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Content Strategy and Machine Translation The Winning Combination
Webinar Content
The Prize What can be achieved with MT
MT & The Content Strategy How content strategy can be
adapted for MT
Q&A
40 minutes
The Prize
What is KantanMT?
Statistical Custom MT Platform
Cloud-based Extremely customisable Highly scalable for high
volume Fully-automated translations High speed, high quality
translations
Active KantanMT Engines
9,392Training Words Uploaded
434,189,753,677Member Words Translated
7,161,269,925
KantanMT
Software Industry.
Software Industry.
ObjectivesBuild MT engines for on-line helpPilot for English => GermanScale to multiple target languagesFocus on Translator productivity
ChallengesComplexity of online help contentVery tight production schedules
Pilot & Other Languages < 4 months
Software Industry.
ResultsHighly Scalable: +4 languages in 6
monthsHigh Quality Translation outputTranslator Productivity Increase: 30-50%Reduced Project Costs: 27-40% savingsLower Post-Edit Rates after KantanMT
Engine Retraining
Case Study available for download.
Technical Manuals
Technical ManualsObjectives
Languages: English->DutchPOC to validate rapid ROIFocus on translation productivitySolution must scale to 50 manuals pa. Integrate to existing L10N workflow
ChallengesClient had already built in-house MTOutput of in-house system very poor
Technical ManualsResults
Seamless integration into existing L10N workflowTranslation productivity: + 25% Reduced Post-Editing effort using PEXReduced project turnaround timeSignificantly higher quality translations achievedProcess will scale to meet future requirements
Case Study available for download.
MT & Content Strategy
Strategic Decisions
High Level Business Needs - Create a ‘Global Model’
Structural Elements What content? Where is it needed? What are the differences?
Governance Elements How will it be managed?
Strategic Decisions – where?
= 3 billion people
What Languages?
Government of India – Hindi in the Devanagari script plus English
Indian constitution lists 22 recognised languages
2001 Census – 122 major languages and 1,599 other languages
Also recorded 30 languages spoken by more than 1m people
Education Levels?
Adult Literacy Rate, 15+ both sexes. Source: Worldbank
World Average
Philippines
India
ChinaIndonesia
Nigeria
In Thailand for instance?
Official government survey : Average amount of reading by respondents – 7 sentences per year.
Website experience - No use of ‘more info’ button No product descriptions Use of imagery and video
Think about how best to present the information
Structural Model and MT
What ContentWhat Locales and
Languages?
What Content Types?
Sharing, Differences,
Transcreation?
MT?
It’s the needs of the business that influence these decisions. Make the decisions and then review the process for MT fit.
Governance Model and MT
Centralised Federated Hybrid
• One MT system makes sense to generate economies of learning across management and users. (Unless that provider cannot service the locale/domain.)
• Cloud based solutions can be accessed from anywhere!• Leverage local language/domain expertise if required
Getting Tactical about Content for MT
Shorter sentences Remove needless words Be consistent Use glossaries Avoid idioms and jargon Use correct grammar Controlled Language Identify Named Entities Stick to Unicode Standard -
UTF8
Get serious about TMs
MT depends on Training data
Cleanse your TMs
Training data can help to:Improve precision – bi-lingualImprove fluency – mono-lingualMaintain consistency – glossaries
Library data and pre-built engines* can help to supplement data.
(*KantanLibrary™ & KantanFleet™)
How is Quality Determined
Automated scores Build Analytics Linguistic Quality Review
But ultimately: The customer decides!! Build in your own kpis
Thank You.
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