What you need to put Machine Translation into practice: Tools, People, and Processes

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You have no doubt been hearing about machine translation (MT) for several years now, but translating it into a high Return on Investment is not an easy task. We have heard many success stories presented at conferences, but we know a high number of LSPs that have failed to achieve their goals. In this master class we will share some success stories but also some failure use cases, so that we can all learn from them. After that, three hints on tools, people and processes will be given to help you successfully integrate MT into your workflow. Finally, we will discuss several examples of post-editing English machine translation output from various source languages.

What you need to put
Machine Translation
into practice:
Tools, People, and Processes
Diego Bartolome
@diegobartolome
dbc@tauyou.com

60+ clients
16 countries
~1 billion words in 2013 (cost reduction)
All language pairs

Why Machine Translation?

Why Machine Translation?
Price pressure
Tight deadlines
Client requests (impossible projects)
New needs from clients
Everyone else is doing it
...

Machine Translation requires
Initial investment
Time
Continuous improvement
Change in company culture
Clear goal

Machine Translation Companies
and others

What do you look for?

Some ideas
Confidentiality Customization
Control User friendliness
Flexibility Technology
Business model Quality
Relationship structure Trust

Engine building FAQ

Engine building FAQ
How many words/segments do I need?
How do I measure quality?
What language pairs work best?
What are the solutions if quality is unacceptable?
How often engines need retraining?

Process integration
What is the best process?

Most extended process
Prepare files
Pre-translate (>85%)
Prefill remaining segments with MT
Post-edit MT + review TM
Update TM (+MT) + compute quality metrics
Automatic Post-editing Rules

People
What are the challenges you have faced?

People
Averse to change
Importance of less time consuming errors
Training
Age/years of experience
Time vs. money

3 hints
Tools
invest in choosing the right one for you
Process
decide a process from the beginning
People
make everybody win

Post-editing examples

Change before
you have to
Jack Welch

Other interesting topics
Optimized big data approach to MT
Quality Checks
Online postediting interface
Process automation (API)

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In this keynote, Asanka Abeysinghe, CTO,WSO2 will explore the shift towards platformless technology ecosystems and their importance in driving digital adaptability and innovation. We will discuss strategies for leveraging decentralized architectures and integrating diverse technologies, with a focus on building resilient, flexible, and future-ready IT infrastructures. We will also highlight WSO2's roadmap, emphasizing our commitment to supporting this transformative journey with our evolving product suite.

Platformless Horizons for Digital Adaptability

Platformless Horizons for Digital Adaptability

Platformless Horizons for Digital Adaptability

The value of a flexible API Management solution for Open Banking Steve Melan, Manager for IT Innovation and Architecture - State's and Saving's Bank of Luxembourg Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Artificial Intelligence Chap.5 : Uncertainty

Artificial Intelligence Chap.5 : Uncertainty

Artificial Intelligence Chap.5 : Uncertainty

Khushali Kathiriya

Elevate Developer Efficiency & build GenAI Application with Amazon Q

Elevate Developer Efficiency & build GenAI Application with Amazon Q

Elevate Developer Efficiency & build GenAI Application with Amazon Q

Bhuvaneswari Subramani

CNIC Information System with Pakdata Cf In Pakistan

CNIC Information System with Pakdata Cf In Pakistan

CNIC Information System with Pakdata Cf In Pakistan

The Good, the Bad and the Governed - Why is governance a dirty word? David O'Neill, Chief Operating Officer - APIContext Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

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Why Teams call analytics are critical to your entire business

Why Teams call analytics are critical to your entire business

Why Teams call analytics are critical to your entire business

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff

Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving

Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving

Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024

Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024

DBX First Quarter 2024 Investor Presentation

DBX First Quarter 2024 Investor Presentation

DBX First Quarter 2024 Investor Presentation

ICT role in 21st century education and its challenges

ICT role in 21st century education and its challenges

ICT role in 21st century education and its challenges

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

"I see eyes in my soup": How Delivery Hero implemented the safety system for ...

MS Copilot expands with MS Graph connectors

MS Copilot expands with MS Graph connectors

MS Copilot expands with MS Graph connectors

Six Myths about Ontologies: The Basics of Formal Ontology

Six Myths about Ontologies: The Basics of Formal Ontology

Six Myths about Ontologies: The Basics of Formal Ontology

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME

Platformless Horizons for Digital Adaptability

Platformless Horizons for Digital Adaptability

Platformless Horizons for Digital Adaptability

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Apidays New York 2024 - The value of a flexible API Management solution for O...

Artificial Intelligence Chap.5 : Uncertainty

Artificial Intelligence Chap.5 : Uncertainty

Artificial Intelligence Chap.5 : Uncertainty

Elevate Developer Efficiency & build GenAI Application with Amazon Q

Elevate Developer Efficiency & build GenAI Application with Amazon Q

Elevate Developer Efficiency & build GenAI Application with Amazon Q

CNIC Information System with Pakdata Cf In Pakistan

CNIC Information System with Pakdata Cf In Pakistan

CNIC Information System with Pakdata Cf In Pakistan

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...

Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...

What you need to put Machine Translation into practice: Tools, People, and Processes

1. What you need to put Machine Translation into practice: Tools, People, and Processes Diego Bartolome @diegobartolome dbc@tauyou.com

2. 60+ clients 16 countries ~1 billion words in 2013 (cost reduction) All language pairs

3.

4. Why Machine Translation?

5. Why Machine Translation? Price pressure Tight deadlines Client requests (impossible projects) New needs from clients Everyone else is doing it ...

6. Machine Translation requires Initial investment Time Continuous improvement Change in company culture Clear goal

7. Machine Translation Companies and others

8. What do you look for?

9. Some ideas Confidentiality Customization Control User friendliness Flexibility Technology Business model Quality Relationship structure Trust

10. Engine building FAQ

11. Engine building FAQ How many words/segments do I need? How do I measure quality? What language pairs work best? What are the solutions if quality is unacceptable? How often engines need retraining?

12. Process integration What is the best process?

13. Most extended process Prepare files Pre-translate (>85%) Prefill remaining segments with MT Post-edit MT + review TM Update TM (+MT) + compute quality metrics Automatic Post-editing Rules

14. People What are the challenges you have faced?

15. People Averse to change Importance of less time consuming errors Training Age/years of experience Time vs. money

16. 3 hints Tools invest in choosing the right one for you Process decide a process from the beginning People make everybody win

17. Post-editing examples

18. Change before you have to Jack Welch

19. Other interesting topics Optimized big data approach to MT Quality Checks Online postediting interface Process automation (API)