Maximising Machine Translation Return on Investment (KantanMT/Medialocate)
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Transcript of Maximising Machine Translation Return on Investment (KantanMT/Medialocate)
No Hardware. No Software. No Hassle MT.
Maximising ROI for Machine Translation
in association with#KantanWebinar
Tony O’Dowd, [email protected] Rizzo, [email protected]
Speakers
KantanMT.comNO HARDWARE. NO SOFTWARE. NO HASSLE MT
Tony O’DowdFounder & Chief Architect
Maximising ROIUsingMachine Translation
What we aim to cover today?
What is KantanMT.com?
MT Return on Investment The hard facts!
Factors that influence ROI
Technologies that maximise ROI
Conclusions
15 minutes
What is KantanMT.com?
Statistical MT System Cloud-based =
Highly scalable
Inexpensive to operate
Quick to deploy
Our Vision To put Machine Translation
Customization
Improvement
Deployment
…into your hands
Active KantanMT Engines
6,191
Training Words Uploaded
36,243,234,615Member Words
Translated
428,526,741
Fully Operational 15 months
Who is generating good ROI on MT today?
Client Never used MT before
Post-Editing Rates 2,400 words per translator day
Vendor New to KantanMT.com platform
Had not previously used MT on any project
ROI
After Client
Time to deploy 6 months for 8 languages
Post-Editing Rates 4,400 words per translator day
Vendor Build all engines for client
87% increase in productivity, 30% cost savings
VendorClient
The hard facts of ROI for Machine Translation Deployment
Client Division had not used MT, but requested
it
Vendor New to KantanMT.com platform
Had not previously used MT on any project
No in-house experience
Used Kickstart Customisation Service
ROI
After Time to deploy
1st Engine built in 5 working days
Used Kickstart Customisation Service for this engine
Post-Editing Rates 12,200 words per translator day
Vendor Predicts Kantan PEX could double
daily productivity rate
VendorClient
The hard facts of ROI for Machine Translation Deployment
ROI The hard facts of ROI for Machine Translation Deployment
Benefits by deploying MT Translation Productivity
Processing more words per day to increase production capacity – 70% to 400% improvement
Translation Capacity Ability to drive more words through your organisation, improving capacity and revenue opportunities
Cost Reduced project costs – 30% + cost advantage
VendorClient VendorClient
KantanAnalytics™
Business Intelligence Quality Estimation Scores
Think FuzzyMatch for MT
Used to determine Scope
Schedule
Resources
Works with all major CATs TRADOS, MemoQ, WS, XLIFF
Kantan TotalRecall – Advanced TM
% of TM hits in this job
KantanMT – automated translations
% of automated translations for this job
Range of QE ScoresQE range defined to match existing fuzzy match ranges used by L10N industry
Quality Estimation ScoresSegment level QE scores – akin to fuzzy match scores
Word Counts – Project Stats
Can be used to develop Project TimeLine and Tiered Pricing Model for Post-Editing Projects
Placeholder & Tag CountsUsed by PM for complexity sur-charges
Business Intelligence to measure ROI
Kantan BuildAnalytics™
F-Measure ScoreMeasures word recall & precision of KantanMT engines
DistributionsProvides distribution of F-Measure scores across all reference translations
Kantan Insight™Holistic analysis of score and advice on how to improve this for KantanMT engines
Detailed Analysis Segment level F-Measure analysis to help SMT Developers improve training material
Business Intelligence to measure ROI
Kantan BuildAnalytics™
Detailed Reports for: F-Measure, BLEU and TER
Business Intelligence to measure ROI
Kantan BuildAnalytics™
Gap Analysis – quickest way of improving fluency
Business Intelligence to measure ROI
Kantan BuildAnalytics™
Training Rejects Report – Improve training data rapidly
Kantan BuildAnalytics™
Timeline – Version Control, Track Changes
Business Intelligence to measure ROI
Machine Translation Applied
Background
R&D discoveries ISO frameworks
○ Repeatable○ Documentable
Predictable Cost Integrate with TMS
○ Automate as much as possible
Project Prep
Vetting PE Resources (VM)○ PE experience○ Price negotiation○ PE Training
Mono-/Bi-lingual Domain Data Acquisition (Engineering)○ TMs○ KantanMT Stock engines○ TAUS○ Web Content/Client Source Docs
Project Prep (Cont’d)
Glossary Building (Terminologist)○ Term extraction○ Client approval○ Integration of glossary in TMS/MT Engine
Managing expectations (Sales/PM)○ Client buy-in (glossaries, style guides)○ Quality expectations○ On-time/On-budget
Engine Prep
Upload Files○ Could be Time-Consuming
Initial Build○ Allow a day for all your languages to build
Review Gap Analysis○ Correct untranslatables, if possible
Review Reject Report○ Break-up long sentences
Review Scores○ Do you need more quality translations?
Rebuild with deep tune○ average 1-5% score gain over normal training
Workflow
Post Editing
Finding the right resources is key Questions you need to ask to yourself:
○ Do we have the right resources? ● Experience, rates and output volume
○ Do we have to train our own resources? ● Guidelines, training materials, pilot projects,
continuous feedback
Set expectations and priorities right from day one with client and resources:○ Light PEMT vs Full PEMT - always give them examples○ Quality expectations:
● Low● Acceptable● On par with human translation
○ Priorities: Terminology vs Style
Post Editing
Quality Assurance
Depends on the SLA In-context check is still recommended for files with rich
formatting (websites, PDFs with images and graphics) Work with your resources to improve quality and process
○ PEX rules○ Quality Matrix○ Client Feedback Implementation
Last Thoughts
Flexibility Ability to change mid-project
Find out more about KantanMT on www.kantanmt.com
Or
Register for a private demo for your team by emailing Gina ([email protected])