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Deploying Machine Translation in an Industrial Setting: Challenges and Opportunities
Opportunities
Deploying Machine Translation in an Industrial Setting: Challenges - - PowerPoint PPT Presentation
Deploying Machine Translation in an Industrial Setting: Challenges - - PowerPoint PPT Presentation
Deploying Machine Translation in an Industrial Setting: Challenges and Opportunities Opportunities Opportunity 1 On-line spending power 2020 - $16 trillion English only! ( Source: PracticalEcommerce ) Industry without borders 2020 -
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Opportunity
On-line spending power
2020 - $16 trillion English only!
( Source: PracticalEcommerce )
Industry without borders
2020 - $17.5 trillion Non-English!
( Source: PracticalEcommerce )
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Opportunity
73% of consumers more likely to purchase a product in their own language
( Source: EU Study of 2,430 web consumers in 8 EU Countries )
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Opportunity
9 out of 10 internet users will visit websites in their own language when given a choice
( Source: EU Study of 2,430 web consumers in 8 EU Countries )
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Opportunity
42% of consumers never buy a product/service in other languages
( Source: EU Study of 2,430 web consumers in 8 EU Countries )
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Opportunity
The Comfort Factor
Consumers prefer not to have to work too hard to get information that shapes their purchasing decisions
( Source: EU Study of 2,430 web consumers in 8 EU Countries )
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Opportunity
40% of current Ecommerce Companies turn away international orders
( Source: QNET Market Report 2015 )
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Lots and Lots of Opportunity
Selling Seamlessly Across Language Boundaries
42% of consumers never buy a product in other
languages
40% of current eCommerce Companies turn away
international orders
Offering Personalisation
73% of consumers more likely to purchase a
product in their own language
9 out of 10 internet users will visit websites in
their own language when given a choice
Building a Trustworthy eCommerce Brand
Consumers prefer not to have to work too hard to get information that shapes their purchasing decisions
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An undeniable truth…
Multi-lingual Digital Age
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Challenges
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Challenges
Some Interesting Challenges Building CMT Systems that Scale (massively)
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Interesting Challenges
Convergence of mechanisms Measuring Quality BLUE, TER, F-Measure For Development SDL Trust Score, KantanAnalytics For Translators
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Interesting Challenges
Establish a standard for MT Quality
Standards - MTQ
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Move beyond comparative methods
Make it Predictive
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Compliment current standard
Business Model
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Interesting Challenges
Making it fit into workflows Integration Making it fit into CAT Environments Post-Editing Making it fit into business models Business Models
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Interesting Challenges
Post-Editing is the future!
CAT Tools are dead Pretranlation is the future!
No difference between MT and TM
Intelligent Convergence
Fully Integrated TM, MT (more than 1), Glossary etc.
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Interesting Challenges
Phrase, Hierarchical, Neural etc. Which is best? Models On-the-fly improvements Static vrs Fluid Every micro-second is sacred Processing Speed
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Interesting Challenges
The new must-have for all MT systems
Adaptive MT Feedback system
Translator needs to see improvements real-time to boost confidence in using MT Systems
Super Fast Speed
New modelling need to be superfast
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Thank you…