This document summarizes the evolution of the translation technology landscape from the 1980s to the present and potential future trends. It covers major developments in each decade including the rise of personal computing and tools like translation memory in the 1980s and 1990s. The 2000s saw the growth of the internet, web services, and content management systems. Recent years have seen increased integration, convergence of technologies like machine translation and speech-to-speech, and a shift to cloud-based and mobile offerings. The document predicts translation may increasingly involve cultural consulting and transcreation rather than direct translation as machine translation capabilities advance.

1. Translation Technology Landscape
<<in an evolutionary perspective>>
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2. Evolution of the Translation Technology Landscape

3. Value proposition
• Native speaker translators
• Quality translations
• Local agencies (yellow pages)
Technology
LSP Profile
• Yellow Pages agencies
• Solitary job
• Single language
• Word processors
The Age of Personal Computing
Translation: Profile of the 80s
HLT
• Spell checkers
• Grammar checkers

4. What happened in the 80s
• From typex to spell checkers
• Grammar checkers (Grammatik – 1981)
• Machine translation
We were all so excited about Language technology

5. What happened in the 80s
… however primitive everything still is when we look back
• From IBM typewriters to Displaywriter system (1980)
• From telex to fax machines
• Systran on Minitel in Paris

6. Value proposition
• Project management
• Computer literacy
LSP profile
• Team work
• Multiple languages
• First consolidation wave
Technology
• Personal Computers
• Software for everything
Software is King
HLT
• DTP, artwork
• Translation memory
Localization: Profile of the 90s

7. What happened in the 90s
The hype around Language Technology continues
Lernout & Hauspie & The Flanders Language Valley
… an MT revival that failed
Logos – Tovna – Metal – DLT – Weidner – ALPS – Rosetta –
Systran
… Translation Memory broke through
ALPS Autoterm – INK Text Tools – Trados (1984)
We got special tools for software ‘translation’?
Alchemy Catalyst – Passolo
… and a better way to manage glossaries
TermTracer (1987) – Termbase – Multiterm (1990)

8. What happened in the 90s
Inflated expectations from language technology
Lernout and Hauspie (1987 – 2001)
The wearable translator
15 years later in Japan
Gaston Bastiaens goes to jail

9. Value proposition
• Single source
• Simship
Profiling
• Global span
• Full service
Globalization: Profile of 2000
Technology
• Client-server
Connectivity rules!
HLT
• Server-based TM
• GMS & TMS

10. Globalization: Technology Landscape of 2000
Competition in TM for the desktop
.. and TM for client-server
.. and ‘Advanced Leveraging’ in other domains

11. Globalization: Technology Landscape of 2000
• ALPNET Xchange • Uniscape
The emergence of GMS and TMS

12. Globalization:
“42 steps to process a simple translation job”
The reason Idiom, GlobalSight, Uniscape were able to raise $250 million…..
• )
And why did they lose it?

13. Why Companies Come and Go
The Gartner Hype Cycle

14. What else happened in 2000
TAUS Summit, Taos, New Mexico, March 15- 17, 2007: A Historical Moment
Let a thousand MT systems bloom
MT is back!

15. Value proposition
• Technology integration
• Web-based TM
• TM and MT as hybrid solution
• MT as an enabler for other business
LSP Profile
• Diversification of services
• Testing
• Digital marketing
• Consulting
Technology
• APIs
The age of web services
HLT
Integration: Technology Profile of 2010

16. Integration: Technology Landscape of 2010
Large MLV focus on CMS integration
• Lionbridge acquires Clay Tablet
• SDL goes on a spree to acquire CMS companies
Web-based TM systems
Localization Project Management Systems
GMS companies (‘old technologies’) absorbed by LSPs
• SDL buys Idiom WorldServer
• Welocalize gets GlobalSight
• Translations.com acquires GlobalLink

17. What else happened around 2010
Enterprise Language Strategy
“For the first time enterprises become strategic about translation.”
Eight things to change!
More words translated by machines than by humans

18. Enterprise SWOT Analysis (2010 – 2011)
S W
O T
• High leverage from Translation Memories
• Well established process and
management
• Quality inconsistent (local flavor missing)
• Lack of flexibility in landscape, reactive rather
than creative
• Quality review is slow – bottleneck
• Opening new markets with MT
• Engaging with users & communities
• Convergence with video and speech
• Search engine optimization
• Translation of user generated content
• Use of mobile
• Content personalization
• Locked in to vendor base
• Not scalable to expand quickly
• Urgent requirement to support new markets
• Inability to ensure quality
• Opportunity loss due to lack of personalization
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19. 19
Clients
MLV’s
In-country
offices/partners
Distributed
translators/authors
4 to 30 vendors
10 to 40 languages
100’ to 1000’s
translators/authors
Vendor Management Project Management
Quality Assurance Translation Memory
Account Management
Resources Management
Quality Assurance
Project Management Translation Memory
Resources Management
Quality Assurance
Project Management
Translation Memory
Quality Assurance Translation Memory
Static Cascaded Supply Chain
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20. Content Disruption
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21. Innovation Dilemma
S W
O T
• High leverage from Translation Memories
• Well established process and management
• Quality inconsistent (local flavor missing)
• Lack of flexibility in landscape, reactive rather
than creative
• Quality review is slow – bottleneck
• Execution on innovation fails
• Opening new markets with MT
• Engaging with users & communities
• Convergence with video and speech
• Search engine optimization
• Translation of user generated content
• Use of mobile
• Content personalization
• Locked in to vendor base
• Not scalable to expand quickly
• Urgent requirement to support new
markets
• Inability to ensure quality
• Lack of corporate awareness of new locales
• Opportunity loss due to lack of
personalization
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22. 20th Century Translation
Top-down globalization
Export mentality – pushing out
One big world
1. One translation quality fits all
2. Selecting locales – limited languages
3. Counting words – owned content
4. TM is core
5. Project-based translation
6. Cascaded supply chain
7. Publisher-driven
8. Unidirectional
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23. 21st Century Translation
Bottom-up and top-down globalization
Information is omnipresent – people are connecting
Many big worlds in one small planet
1. Quality differentiation
2. Long-tail of languages
3. Zettabytes of content–
owned, shared, earned
4. Data is core
5. Continuous translation
6. Collaborative translation
7. User-driven
8. Multidirectional
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24. Convergence: Technology Profile of 2020
Value proposition
• Real-time MT
• Speech-to-speech
LSP Profile
• Start-ups competition
• Location not so relevant
anymore
• Platforms instead of
supply chains
Technology
• Mobile
• Free & open source
The cloud is irresistible
HLT
• Subscriptions
• Innovative offerings: social
• Quality levels: transcreation
• Dashboards

25. Convergence of Markets: Translation Shifts Gears
21st Century Convergence
Luxury
Publisher-driven
translation industry
Mobile
Real-time
Personalized
Datafied Embedded
New payment models
Good enough
Continuous
+ 1,000 languages
Innovation Invaders
From 10,000 customers
who buy translation as
a ‘luxury’ product to 6
billion users who
consider translation
‘free’.

26. What is happening now
Drag and drop …
• Real-time customization of MT
Plug and play …
• Mobile apps for speech-to-speech
Translation as utility
• On every screen, in every app
Convergence of:
• Technologies: MT & S2S
• Markets: Consumer & Business
• Business: Free and Premium
Many new start-ups
Insider and invader innovators
MT as an API: pay as you go or free for data

27. Convergence: Technology Landscape of 2020
Platforms
Proxy-based localization platforms
Community translation platforms
Competitors or technology platforms to use

28. Convergence: Technology Landscape of 2020
Terminology
Web-based terminology management
Terminology search

29. Convergence: Technology Landscape of 2020
Translator productivity
Free & open source
Translator productivity tools

30. Convergence: Technology Landscape of 2020
Quality Management and Assurance
Source language control
Quality checking

31. Streetwise
Translation apps
Convergence: Technology Landscape of 2020
Translation as a utility

32. Convergence: Technology Landscape of 2020
Audio/video and speech
Audio-video captioning
Speech-to-speech

33. Singularity: Technology Profile of 2030
Value proposition
• Deep learning
• FAUT
LSP Profile
• Cultural consultants
Technology
• Robots & AI
• Law of Moore reaches a
climax
Explosion of intelligence
HLT
• Data services and cleaning
• Transcreation

34. Singularity: Trends of 2030
“Would I recommend to my young children to choose human
translator as a profession? The answer is clearly "no". I would
try to redirect them to be a language- and culture consultant.
Transcreation and adaptation between cultures will remain
necessary for one more generation, until the differences
between earth's cultures have been reduced to minor deltas
that machines can bridge. It is not only the technology that
changes. Human behavior, thought and creativity also change
in an increasingly connected world.”
Chris Wendt, Microsoft:
The Future Does Not NeedTranslators*
Read the blog and comment

35. Evolution of the Translation Technology Landscape

36. What Have we Learned?
Mission driven
Data driven

37. ThinkTank →→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→→
Platform for Industry-shared services →→→→→→→→
Themes
Translation
Automation
Language
Business
Innovation
Enterprise
Language
Strategy
Together We
Know More
Human
Language
Project
Game-Changers
in Localization
Milestones
Drive MT
adoption
Introduced
crowdsourcing
in translation
TM Data
Sharing
Best practices in
post-editing
Dynamic Quality
Framework
DQF Public API
TAUS is a resource center for the global language and translation industries.
Our mission is to enable better translation through innovation and automation.
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

38. MT is here to Stay
But who owns it and makes money with it?
• Google, Microsoft, Baidu, Alibaba, Google, eBay,
Facebook, Microsoft, Yandex, Amazon will be the
strongest MT operators without straight revenue
goals
• IBM, NTT DoCoMo?
No more empty segments
• TM and MT ‘re-converge’
Commercial MT providers
• Systran, KantanMT, Iconic, Asia Online, tauyou,
Mirai, Cross Language, ProMT, Lucy Software, CCID,
PangeaMT, Globalese
MT as an enabler
• For other business benefits and revenue generation
FAUT
• Focus on MT has changed from FAHQT to a tool to
support global communications

39. Keynotes 2015 eBook
Download it here:
https://www.taus.net/think-
tank/reports/event-
reports/keynotes-2015

40. TAUS Translation Data Landscape Report
TAUSTranslationDataLandscapeReport
December 2015

41. This slide may not be used or copied without permission from TAUS