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

mailto:[email protected]

mailto:[email protected]

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


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


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



Detailed Reports for: F-Measure, BLEU and TER



Gap Analysis – quickest way of improving fluency



Training Rejects Report – Improve training data rapidly


Timeline – Version Control, Track Changes


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

Marcelo Rizzo

perfect

Martiño Prada

[email protected] not sure how Kantan MT integrates glossaries in their engine and how that affetcs the output, but I threw this one out there.

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])

http://www.kantanmt.com/

Maximising Machine Translation Return on Investment (KantanMT/Medialocate)

Technology

Transcript of Maximising Machine Translation Return on Investment (KantanMT/Medialocate)