﺎﻓﻴﺔ‪ ،‬ﻗﺪ‬

‫��ىيء اﳌ��ﺟﻤﻮن ﻗﺮاءة أو ﺗﺤﺮ�ﻒ اﳌﻌ�ى اﳌﻘﺼﻮد ﻣﻦ اﻟﻮﺛﻴﻘﺔ اﳌﺼﺪر‪ .‬ﻋ�� ﺳبﻴﻞ اﳌﺜﺎل‪ ،‬ﻗﺪ ﻳ�ﻮن ﻟﺒﻌﺾ اﻟ�ﻠﻤﺎت أو‬

‫اﻟﻌﺒﺎرات دﻻﻻت أو آﺛﺎر ﻣﺨﺘﻠﻔﺔ �� اﻟﺜﻘﺎﻓﺎت ا�خﺘﻠﻔﺔ‪ .‬ﻗﺪ ﻳﻀﻤﻦ ﻣ��ﺟﻢ اﻟﻔﺤﺺ اﻟﺬي ﻳﺪﻣﺞ ا�حﺴﺎﺳﻴﺔ واﻟﻔهﻢ اﻟﺜﻘﺎﻓﻴ�ن‬

‫ﺗﺮﺟﻤﺎت دﻗﻴﻘﺔ وذات ﺻﻠﺔ ﺛﻘﺎﻓﻴﺔ‪ ،‬و�ﺎﻟﺘﺎ�� ﺗﺤﺴ�ن ا�جﻮدة اﻟﻌﺎﻣﺔ ﻟ�خﺪﻣﺔ‪.‬‬

‫ُ‬
‫اﻟ��ﺟﻤﺔ �� ﻧﻘﻞ اﻟﻜﻼم أو اﻟﻨﺺ ﻣﻦ ﻟﻐﺘﮫ اﻷﺻﻠﻴﺔ اﻟ�ي ﻛﺘﺐ ��ﺎ إ�� ﻟﻐﺔ أﺧﺮى ﻣﻊ اﻻﻟ��ام ﺑﻨﻘﻞ اﻟ�ﻠﻤﺎت ﺑﻄﺮ�ﻘﺔ �حﻴﺤﺔ‬

‫ﻟﺘتﺸﺎﺑﮫ ﻣﻊ ﻣﻌﺎﻧ��ﺎ اﻷﺻﻠﻴﺔ ﺣ�ى ﻻ ﻳﺆدي إ�� �ﻐﻴ�� �� ﻣﻌ�ى اﻟﻨﺺ اﻷﺻ��‪ ،‬ﺗﺮﺟﻊ أﺻﻞ �ﻠﻤﺔ اﻟ��ﺟﻤﺔ إ�� اﻟﻠﻐﺔ اﻟﻼﺗﻴنﻴﺔ و�ﻌ�ي‬

‫ﻧﻘﻞ‪ ،‬أﻣﺎ اﳌ��ﺟﻢ هﻮ اﻟ�خﺺ أو ا�جهﺎز اﻟﺬي ﻳﻘﻮم ﺑﻨﻘﻞ اﻟﻜﻼم أو اﻟﻨﺺ ﻣﻦ اﻟﻠﻐﺔ اﻷﺻﻠﻴﺔ إ�� ﻟﻐﺔ أﺧﺮى‪ ،‬ﻓ�ﻞ �خﺺ‬
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‫ﻟﮫ أﺳﻠﻮ�ﮫ ا�خﺎص �� اﻟ��ﺟﻤﺔ و�ﺠﺐ أن ﻳبﺘﻌﺪ اﳌ��ﺟﻢ ﻋﻦ اﻟ��ﺟﻤﺔ ا�حﺮﻓﻴﺔ ﻷﻧﮫ ﺳﻴﺆدي ﺑﮫ إ�� اﻟﻔﺸﻞ �� ﺻﻴﺎﻏﺔ اﻟﻨﺺ‪.‬‬

‫ﻓﻴﺪﻳﻮ ﻗﺪ ��جﺒﻚ‪ :‬ﺗﺎر�ﺦ اﻟ��ﺟﻤﺔ أول ﺣﻀﺎرة ﻋﺮﻓﺖ اﻟ��ﺟﻤﺔ �� ﺣﻀﺎرة ﻣﺎ ﺑ�ن اﻟ��ﺮ�ﻦ‪� ،‬ﺎن ﻋﺒﺎرة ﻋﻦ ﻣ�جﻢ ﻣﻜﺘﻮب ﻓﻴﮫ‬

‫ﻣﺠﻤﻮﻋﺔ �ﻠﻤﺎت وﺗﻘﺎﺑﻠهﺎ ﻣﻌﺎﻧ��ﺎ‪ ،‬وازدهﺮت اﻟﻜﺘﺎﺑﺔ �ﻌﺪ ذﻟﻚ �� ﺑﻼد اﻟﺮاﻓﺪﻳﻦ وﻣﺼﺮ اﻟﻘﺪﻳﻤﺔ‪ ،‬أﻣﺎ اﻟﻌﺮب و�ﻌﺪ اﻧتﺸﺎر‬

‫اﻟﺪوﻟﺔ اﻹﺳﻼﻣﻴﺔ واﺧﺘﻼﻃهﻢ ﺑﺄﻣﻢ وﺷﻌﻮب ﻣﺨﺘﻠﻔﺔ �ﺎﻟﺮوم واﻟﻔﺮس‪ ،‬ﻇهﺮت ﺣﺎﺟ��ﻢ ﻟﻌﻠﻮﻣهﻢ ﻣﻤﺎ أدى ��ﻢ إ�� ﺗﺮﺟﻤﺔ اﻟﻜﺘﺐ‬

‫واﳌﺆﻟﻔﺎت‪ ،‬وﻣﻊ ﻇهﻮر اﻟﺪوﻟﺔ اﻷﻣﻮ�ﺔ ﻇهﺮت ﻋﻤﻠﻴﺎت اﻟﺘﻌﺮ�ﺐ وازدهﺮت �ﻌﺪ ذﻟﻚ �� زﻣﻦ اﻟﺪوﻟﺔ اﻟﻌﺒﺎﺳﻴﺔ‪ ،‬وﺗﻄﻮرت اﻟ��ﺟﻤﺔ‬
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‫ﻓﺄﺻﺒﺤﻮا ﻳ��ﺟﻤﻮن ا�جﻤﻞ ﺑﺪل اﻟ�ﻠﻤﺎت‪ ،‬وازدادت ﺣﺎﺟﺔ اﻟﻌﺮب ﻟﻠ��ﺟﻤﺔ ﻟﻠ��ﻮض ﺑﺎﻟﺪول وﺗﺤﻘﻴﻖ اﻟﺘﻘﺪم ا�حﻀﺎري �ﻌﺪ‬

‫ﻣﺎ وﺟﺪ اﻟﺘﻘﺪم اﻟﻌﻠ�ي واﻟﺘﻜﻨﻮﻟﻮ�� �� اﻟﺪول اﻟﻐﺮ�ﻴﺔ ﻋ�� ﻏﺮار اﻟﺪول اﻟﻌﺮ�ﻴﺔ‪ ،‬ﻓﻘﺎﻣﻮا ﺑﺈرﺳﺎل �ﻌﺜﺎت ﻟﻠﺪول اﻟﻐﺮ�ﻴﺔ‬

‫وﺗﺄﺳيﺲ ﻣﺪرﺳﺔ ﻟﻠﻐﺎت ﻟ�حﺎق ﺑﺎﻟﺘﻄﻮر واﻟﺘﻘﺪم اﻟﺬي ﺣﻘﻘﺘﮫ اﻟﺪول اﻟﻐﺮ�ﻴﺔ‪ .‬وهﻨﺎك ﻋﺪة أﻧﻮاع ﻟﻠ��ﺟﻤﺔ أهﻤهﺎ‪ :‬اﻟ��ﺟﻤﺔ‬

‫اﻟﺘﺤﺮ�ﺮ�ﺔ ﺗﻨﻘﺴﻢ اﻟ��ﺟﻤﺔ اﻟﺘﺤﺮ�ﺮ�ﺔ إ�� ﻋﺪة أﺷ�ﺎل ﻣ��ﺎ‪ :‬ﺗﺮﺟﻤﺔ اﻟﻨﺺ ﺑﺎﻟﻠﻐﺔ ﻧﻔﺴهﺎ‪� :‬ﻌ�ي ﺑﺎﻟ��ﺟﻤﺔ هﻨﺎ إﻋﺎدة ﺻﻴﺎﻏﺔ‬

‫ﻟﻠﻨﺺ ﺑﻨﻔﺲ ﻟﻐﺔ اﻟﻨﺺ اﻷﺻ��‪ .‬ﺗﺮﺟﻤﺔ اﻟﻨﺺ ﺑﻠﻐﺎت أﺧﺮى‪� :‬ﻌ�ي ﺗﺮﺟﻤﺔ اﻟﻨﺺ ﻣﻦ اﻟﻠﻐﺔ اﻷﺻﻠﻴﺔ إ�� ﻋﺪة ﻟﻐﺎت أﺧﺮى‪.‬‬

‫ﺗﺮﺟﻤﺔ اﻹﺷﺎرة‪� :‬ﻌ�ي ﺗﺮﺟﻤﺔ اﻹﺷﺎرة اﻟﻠﻔﻈﻴﺔ إ�� إﺷﺎرة ﻏ�� ﻟﻔﻈﻴﺔ �ﺎﳌﻮﺳﻴﻘﻰ واﻟﺼﻮر‪ .‬اﻟ��ﺟﻤﺔ اﻟﻔﻮر�ﺔ ﺗﻨﻘﺴﻢ إ�� ﻋﺪة‬

‫أﺷ�ﺎل ﻣ��ﺎ‪ :‬اﻟ��ﺟﻤﺔ اﻟﻔﻮر�ﺔ اﳌ��اﻣﻨﺔ‪� :‬ﻌ�ي اﻟ��ﺟﻤﺔ اﻟﻜﻼﻣﻴﺔ اﻟ�ي ﺗﺘﻢ �� ﻧﻔﺲ اﻟﻮﻗﺖ اﻟ�ي ﻳﺼﺪر ﻓ��ﺎ اﻟﻨﺺ اﻷﺻ�� و���ﺟﻢ‬

‫ﺑﻠﻐﺔ أﺧﺮى ﻋ�� اﻟﻔﻮر‪ ،‬ﻳ�ﻮن اﳌ��ﺟﻢ ﻣﻮﺟﻮد ﺑﻨﻔﺲ اﻟﻮﻗﺖ اﻟﺬي ﻳﺘﺤﺪث ﻓﻴﮫ ﺻﺎﺣﺐ اﻟﻨﺺ اﻷﺻ�� وﻟﻜﻦ �� ﻣ�ﺎن ﻣﺨﺘﻠﻒ‬

‫ﻋﻦ ﻣ�ﺎن اﳌﺘﺤﺪث‪ ،‬وﺗﺤﺘﺎج هﺬﻩ اﻟ��ﺟﻤﺔ إ�� ﺗﺮﻛ�� ﺷﺪﻳﺪ ﻟﻌﺪم ﺗﻮﻓﺮ اﻟﻨﺺ اﻷﺻ�� ﻣﻊ اﳌ��ﺟﻢ‪ .‬اﻟ��ﺟﻤﺔ اﻟﺘﺘﺎ�ﻌﻴﺔ‪ :‬ﻳﻘﺼﺪ‬

‫��ﺬا اﻟﻨﻮع ﻣﻦ اﻟ��ﺟﻤﺔ أن ﻳنﺘﻈﺮ اﳌ��ﺟﻢ اﻧ��ﺎء اﳌﺘﺤﺪث ﻣﻦ ﻛﻼﻣﮫ ﻣﻦ ﺛﻢ ﻳﺒﺪأ هﻮ ﺑﺎﻟ��ﺟﻤﺔ‪ ،‬وهﺬا اﻟﻨﻮع ﻣﻦ اﻟ��ﺟﻤﺔ �ﺴﻤﺢ‬

‫ﻟﻠﻤ��ﺟﻢ ﺑﻔهﻢ اﻟﻨﺺ واﻟﻔﻜﺮة ﻣﻨﮫ ﻟﻴﺘﻢ ﺗﺮﺟﻤﺘﮫ �ﺸ�ﻞ دﻗﻴﻖ‪ ،‬ﻋﻜﺲ اﻟ��ﺟﻤﺔ اﻟﻔﻮر�ﺔ و��ﻮن اﳌ��ﺟﻢ ﻣﻊ اﳌﺘﺤﺪث ﺑﻨﻔﺲ‬

‫اﳌ�ﺎن‪ ،‬ﺗﺤﺘﺎج هﺬﻩ اﻟ��ﺟﻤﺔ إ�� ذاﻛﺮة ﻗﻮ�ﺔ ﻟﺘﺬﻛﺮ ﻣﺎ ﺗﻢ ﻗﻮﻟﮫ ﻣﻦ ﻗﺒﻞ اﳌﺘﺤﺪث ﻟﻴﺘﻢ ﺗﺮﺟﻤﺘﮫ إ�� اﻟﻨﺎس �ﺸ�ﻞ ﻣﺒﺎﺷﺮ‪.‬‬

‫اﻟ��ﺟﻤﺔ ﺑﺎﻟﻨﻈﺮ‪� :‬ﻌ�ي أن ﻳﻘﺮأ اﳌ��ﺟﻢ اﻟﻨﺺ اﻷﺻ�� �ﻌﻴنﻴﮫ و���ﺟﻤهﺎ �� ﻋﻘﻠﮫ ﺛﻢ ﻳ��ﺟﻤهﺎ ﻟﻠﻐﺔ اﳌﺮاد ﻧﻘﻠﮫ ��ﺎ ﺑﺎﻟﻜﻼم‪ ،‬ﻛ��ﺟﻤﺔ‬

‫اﻟﻮﺛﺎﺋﻖ واﳌﺴتﻨﺪات‪ .‬اﻟ��ﺟﻤﺔ اﻹﻋﻼﻣﻴﺔ‪ :‬ﺗﺘﻢ هﺬﻩ اﻟ��ﺟﻤﺔ �� اﻟ��اﻣﺞ اﻟﺘﻠﻔﺰ�ﻮﻧﻴﺔ واﻷﻓﻼم اﻟﻮﺛﺎﺋﻘﻴﺔ‪ .‬اﻟ��ﺟﻤﺔ اﻟﻘﺎﻧﻮﻧﻴﺔ‪ :‬ﺗﺘﻢ‬

‫هﺬﻩ اﻟ��ﺟﻤﺔ �� ا�حﺎﻛﻢ وﻟﻠﻘﻀﺎﻳﺎ اﻟﻘﺎﻧﻮﻧﻴﺔ ا�خﺘﻠﻔﺔ‬

‫ً‬
‫ﺗﻠﻘﺎﺋﻴﺎ ﻣﻦ ﻟﻐﺔ إ�� أﺧﺮى‬ ‫وأﻳﻀﺎ ﻟﺪﻳﻨﺎ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ﻋﺒﺎرة ﻋﻦ ﻋﻤﻠﻴﺔ اﺳﺘﺨﺪام اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� �� ﺗﺮﺟﻤﺔ اﻟﻨﺼﻮص‬
‫ﺑﺪون أي ﺗﺪﺧﻞ �ﺸﺮي‪ .‬ﺗﺘﺠﺎوز اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ا�حﺪﻳﺜﺔ �� ﻃﺮ�ﻘﺔ ﻋﻤﻠهﺎ اﻟ��ﺟﻤﺔ ا�حﺮﻓﻴﺔ اﻟبﺴﻴﻄﺔ‪ ،‬ﻓ�ي ّ‬
‫ﺗﻘﺪم ً‬
‫ﻧﺼﺎ ﺑﺎﻟﻠﻐﺔ‬
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‫اﻟهﺪف ﻳﺤﻤﻞ ﻣﻌ�ى ﻧﺺ اﻟﻠﻐﺔ اﻷﺻﻠﻴﺔ ﺑ�ﺎﻣﻠﮫ‪ .‬ﻛﻤﺎ ﺗﺤﻠﻞ ﺟﻤﻴﻊ ﻋﻨﺎﺻﺮ اﻟﻨﺺ وﺗﺪرك ﺗﺄﺛ�� �ﻞ �ﻠﻤﺔ ﻓﻴﮫ ﻋ�� ﻏ��هﺎ وﻣﻦ‬

‫ﻣﺰاﻳﺎ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ‪� .‬ﺴﺘﺨﺪم اﳌ��ﺟﻤﻮن ﺧﺪﻣﺎت اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ��ﺪف اﻟ��ﺟﻤﺔ �ﺴﺮﻋﺔ وﻛﻔﺎءة أﻛ��‪ .‬ﺗﻮﻓﺮ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ‬
‫ﻧﻤﻮذﺟﺎ ً‬
‫واﺣﺪا أو أﻛ�� ﻣﻦ ﻧﻤﺎذج‬ ‫ً‬ ‫ﻧﻘﻄﺔ اﻧﻄﻼق ﺟﻴﺪة ﻟﻠﻤ��ﺟﻤ�ن اﻟبﺸﺮ��ن ا�ح��ﻓ�ن‪ .‬ﻓﺘﺪﻣﺞ أﻧﻈﻤﺔ ﻣﺘﻌﺪدة ﻹدارة اﻟ��ﺟﻤﺔ‬
‫ً‬
‫ﺗﻠﻘﺎﺋﻴﺎ‪ ،‬ﺛﻢ إرﺳﺎﻟهﺎ إ�� اﳌ��ﺟﻤ�ن اﻟبﺸﺮ��ن ﻟﻠﺘﺤﺮ�ﺮ اﻟﻼﺣﻖ‪.‬‬ ‫اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ �� ﺳ�� ﻋﻤﻠهﺎ‪ .‬ﻟﺪ��ﺎ ً‬
‫أﻳﻀﺎ إﻋﺪادات ﳌﻞء اﻟ��ﺟﻤﺎت‬
‫و�ﻌﻤﻞ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ �ﺴﺮﻋﺔ ﻛﺒ��ة‪ ،‬ﻓ�ي ﻗﺎدرة ﻋ�� ﺗﺮﺟﻤﺔ ﻣﻼﻳ�ن اﻟ�ﻠﻤﺎت ﻋ�� اﻟﻔﻮر ً‬
‫ﺗﻘﺮ�ﺒﺎ‪ .‬ﻳﻤﻜﻦ ﻟهﺬﻩ اﻟﺘﻘﻨﻴﺔ ﺗﺮﺟﻤﺔ‬
‫ﻛﻤﻴﺎت ﻛﺒ��ة ﻣﻦ اﻟﺒﻴﺎﻧﺎت‪ ،‬ﻣﺜﻞ اﻟﺪردﺷﺔ �� اﻟﻮﻗﺖ اﻟﻔﻌ�� أو اﻟﻘﻀﺎﻳﺎ اﻟﻘﺎﻧﻮﻧﻴﺔ واﺳﻌﺔ اﻟﻨﻄﺎق‪ .‬ﻳﻤﻜ��ﺎ أ ً‬
‫ﻳﻀﺎ ﻣﻌﺎ�جﺔ‬
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‫اﳌﺴتﻨﺪات ﺑﻠﻐﺔ أﺟﻨبﻴﺔ‪ ،‬واﻟﺒﺤﺚ ﻋﻦ اﳌﺼﻄ�حﺎت اﳌﻨﺎﺳﺒﺔ‪ ،‬وﺗﺬﻛﺮ هﺬﻩ اﳌﺼﻄ�حﺎت ﻻﺳﺘﺨﺪاﻣهﺎ �� اﳌﺴﺘﻘﺒﻞ‪ .‬و�تﻴﺢ‬
‫اﻟﻌﺪﻳﺪ ﻣﻦ ﻣﺰودي ﺧﺪﻣﺔ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ اﻟﺮﺋيﺴﻴ�ن ﻣﺎ ﻳ��اوح ﺑ�ن ‪ 50‬وأﻛ�� ﻣﻦ ‪ 100‬ﻟﻐﺔ‪ .‬ﺗﺼﺪر اﻟ��ﺟﻤﺎت اﻵﻟﻴﺔ ً‬
‫أﻳﻀﺎ ��‬
‫اﻟﻮﻗﺖ ﻧﻔﺴﮫ ﻟﻠﻐﺎت ﻣﺘﻌﺪدة‪ ،‬وهﺬﻩ ﻣ��ة ﻣﻔﻴﺪة ﻋﻨﺪ ﻃﺮح اﳌﻨﺘﺠﺎت واﻟن�خ ّ‬
‫ا�حﺪﺛﺔ ﻣﻦ اﻟﻮﺛﺎﺋﻖ ً‬
‫ﻋﺎﳌﻴﺎ‪ .‬وﺗﺰ�ﺪ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ‬

‫ﻣﻦ اﻹﻧﺘﺎﺟﻴﺔ واﻟﻘﺪرة ﻋ�� ﺗﻘﺪﻳﻢ اﻟ��ﺟﻤﺎت �ﺴﺮﻋﺔ أﻛ��‪ ،‬ﻣﺎ ﻳﻘﻠﻞ ﻣﻦ اﻟﻮﻗﺖ اﻟﻼزم ﻟﻄﺮﺣهﺎ �� اﻟﺴﻮق‪ .‬هﻨﺎك ﻣﺸﺎرﻛﺔ �ﺸﺮ�ﺔ‬
‫أﻗﻞ �� اﻟﻌﻤﻠﻴﺔ ﺑﺤﻴﺚ ﺗﻮﻓﺮ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ﺗﺮﺟﻤﺎت أوﻟﻴﺔ وﻟﻜ��ﺎ ّ‬
‫ﻗﻴﻤﺔ‪ ،‬ﻣﺎ ﻳﻘﻠﻞ ﻣﻦ اﻟﺘ�ﻠﻔﺔ ووﻗﺖ اﻟتﺴﻠﻴﻢ‪ .‬ﻋ�� ﺳبﻴﻞ‬

‫اﳌﺜﺎل‪ �� ،‬اﳌﺸﺎريﻊ ﻛﺒ��ة ا�حجﻢ‪ ،‬ﻳﻤﻜﻨﻚ دﻣﺞ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ﻣﻊ أﻧﻈﻤﺔ إدارة ا�حﺘﻮى ﻟﺪﻳﻚ ﻟﻮﺿﻊ ﻋﻼﻣﺔ ﻋ�� ا�حﺘﻮى‬
‫ً‬
‫ﺗﻠﻘﺎﺋﻴﺎ ﻗﺒﻞ ﺗﺮﺟﻤﺘﮫ إ�� ﻟﻐﺎت ﻣﺨﺘﻠﻔﺔ‪.‬‬ ‫وﺗﻨﻈﻴﻤﮫ‬

‫ﻇهﺮت ﻓﻜﺮة اﺳﺘﺨﺪام أﺟهﺰة اﻟﻜﻤﺒﻴﻮﺗﺮ ﻟ��ﺟﻤﺔ اﻟﻠﻐﺎت اﻟبﺸﺮ�ﺔ ً‬

‫آﻟﻴﺎ ﻷول ﻣﺮة �� أواﺋﻞ ا�خﻤﺴﻴنﻴﺎت ﻣﻦ اﻟﻘﺮن اﳌﺎ��ي‪ .‬وﻣﻊ‬

‫ذﻟﻚ‪ �� ،‬ذﻟﻚ اﻟﻮﻗﺖ‪� ،‬ﺎﻧﺖ درﺟﺔ �ﻌﻘﻴﺪ اﻟ��ﺟﻤﺔ أﻛ�� ﺑﻜﺜ�� ﻣﻤﺎ اﻋﺘﻘﺪﻩ ﻋﻠﻤﺎء ا�حﺎﺳﻮب �� اﻟﺒﺪاﻳﺔ‪ .‬ﻓﻘﺪ ﺗﻄﻠﺒﺖ اﻟﻌﻤﻠﻴﺔ‬

‫ﻗﺪرة هﺎﺋﻠﺔ ﻋ�� ﻣﻌﺎ�جﺔ اﻟﺒﻴﺎﻧﺎت وﺗﺨﺰ���ﺎ‪ ،‬وهﻮ ﻣﺎ �ﺎن ﻳﻔﻮق ﻗﺪرات اﻷﺟهﺰة اﻟﻘﺪﻳﻤﺔ و�� أواﺋﻞ اﻟﻌﻘﺪ اﻷول ﻣﻦ اﻟﻘﺮن‬

‫ا�حﺎدي واﻟﻌﺸﺮ�ﻦ‪ ،‬أﺻﺒﺤﺖ ﺑﺮاﻣﺞ اﻟﻜﻤﺒﻴﻮﺗﺮ واﻟﺒﻴﺎﻧﺎت واﻷﺟهﺰة ﻗﺎدرة ﻋ�� ﺗﻮﻓ�� ﺗﺮﺟﻤﺔ آﻟﻴﺔ ّأوﻟﻴﺔ‪ .‬و�جﺄ اﳌﻄﻮرون اﻷواﺋﻞ‬

‫إ�� ﻗﻮاﻋﺪ اﻟﺒﻴﺎﻧﺎت اﻹﺣﺼﺎﺋﻴﺔ ا�خﺎﺻﺔ ﺑﺎﻟﻠﻐﺎت ﻣﻦ أﺟﻞ ﺗﺪر�ﺐ أﺟهﺰة اﻟﻜﻤﺒﻴﻮﺗﺮ ﻋ�� ﺗﺮﺟﻤﺔ اﻟﻨﺺ‪ .‬اﻧﻄﻮت هﺬﻩ اﻟﻌﻤﻠﻴﺔ‬
‫ً‬ ‫ﻋ�� اﻟﻜﺜ�� ﻣﻦ اﻟﻌﻤﻞ اﻟﻴﺪوي واﺳﺘﻐﺮﻗﺖ ً‬
‫وﻗﺘﺎ ﻃﻮ�ﻼ‪ .‬و�ﻠﻤﺎ ﻗﺮروا إﺿﺎﻓﺔ ﻟﻐﺔ ﺟﺪﻳﺪة‪� ،‬ﺎن ﻋﻠ��ﻢ اﻟﺒﺪء �� ﺗﻄﻮ�ﺮهﺎ ﻣﻦ‬

‫ﺟﺪﻳﺪ‪ .‬ﻣﻨﺬ ذﻟﻚ ا�ح�ن‪ ،‬ﺗﻄﻮرت ﺳﺮﻋﺔ إﻧﺠﺎز اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ وﻣﺪى دﻗ��ﺎ‪ ،‬وﻇهﺮت اﻟﻌﺪﻳﺪ ﻣﻦ اﺳ��اﺗﻴﺠﻴﺎت اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ‬
‫ا�خﺘﻠﻔﺔ‪ �� .‬اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ‪ُ ،‬ﻳﻄﻠﻖ ﻋ�� اﻟﻨﺺ اﻷﺻ�� أو اﻟﻠﻐﺔ اﻷﺻﻠﻴﺔ اﺳﻢ ﻟﻐﺔ اﳌﺼﺪر‪ُ ،‬و� ّ‬
‫ﺴ�ى اﻟﻠﻐﺔ اﻟ�ي ﺗﺮ�ﺪ اﻟ��ﺟﻤﺔ‬

‫إﻟ��ﺎ اﻟﻠﻐﺔ اﻟهﺪف‪� .‬ﻌﻤﻞ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ﺑﺈﺗﺒﺎع ﻋﻤﻠﻴﺔ أﺳﺎﺳﻴﺔ ﻣﺆﻟﻔﺔ ﻣﻦ ﺧﻄﻮﺗ�ن‪:‬‬

‫ﻓﻚ ﺷﻔﺮة ﻣﻌ�ى اﻟﻠﻐﺔ اﳌﺼﺪر �� اﻟﻨﺺ اﻷﺻ�� و�ﺸﻔ�� اﳌﻌ�ى ﺑﺎﻟﻠﻐﺔ اﻟهﺪف ﻧﻘﺪم ﻟﻚ �ﻌﺾ اﻷﺳﺎﻟﻴﺐ اﻟﺸﺎئﻌﺔ ﺣﻮل‬

‫اﻟﻄﺮ�ﻘﺔ اﻟ�ي �ﻌﺘﻤﺪهﺎ ﺗﻘﻨﻴﺔ ﺗﺮﺟﻤﺔ اﻟﻠﻐﺔ ﻹﺟﺮاء ﻋﻤﻠﻴﺔ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ هﺬﻩ‪ .‬و�ﻄﻮر ﺧ��اء اﻟﻠﻐﺔ ﻗﻮاﻋﺪ ﻟﻐﻮ�ﺔ ﻣﺪﻣﺠﺔ‬

‫وﻗﻮاﻣيﺲ ﺛﻨﺎﺋﻴﺔ اﻟﻠﻐﺔ �جﺎﻻت أو ﻣﻮﺿﻮﻋﺎت ﻣﻌﻴﻨﺔ‪� .‬ﺴﺘﺨﺪم اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ اﳌﺴتﻨﺪة إ�� اﻟﻘﻮاﻋﺪ هﺬﻩ اﻟﻘﻮاﻣيﺲ ﻟ��ﺟﻤﺔ‬

‫ﻣﺤﺘﻮى ﻣﻌ�ن ﺑﺪﻗﺔ‪ .‬ﻓﻴﻤﺎ ﻳ�� ﺧﻄﻮات اﻟﻌﻤﻠﻴﺔ‪:‬‬

‫اﻧﺘﻘﺎﻟﻴﺎ ّ‬
‫ً‬ ‫ً‬ ‫ّ‬
‫و�ﺤﻮل اﻟ��ﻧﺎﻣﺞ اﻟﺘﻤﺜﻴﻞ إ�� ﻟﻐﺔ اﻟهﺪف ﺑﺎﺳﺘﺨﺪام اﻟﻘﻮاﻋﺪ‬ ‫ﻳﻮزع ﺑﺮﻧﺎﻣﺞ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ﻧﺺ اﻹدﺧﺎل و�ن��ئ ﺗﻤﺜﻴﻼ‬

‫اﻟﻨﺤﻮ�ﺔ واﻟﻘﻮاﻣيﺲ ﻛﻤﺮﺟﻊ و�ﻤﻜﻦ ﺗﺨﺼﻴﺺ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ اﳌﺴتﻨﺪة إ�� اﻟﻘﻮاﻋﺪ �جﺎل أو ﻣﻮﺿﻮع ﻣﻌ�ن‪ .‬و�� ﻗﺎﺑﻠﺔ‬
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‫ﻟﻠﺘﻮﻗﻊ وﺗﻮﻓﺮ ﺗﺮﺟﻤﺔ ﻋﺎﻟﻴﺔ ا�جﻮدة‪ .‬وﻣﻊ ذﻟﻚ‪ ،‬ﻓﺈ��ﺎ اﻟ��ﺟﻤﺔ ﺗ�ﻮن ﺳيﺌﺔ إذا �ﺎن اﻟﻨﺺ اﳌﺼﺪر ﻳﺤﺘﻮي ﻋ�� أﺧﻄﺎء أو‬
‫ً‬ ‫�ﺴﺘﺨﺪم �ﻠﻤﺎت ﻏ�� واردة �� اﻟﻘﻮاﻣيﺲ اﳌﻀﻤﻨﺔ‪ .‬ﻻ ﻳﻤﻜﻦ ﺗﺤﺴ�ن اﻟ��ﺟﻤﺔ ﺳﻮى ﺑﺘﺤﺪﻳﺚ اﻟﻘﻮاﻣيﺲ ً‬
‫ﻳﺪو�ﺎ ﺑﺎﻧﺘﻈﺎم‪ .‬و�ﺪﻻ‬

‫ﻣﻦ اﻻﻋﺘﻤﺎد ﻋ�� اﻟﻘﻮاﻋﺪ اﻟﻠﻐﻮ�ﺔ‪� ،‬ﺴﺘﺨﺪم اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ اﻹﺣﺼﺎﺋﻴﺔ ﺗﻘﻨﻴﺔ اﻟﺘﻌﻠﻢ اﻵ�� ﻟ��ﺟﻤﺔ اﻟﻨﺺ‪ .‬ﺗﺤﻠﻞ ﺧﻮارزﻣﻴﺎت‬

‫اﻟﺘﻌﻠﻢ اﻵ�� ﻛﻤﻴﺎت ﻛﺒ��ة ﻣﻦ اﻟ��ﺟﻤﺎت اﻟبﺸﺮ�ﺔ اﻟﺴﺎﺑﻘﺔ وﺗﺒﺤﺚ ﻋﻦ اﻷﻧﻤﺎط اﻹﺣﺼﺎﺋﻴﺔ‪ .‬ﻳﻘﻮم اﻟ��ﻧﺎﻣﺞ �ﻌﺪ ذﻟﻚ‬

‫ﺑﺘﺨﻤﻴﻨﺎت ذﻛﻴﺔ ﻋﻨﺪﻣﺎ ُﻳﻄﻠﺐ ﻣﻨﮫ ﺗﺮﺟﻤﺔ ﻧﺺ ﻣﺼﺪر ﺟﺪﻳﺪ‪ .‬ﻛﻤﺎ �ﺴتﻨﺪ ﺗﻮﻗﻌﺎﺗﮫ ﻋ�� اﻻﺣﺘﻤﺎل اﻹﺣﺼﺎئﻲ ﺑﺄن �ﻠﻤﺔ أو‬

‫ﻋﺒﺎرة ﻣﻌﻴﻨﺔ ﺳ��د ﻣﻊ �ﻠﻤﺔ أو ﻋﺒﺎرة أﺧﺮى �� اﻟﻠﻐﺔ اﻟهﺪف‪ .‬واﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ اﳌﺴتﻨﺪة إ�� اﻟﻨﺤﻮ �� ﻓﺌﺔ ﻓﺮﻋﻴﺔ ﻣﻦ اﻟ��ﺟﻤﺔ‬
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‫اﻵﻟﻴﺔ اﻹﺣﺼﺎﺋﻴﺔ‪ .‬و�� �ﺴﺘﺨﺪم اﻟﻘﻮاﻋﺪ اﻟﻠﻐﻮ�ﺔ ﻟ��ﺟﻤﺔ اﻟﻮﺣﺪات اﻟﻨﺤﻮ�ﺔ‪ .‬وﺗﺤﻠﻞ ا�جﻤﻞ ﻟﺪﻣﺞ ﻗﻮاﻋﺪ اﻟﻨﺤﻮ �� ﻧﻤﺎذج‬
‫اﻟ��ﺟﻤﺔ اﻹﺣﺼﺎﺋﻴﺔ ‪.‬وﺗﺘﻄﻠﺐ اﻷﺳﺎﻟﻴﺐ اﻹﺣﺼﺎﺋﻴﺔ ً‬
‫ﺗﺪر�ﺒﺎ ﻋ�� ﻣﻼﻳ�ن اﻟ�ﻠﻤﺎت ﻟ�ﻞ زوج ﻟﻐﻮي‪ .‬وﻣﻊ ذﻟﻚ‪ ،‬ﺗ�ﻮن اﻟ��ﺟﻤﺎت‬
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‫اﻵﻟﻴﺔ دﻗﻴﻘﺔ إذا ﺗﻮﻓﺮت ﺑﻴﺎﻧﺎت �ﺎﻓﻴﺔ‪� .‬ﺴﺘﺨﺪم اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ اﻟﻌﺼبﻴﺔ اﻟﺬ�ﺎء اﻻﺻﻄﻨﺎ�� ﻟﺘﻌﻠﻢ اﻟﻠﻐﺎت‪ ،‬وﻟﺘﺤﺴ�ن‬
‫وﻏﺎﻟﺒﺎ ﻣﺎ �ﻌﻤﻞ ً‬
‫ﺟﻨﺒﺎ إ�� ﺟﻨﺐ ﻣﻊ‬ ‫ﻣﻌﺮﻓ��ﺎ ��ﺎ ﺑﺎﺳﺘﻤﺮار ﺑﺎﺳﺘﺨﺪام ﻃﺮ�ﻘﺔ ﻣﺤﺪدة ﻟﻠﺘﻌﻠﻢ اﻵ�� اﺳﻤهﺎ اﻟﺸﺒ�ﺎت اﻟﻌﺼﺒﻮﻧﻴﺔ‪ً .‬‬

‫ﻃﺮق اﻟ��ﺟﻤﺔ اﻹﺣﺼﺎﺋﻴﺔ‪..‬‬

‫�ﻌﻤﻞ أدوات اﻟ��ﺟﻤﺔ ﺑﻤﺴﺎﻋﺪة ا�حﺎﺳﻮب )‪ (CAT‬ﻣﻊ ﺑﺮاﻣﺞ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ﻟﺪﻋﻢ ﺗﺮﺟﻤﺔ اﻟﻨﺼﻮص‪ .‬و�ﻌﻤﻞ أدوات اﻟ��ﺟﻤﺔ‬

‫ﺑﻤﺴﺎﻋﺪة ا�حﺎﺳﻮب ﻋ�� أﺗﻤﺘﺔ اﳌهﺎم اﳌﺘﻌﻠﻘﺔ ﺑﺎﻟ��ﺟﻤﺔ‪ ،‬ﻣﺜﻞ ﺗﺤﺮ�ﺮ اﻟ��ﺟﻤﺎت و�دار��ﺎ وﺗﺨﺰ���ﺎ‪ .‬ﻳﺘﻢ إدﺧﺎل اﻟﻨﺺ �� ﺑﺮﻧﺎﻣﺞ‬

‫اﻟ��ﺟﻤﺔ ﺑﻤﺴﺎﻋﺪة ا�حﺎﺳﻮب‪ ،‬و�ﺘﻢ ﺗﻘﺴﻴﻤﮫ إ�� ﻣﻘﺎﻃﻊ‪ ،‬ﻣﺜﻞ ﻋﺒﺎرات أو ﺟﻤﻞ أو ﻓﻘﺮات‪ .‬ﻳﺤﻔﻆ اﻟ��ﻧﺎﻣﺞ �ﻞ ﻣﻘﻄﻊ وﺗﺮﺟﻤﺘﮫ‬

‫�� ﻗﺎﻋﺪة ﺑﻴﺎﻧﺎت‪ ،‬ﻣﺎ �ﺴﺮع ﻋﻤﻠﻴﺔ اﻟ��ﺟﻤﺔ و�ﻀﻤﻦ اﻻ�ﺴﺎق ﻣﻊ اﻟ��ﺟﻤﺎت اﻟﺴﺎﺑﻘﺔ و�ﺴﺘﺨﺪم اﻟﻌﺪﻳﺪ ﻣﻦ اﻟﺸﺮ�ﺎت اﻟﻌﺎﳌﻴﺔ‬

‫أدوات ﺑﺮاﻣﺞ اﻟ��ﺟﻤﺔ ﺑﻤﺴﺎﻋﺪة ا�حﺎﺳﻮب ﻷﺗﻤﺘﺔ اﳌﺸﺎريﻊ اﻟ�ي ﺗﺘﻄﻠﺐ اﻟ��ﺟﻤﺔ‪.‬‬

‫وﻋﻨﺪ ا�حﺪﻳﺚ ﻋﻦ أﻧﻮاع اﻟﻨﺼﻮص اﳌﺴﺘﺨﺪﻣﺔ �� اﻟ��ﺟﻤﺔ‪� .‬ﻠﻤﺎ ّأدى اﻟ��ﻧﺎﻣﺞ ً‬

‫ﻋﺪدا أﻛ�� ﻣﻦ اﻟ��ﺟﻤﺎت �� ﻟﻐﺔ ﻣﻌﻴﻨﺔ أو‬

‫ﻣﺠﺎل ﻣﻌ�ن‪ ،‬ﻧﺘﺞ ﻋﻨﮫ ﻧﺺ هﺪف ﺑﺠﻮدة أﻋ��‪ .‬ﺑﻤﺠﺮد ﺗﺪر�ﺐ اﻟ��ﻧﺎﻣﺞ‪ ،‬ﺗﺼﺒﺢ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ اﻟﻌﺼبﻴﺔ أﻛ�� دﻗﺔ وأﺳﺮع‪،‬‬

‫وﺗﺼﺒﺢ إﺿﺎﻓﺔ ﻟﻐﺎت ﺟﺪﻳﺪة ﻣهﻤﺔ أﺳهﻞ‪.‬‬

‫ﻧﻈﺮا ﻟﻜﻤﻴﺎت اﻟﺒﻴﺎﻧﺎت‬ ‫ً‬

‫ﻣﻨﻄﻘﻴﺎ ً‬ ‫ﻳﻤﻜﻦ أن ﺗﺤﻞ اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ﻣﺤﻞ اﻟ��ﺟﻤﺔ اﻟبﺸﺮ�ﺔ �� ﺣﺎﻻت ﻗﻠﻴﻠﺔ ﻳ�ﻮن ﻓ��ﺎ اﺳﺘﺨﺪاﻣهﺎ‬
‫اﻟﻜﺒ��ة اﳌﻄﻠﻮب ﺗﺮﺟﻤ��ﺎ‪ .‬ﻋ�� ﺳبﻴﻞ اﳌﺜﺎل‪ ،‬ﺗ�جﺄ اﻟﻌﺪﻳﺪ ﻣﻦ اﻟﺸﺮ�ﺎت اﻟ�ي ّ‬
‫ﺗﻘﺪم ا�خﺪﻣﺎت إ�� اﻟ��ﺟﻤﺔ اﻵﻟﻴﺔ ��ﺪف ﻣﺴﺎﻋﺪة‬

‫اﻟﻌﻤﻼء ﻋ�� ﻣ��ة اﻟﺪردﺷﺔ اﻟﻔﻮر�ﺔ أو اﻟﺮد �ﺴﺮﻋﺔ ﻋ�� رﺳﺎﺋﻞ اﻟ��ﻳﺪ اﻹﻟﻜ��و�ﻲ‪ .‬وﻣﻊ ذﻟﻚ‪ ،‬إذا أردت ﺗﺮﺟﻤﺔ ﻣﺤﺘﻮى أﻛ��‬
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‫ً‬
‫ﺗﻔﺼﻴﻼ‪ ،‬ﻣﺜﻞ ﺻﻔﺤﺎت اﻟﻮ�ﺐ أو ﺗﻄﺒﻴﻘﺎت اﻷﺟهﺰة ا�جﻮاﻟﺔ‪ ،‬ﻓﻘﺪ ﺗ�ﻮن اﻟ��ﺟﻤﺔ ﻏ�� دﻗﻴﻘﺔ‪ .‬ﻣﻦ اﳌهﻢ إرﺳﺎل ا�حﺘﻮى إ��‬

‫ﻣ��ﺟﻢ �ﺸﺮي ﻟﺘﺤﺮ�ﺮﻩ ﻗﺒﻞ اﺳﺘﺨﺪاﻣﮫ‪.‬‬

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Appendices
Appendix I:
Scan Translator photos
Figures. 1

Figures.2
Figures.3

Figures. 4
Figures. 5
Appendix II:
Glossary English Arabic French

Glossary
Source (English) Arabic French

AI-based technological ‫اﻟﺘﻜﻨﻮﻟﻮﺟﯿﺎ اﻟﻘﺎﺋﻤﺔ ﻋﻠﻰ اﻟﺬﻛﺎء‬ Technologies basées sur

‫اﻻﺻﻄﻨﺎﻋﻲ‬
l'IA

Artificial intelligence ‫اﻟﺬﻛﺎء اﻻﺻﻄﻨﺎﻋﻲ‬ Intelligence artificielle

Machine Translation ‫اﻟﺘﺮﺟﻤﺔ اﻵﻟﯿﺔ‬ Traduction automatique

Algorithms ‫اﻟﺨﻮارزﻣﯿﺎت‬ Algorithmes

Mimicking ‫ﺗﻘﻠﯿﺪ‬ Mimétisme

Breakthroughs ‫اﺧﺘﺮاﻗﺎت‬ Percées

data-driven algorithms ‫ﻗﺎﺋﻢ ﻋﻠﻰ اﻟﺒﯿﺎﻧﺎت‬ Algorithmes pilotés par

les données

scan translator ‫ﺳﻜﺎن ﺗﺮاﻧﺰﻟﯿﺘﺮ‬ Traducteur de balayage

speech recognition ‫اﻟﺘﻌﺮف اﻟﺼﻮﺗﻲ‬ Reconnaissance vocale

Robotics ‫ﺑﺮﻣﺠﯿﺎت آﻟﯿﺔ‬ Robotique

Post-translation ‫ﻣﺮﺣﻠﺔ ﻣﺎ ﺑﻌﺪ اﻟﺘﺮﺟﻤﺔ‬ Post-traduction