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Getting the Most
from MT + PE
Reducing turn-around times and maximizing cost-
effectiveness
In translation
since 1982
Working with
MT since 1991
Practical
advice
Method?
Overview
 Laying foundations
 Defining requirements
 Arranging the platform
 Running projects
Laying foundations
Devising strategies
Modes of use
Fully
automatic
High
quality
Unrestricted
texts
Restricted
input
Impractical
Low
quality Interactive
Cobbler, stick to thy
last
Zapatero, a tus zapatos
Schuster, bleib bei deinem Leisten!
Schoenmaker, blijf bij je leest
Ne supra crepidam sutor iudicaret
Not exactly
child’s play
 Technology
 Data
 Skills
A typical
translation
industry
mindset
Would you ask
a barber if you
need a haircut?
3 tips for
getting started
1. Recap your goals and requirements
2. Hire an independent consultant
3. Qualify your business processes for MT
Defining
requirements
KISS, or Keep It Short and Simple
Building blocks
 Scope
 Goals
 Expectations
 E-services
• Knowledge bases, assistance-and-support
pages, intranets
• Real-time communication
 Productivity
• User support, technical and user
documentation
 Intelligence
• Text mining and analysis, research, CRM,
patents
 Communication
• Emails, messaging, chats
Scope
 Reduce cost
• By cutting labor
 Boost productivity
• Greater volumes, faster delivery
 Improve consistency
• Of terminology and style
 Reach a global audience
Goals
Expectations
 Financial
• Develop business
• Increase revenue
• Increase profits
 Business
• Expand offering
• Increase service levels
• Streamline processes
 Performance
• Boost productivity
• Deliver faster
• Offer higher quality
Requirements
 Spending cap
 Timeline
 Technology
 Security
 Expertise
 Reporting & analytics
 Support
Trust the
consultant
 Reconcile goals and expectations
 Outline an exploratory program
 Benchmark performance
 Prepare the specs
 Draft a SOW
 Write the RFP
 Vet vendors
 Prepare your data
 Revise business and pricing models
 Retrofit processes
Pick the right
vendor
Not all beers are created equal.
(Not all vendors are created equal.)
Prepare
 Data
 Configuration plan
 Training/recruiting program
Business
model
Be realistic MT grants no immunity to price pressure
Note the trend
More and more, intermediaries are cut out
Building the
platform
Selecting vendors, completing set-up, training staff,
testing
Givens
 Not all engines are created equal
 Raw output can vary across systems—
and language pairs
 Errors may not follow a consistent
pattern
 Engine performance also varies
Set-up
 Data
• Maintenance
 Customized engine
• +50,000 segments
 Tool settings
• Sub-segment recall
• Fuzzy match repair
In-house or
outsourced?
 Total cost of ownership
 Integration
 In-house expertise
 Confidentiality
 Intellectual property issues
Best practices
Running projects
Key questions
 Buyer or vendor?
 Dos & Don’ts?
 How do I deal with data?
 How do I assess quality?
 How do I hire staff?
 What about post-editing?
Dos
 Know your data
 Consider training necessary
 Leverage quality evaluation metrics
 Define AQLs
 Plan for continuous improvement
 Arrange for post-editing
 Devise a compensation scheme
Don’ts
 Treat all content equally
 DIY
 Rely on vendors only
 Mess with data
 Trust one single metric
 Rush
 Mess with staff
 Expect miracles
And remember:
Tell the customer you are using MT
So you won’t get sued
The fuel Output is only as good as the data used
Quantity and
quality
 1,000,000 words/50,000 segments
• No contiguous/inclusive domains
 More data  higher quality
• Good data
Good data
 Few reliable sources
 Single domain
 Current data
 Same encoding
 No empty segments
 No errors
 Terminologically consistent segments
 Same style
 Same-length segments
The output Accept that output is unpredictable
Automatic
metrics
Use all available automatic metrics
Post-editing:
expectations
1. Fast
2. Unchallenging
3. Flowing
Post-editing:
measures
 Edit Time
• The time required to get a raw MT output to
the desired standard
 Post-editing effort
• Percentage of edits to be applied to raw MT
output to attain the desired standard
Can only be computed downstreamEdit time
Post‐editing
effort
 Probabilistic forecasts
• Based on automatic metrics
 Depending on
• Post‐editing level
• Volume
• Turn‐around time
Post-editing
levels
 Gisting
• Volatile content
– Automatic scripts to fix mechanical/recurring errors
 Light
• Continuous delivery
– Fixing capitalization and punctuation, replacing unknown
words, removing redundant words, ignoring stylistic
issues
 Full
• Publishing and engine training
– Fixing meaning distortion, fixing grammar and syntax,
translating untranslated terms (possibly new terms),
adjusting fluency
Vetting and
training editors
 Tests not applicable
• Dedicated or properly-filtered vendor base
– Previous experience
– Specific certifications
– Domain expertise
– Ability to follow instructions and style guides
– Ability to process linguistic data
 Specific training
• Specific engines
• Clients served
• Instructions
Dos
 Test before operating
 Provide MT samples for negotiation
 Negotiate throughput rates
 Provide glossary (with DNT words)
 Provide instructions
 Provide feedback forms
Don’ts
 Use MT to curb the pressure on prices
 Process poor MT outputs
 Treat post-editing as fuzzy matches
Post-editing
instructions
 Tool selection
 Environment setup
 General references
 Conventions
 Project details
 Pricing model
 Operating instructions
Pricing and
compensation
 Upstream
• Clear-cut predictive scheme
– No fuzzy match scheme
o Fuzzy match over 85% are inherently correct while MT segments may
contain errors and inaccuracies
 Downstream
• Measurement of actual work
Negotiation
grid
 Generals
• Engine
– Generic or trained
• Quality
– Raw output
– Expectations
• Formats and formatting
 Compensation
• Per-word rate
– Productivity rate
• Hourly rate
– Time tracking
Automatic
processing
 Empty and/or untranslated segments
 Duplications
 Punctuation, diacritics, extra spaces,
noise
 Numbers, dates, weights, measures
 Terminology
 Spellcheck
Automatic tasks
Pre-processing
 Segmentation
 Normalization
 Formatting
 Terminology
Post-processing
 Encoding
 Normalization
 Formatting (tag injection)
 Terminology

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Getting the Most from MT + PE