As an academic trainer, professor or lecturer in translation and localization, staying up-to-date with technology used in industry will help your students prepare for their future careers. In this webinar geared towards our existing and potential University Partners, Carlos covers the complete language review workflow and how this helps in building better quality Machine Translation engines. Link to YouTube:https://www.youtube.com/watch?v=x0fIdGlIVNE

1. Getting Started with
KantanLQR™

2. START

3. What is the importance of LQR?
 Steps to improve the quality of an engine
KantanMT
Engine
Add
Training
Data
Build
Check the scores
Add
more
Training
Data
Build again
Check the scores again
LQR
Perform the LQR

4. How to prepare for an LQR
Output
Machine
Translated Test
Sets
Set up the LQR
KantanMT
Engine
Untranslated
Test Sets

5. What do you need to set up the LQR?
2. Select your KPIs

6. KantanLQR Platform

7. After the LQR
 Customize your Engine – Runtime customisation improves Quality too!
Reduced Post-Editing Higher Quality
KantanMT
Engine

8. Constant Quality Improvement
Rebuild KantanMT EngineHigher Quality
 Post-Editing Feedback - Rapidly improves your KantanMT Engine.
XLIFF, TMX
Finalised Publishable
XLIFF, TMX
Post-EditingMachine Translation
KantanMT
Engine
KantanMT
Engine

9. Q&A
For more information on KantanLQR
or our University Partner Programme,
mail info@kantanmt.com
Thank you!