Lights Out! Translation is Datafied.<<the evolution of translation technology>>

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Evolution of the Translation Technology Landscape

Convergence of Markets: Translation Shifts Gears

21st Century Convergence

Luxury

Publisher-driventranslation 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’.

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

Translation production is growing faster (in words)

HT

Machine Translation output(No human touch)

= 100 times bigger than

human

translation production *

* 30B times 100 = 3 Trillion words in translation volume.

Human Translation = TM + MT + PEAnd diversifying with crowdsourcing, digital marketing, testing, validation,

transcreation, talent search

* 30B/$0.10 = 300 Billion words in translation volume.Check: 300 Billion words / half million per translator = 600,000 translators

Industry is Growing (in $)

0

5

10

15

20

25

30

35

40

45

1980 1990 2000 2010 2020

… but changing radically

Translation PM QM Testing Digital Marketing

Crowdsourcing Talent Mgnt MT PE Transcreation

We want to publish a report:

TAUS Five Year Translation Innovation RoadmapReport to be published in April, freely downloadable from TAUS web site.

Objectives:1. Influence the ecosystem and promote innovation across the industry2. Provide a reference for strategy planning for all stakeholders in the global translation industry3. Setting priorities and providing ideas and guidance for TAUS industry-shared services

Objectives of the TAUS Industry Consultation

The TAUS Industry Consultation Process

1. Survey to collect ideas: we received 60 ideas from TAUS members and non-

members

Nov./Dec. 2016

2. TAUS categorized the ideas and grouped them under 13 themes or programs Dec. 2016

3. 200+ responses to survey to prioritize the programs. Jan. 10 2017

4. TAUS New Year’s Reception webinar: preview of outcome Jan. 17, 2017

4. TAUS Advisory Board selects 5 to 7 programs that will be further researched and

prepared

Jan. 18 2017

5. TAUS team plus industry experts research ideas and prepare briefing for the

Summit

Jan./Feb. 2017

6. Registration for the Summit needs to confirmed (50 participants) Jan. 31 2017

7. Participants will be engaged in some of the Summit preparations Feb./Mar. 2017

8. Industry Summit takes place in Amsterdam, chaired by an independent facilitator Mar. 22-24, 2017

9. TAUS Five Year Translation Innovation Roadmap report will be published. Apr. 30 2017

Results Survey Industry Consultation

8

97

90

4 3

Distribution of Responses

Academic Buyers Providers Gov-NGO Freelancers

All responses are from decision makers, director level and business owners. (Thanks to very targeted and personal email invitations.)

TAUS Priorities

Top 5:1.Machine Learning2.Quality Dashboard & DQF3.Machine Translation4.Intelligent TM 5.Interoperability

Second rank:6. Data Cloud7. Translation and IT infrastructure8. Open source tools

Out?9. Academy10. Driving adoption11. Speech data?????12. Regulations13. Crowdsourcing

Comparing Priorities Board with Totals

Total

Board

1. 2.3.5.4.6. 7.8.9. 10. 11.

13. 12.

Translation is datafied

Machines are learningFor improvement of automated translation: Neural MT of course ….

… but also for translation process automation:• Translator: productivity (words and edits per hour, mouse clicks), behavior, on-

time delivery, eye tracking, biographical data, capacity, third party evaluations, interests, social graph

• Environment: weather, time zone, news events• Project metadata: industry, content type, language pair, process, technology,

client, translator, reviewer• Quality: requested quality level (good enough, human quality), purpose, source

analysis• Technology: MT engines, TM leverage, process settings, data used for training

Lights out:Translation becomes ‘invisible’, a utility like electricity, internet.We (as professionals) will all have dashboards to control and track the quality of our translations.

Algorithmic Management of Translation

“How long will it take before my customer finds out?”

Datafied Translation Platforms

Discussion

Trends and innovations emerging from algorithmic management in the translation industry?

Define Machine Learning: …..

Algorithmic management: “how to instruct, track and evaluate a crowd of casual workers you do not employ, so they deliver a responsive, seamless standardized service.”

SWOT of Machine Learning in Translation

S W

TO

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