Translation technologies have evolved significantly with each industrial revolution due to advances in communication and computing. Industry 5.0 will see greater man-machine integration through collaborative robots and voice command interfaces. Neural machine translation powered by deep learning is becoming more accurate but still requires human oversight. The growth of technologies like the Internet of Things, cloud computing and artificial intelligence will drive new applications of translation in industry and global communication.

1. Scope of Translation
Technologies in Industry 5.0
Dr. VMS

2. Eugene Nida
“That translation consist of reproducing in
the receptor language the closest natural
equivalence of the source language
message, first in terms of meaning and
secondly in terms of style”

3. Peter Newmark
“Translation is rendering the meaning of a
text into another language in the way that
the author intended the text”

4. Jacobson
 Intralingual translation or rewording is an
interpretation of verbal signs by means of
other signs of the same language. It means
“to put meaning in different words.”
 Interlingual translation or translation proper
is an interpretation of verbal signs by
means of some other language.
 Intersemiotic translation or transmutation is
an interpretation of verbal signs by means
of signs of non verbal sign systems. As like
novel to film or story to a play.

5. Catford
 Full Translation: It is a type of
translation in which the entire SL text is
reproduced by the TL text materials.
 Partial Translation: there are only some
parts of the SL text to be translated into
the TL text
 Total Translation: the TL material
replaces all levels of the SL text.

6. Catford
 Restricted Translation: it is the
replacement of SL textual material with
equivalent TL material at only one level;
whether at the phonological level,
graphological level, or at the level of
grammar and lexis
 Rank – bound translation: It means that
the selection of TL text equivalent is limited
at only one rank, such as word-for-word
equivalence, morpheme-for-morpheme
equivalence, etc.

7. Components of language
 Phonology ((rhyme – rhythm – alliteration –
consonance – assonance – metre – foot –
chiming – stress – pitch – tone -, etc.
 Vocabulary- synonymy – polysemy – antonyms –
connotations – collocations – idioms – proverbs –
metaphors – technical terms – culture, etc.
 Grammar (sentences – clauses – word order –
tenses – voice – questions – negations –
imperatives adjectives –adverbs – articles, etc.
 Style (formality vs. informality – fronting –
parallelism – ambiguity – repetition –
redundancy- short sentencing – long sentencing
– nominalization – verbalization, etc.

8. Translation
 Phonological,
 morphological,
 syntactic
 Pragmatics
 Culture
 Social
 Translators, knowledge and fluency in
language

10. Major Translation Domains
 cultural exchanges,
 countries’ external affairs,
 tourism, health care and medical,
 banking and insurance,
 education and training,
 software development,
 research publications,
 patent filing,
 Artificial intelligence, etc.

11. Evolution of Translation
 Translation has always played a crucial
role in interlingual communication by
allowing for the sharing of knowledge and
culture between different languages.
 Cronin (2013) argues that any form of
global interaction cannot occur without
interlingual activities and thus
globalization denotes translation.

12. Industrial Revolution 1
Time line Industrial
revolution
Impact over
human life
Impact of
language
18th
century
steam
power and mechani
sation of production
increasing
productivity
steamship
steam-powered
locomotive
Easy and faster
work,
Human beings
got leisure time,
Thinking
process got new
avenues,
Ideas of
movements from
place to place
Work with new
machines need
identification of
mechanical
parts and
instruction.
Instruments’
source
language need
to be
translated into
the borrowers

13. Industrial Revolution 2
Time
line
Industrial
revolution
Impact over
human life
Impact of language
19th
century
1870
oil, electricity,
and gas,
Automobile
production,
Telegraph and
the telephone
Work time
altered in
between day
and night,
Machines
became more
reliable
sources,
Mobility made
easier,
Cost of material
Travel, excursion and
enterprise started,
Translation for survival in
new environment was
insisted,
Thrust for new
knowledge across the
community needed
linguistic equivalence

14. Industrial Revolution 3
Time line Industrial
revolution
Impact over
human life
Impact of
language
20th century
Started during
1970s
Partial
automation,
Microprocessors
,
Memory
program
controls and
computers,
globalization
and
manufacturing
outsourcing
Automatic
production,
Robots to
carryout
programmed
sequences,
man- machine
integration
e-translation
dictionaries,
Initiation of
machine
translation,
Need for
multilingual
translation in
globalisation

15. Industrial Revolution 4
Time line Industrial
revolution
Impact over
human life
Impact of
language
Until recent past,
mostly currently
implementing
Information and c
ommunication
technologies to in
dustry,
Computer
technology with
networking,
Smart production
and smart
factories, Cloud
computing, AI,
IOT, Data
analytics,
Augmented reality
Faster and
reliable
production,
Sophisticated
work environment,
Autonomous
production
Voice commands
to machines,
Hi-fi sensing
oriented machine
instructions,
Human- machine
and machine-
human
communication,

16. Industrial Revolution 5
Time line Industrial
revolution
Impact over
human life
Impact of
language
Present age robotics and
artificial
intelligence.
,
virtual
education,
“cobots”-
collaborativ
e robots
Sustainable
policies,
Minimal waste,
Making
organisation
more effective,
Comfort and
convenience
Human –machine
interaction,
multilingual voice
commands and
perception,
Involving the
interaction of
human
intelligence and
cognitive
computing,

17. Industrial revolution and translation activities
 need for knowing the operation of
machines-reading manuals and listening
instructions
 travel made exploration to newer places
and meet newer people-translation for
understanding people, language and
survival
 incorporating human language into
machine at global context-computational
technologies for easy access, machine

18. Industrial revolution and translation activities
 integrating information and
communication technology into the
global village-man-machine
communication, speech to text and text
to speech synthesis, augmenting AI in
communication systems
 Considering machine as human like
servants-complete voice command over
machines-synthesis at multilingual
levels, bot and cobot synergies in human
communication

19. Man-Machine integration
 integrate intelligent automation, devices,
and systems at the workplace to elevate
co-operation and collaboration between
humans and machines.
 It would help highly-skilled workers to
guide smart machines and robots and
work better and faster alongside
collaborative bots or cobots.

20. Machine Translation
 Statistical Machine Translation (SMT)
 SMT works by referring to statistical models that are based
on the analysis of large volumes of bilingual text. It aims to
determine the correspondence between a word from the
source language and a word from the target language.
 Rule-Based Machine Translation (RBMT)
 RBMT, on the other hand, translates on the basis of
grammatical rules. It conducts a grammatical analysis of the
source language and the target language to generate the
translated sentence.
 Hybrid Machine Translation (HMT)
 HMT, as the term indicates, is a blend of RBMT and SMT. It
leverages a translation memory, making it far more effective
in terms of quality.
 Neural Machine Translation (NMT)
 NMT is a type of machine translation that depends on neural
network models (based on the human brain) to develop
statistical models for the purpose of translation. The primary
benefit of NMT is that it provides a single system that can be
trained to decipher the source and target text.

21. Industry 4.0
Industry 4.0 refers to the intelligent networking
of machines and processes for industry with the
help of information and communication
technology.
 System Integration
 Big Data and Analytics
 Simulation and Virtualization
 Internet of Things (IoT)
 The Cloud
 Cybersecurity
 Autonomous Robots
 Augmented Reality
 Additive Manufacturing

24. Industry 5.0
 Industry 5.0 is already being spoken about and involves
robots and smart machines allowing humans to work
better and smarter.
 Esben Østergaard, U “Industry 5.0 will make the factory
a place where creative people can come and work, to
create a more personalised and human experience for
workers and their customers."
 By connecting the way in which man and machine work
together, estimates say that Industry 5.0 will mean that
over 60% of manufacturing, logistics and supply chains,
agri-farming, and the mining and oil and gas sectors
will employ chief robotics officers by 2025.

25. Industry 5.0
 Driverless cars with artificial
intelligence
 Automated supermarkets run by
collaborative robots (cobots) working
without human supervision
Big Data and IoT builds on
(1) broadband wireless internet
connectivity,
(2) miniaturized sensors embedded in
animate and inanimate objects
(3) artificial intelligence and cobots

26. Japanese perspective on 5.0
Japan defines Industry 5.0 as ‘Society 5.0
’ a ‘human touch’ revolution: “A human-
centered society that balances economic
advancement with the resolution of social
problems by a system that highly
integrates cyberspace and physical
space.” The phenomenon visualizes a
forward-looking society and without
information stagnation.

27. Considerations
 Introducing scientific, technical and computer
oriented models and knowledge aspects in all
viable fields of Linguistics
 Analysing Human language and investigate
the possibilities of matching with Machine
language through Linguistic insights

28. Translators skills
As Samuelsson-Brown notes, among the
skills that a translator needs to acquire in
the 21st century there is a whole cluster of
IT-skills, including mastering the hardware
and software used in producing
translations, electronic file management,
and E-commerce (Samuelsson-Brown
2004: 2).

29. Neural Machine Translation
Neural Machine Translation is a machine
translation approach that applies a large
artificial neural network toward predicting
the likelihood of a sequence of words, often
in the form of whole sentences. Unlike
statistical machine translation, which
consumes more memory and time, neural
machine translation, NMT, trains its parts
end-to-end to maximize performance. NMT
systems are quickly moving to the forefront
of machine translation, recently
outcompeting traditional forms of translation
systems.

31. Neural Machine Translation
Recent advances in deep learning, also known as using
neural machine learning, has proven to achieve state of
the art results in machine translation. Google Translate
announced they had made the full switch to neural
machine

32. Neural Machine Translation
 State of the art neural machine translation
engines are now capable of instantly
translating texts with 60-90% accuracy?
 But the technology is not without its faults
when put in practice for real-world
translation.
 Neural machine translation will likely
continue to improve over time through better
neural network architecture, vetted quality
data, and more computation. This change in
neural AI technology will require human
translators to adapt to the benefits of the

33. IOT
 “IoT”, refers to the digital interconnection
between any device to the Internet. It is all
about bringing objects to life through the
power of Internet and making them
communicate through wireless protocols,
domains, and applications.
 IoT is changing the way we interact with
products and how fast we perform tasks
with them, which demands for almost
instantaneous communication. This instant
communication not only needs to happen
between machines, but also between the
devices and users.

34. 20 billion IoT devices will be
available by 2020

36. Deep Learning
 Deep learning is an AI function that
mimics the workings of the human brain
in processing data for use in detecting
objects, recognizing speech, translating
languages, and making decisions.
 Google's search engine, voice
recognition system and self-driving cars
all rely heavily on deep learning. They've
used deep learning networks to build
a program that picks out an attractive
still from a YouTube video to use as a
thumbnail.

38. Cloud Computing
Computer technology that uses the internet
network to provide software and hardware
resources remotely. Cloud computing
service is supplied by specific companies
called Cloud providers, which handle the
resource allocation and, eventually, even
the complete management of the service.

39. Cloud-based translation
 Cloud-based translation is used to enhance
functionality or increase capacity without
incurring increased costs such as that of
training in-house staff.
 cloud-based translation is translation
performed using a cloud-based server.

40. ’Machine translation is still nowhere
near the standard of human
translation'

43. Future of Machine
Translation
 The Use of Machine Translation with
Human Post Editing Will Increase.
 More Companies will Decide to
Globalize
 Video Localization Will Experience
Huge Growth

45. Thank You