Although many companies have found MT inevitable, the threshold of its implementation into professional translation process remains high. Customization of MT requires time, budgets and considerable amount of translation memory databases. The choice and integration of different MT systems into professional translation process is also challenging. So what should we aim for when introducing MT to our existing working environment? This presentation focuses on the means of continuous MT customization via TM and glossaries updated in real time. Anton discusses the ways of how to approach MT engines training, touches upon the practices of measuring the productivity of translators and sees what can be done when there is no large TM corpus to customize the MT system.

1. THURSDAY,
22
May
/15:00
–
15:30
Machine
Transla>on
in
Professional
Transla>on
Process:
Con>nuous
Customiza>on
and
Measured
Produc>vity
Anton
Voronov,
ABBYY
Language
Services
TAUS
ROUNDTABLE
2014
22
May/
Moscow
(Russia)

2. Challenge
accepted
• The
amount
of
content
generated
almost
doubles
annually
• Transla>on
speed
and
number
of
translators
are
more
or
less
constant
Main
tools
to
increase
produc>vity
• Dic>onaries,
glossaries
• Transla>on
memory
• Machine
transla>on
• Crowdsourcing
Machine
transla>on
• Increases
transla>on
speed
• Enables
new
types
of
content
to
be
translated

3. Machine
transla>on
Precondi>ons
• Big
projects,
>ght
deadlines
• New,
less
visible
types
of
content
• Well
structured
texts
with
high
repe>>on
rates
• Combined
processes
with
flexible
quality
requirements
(e.g.
crowdsourcing)
Requirements
• Considerable
volume
of
transla>on
memory
• Customiza>on
of
MT
engines
• Proper
choice
of
an
MT
system
• Deep
integra>on
of
MT
systems
into
professional
transla>on
process

4. The
Process
• Extract
and
translate
terminology;
• Use
linguis>c
assets
both
for
MT
customiza>on
and
transla>on;
• Evaluate
MT
engines
and
select
the
best
one
for
each
par>cular
text;
• Retrain
the
engine
based
on
process
results
(dynamically);
• Control
MT
quality
(dynamically);
• Decide
which
(MT
or
TM)
is
the
be]er
op>on
for
each
par>cular
segment
based
on
metrics
and
terminology
(dynamically);
• Control
and
improve
overall
quality
(dynamically);
• Measure
all
the
parameters
both
to
es>mate
your
PE
rate
and
further
tune
the
process;
• Have
a
pla^orm
which
will
allow
you
to
do
all
this
automa>cally.

5. Transla>on
workflow
automa>on
• Integrated
terminology
management
process
• Web-­‐based
CAT
tool
• Integrated
MT
engines
• Agile
workflow
automa>on
• Simultaneous
mul>-­‐user
collabora>on
on
the
same
document
• Automated
logging
of
every
post-­‐edi>ng
ac>on
and
its
>me
• Built-­‐in
QA
In
our
case
all
this
is
done
in
ABBYY
SmartCAT,
a
unified
cloud
environment
for
professional
transla>on
automa>on.

6. Engine
retraining
Terminology
• Extract
• Improve
• Retrain
Reuse
of
translated
and
post-­‐edited
segments
• Use
your
post-­‐edited
segments
as
soon
as
possible
• The
content
translated
now
is
more
relevant

7. Dynamic
selec>on
of
assets
Dynamic
engine
selec>on
• Personal
preferences
• Edi>ng
effort
and
produc>vity
parameters
at
all
stages
Dynamic
MT
/
TM
selec>on
• Match
percentage
• Terminology
consistency
• Personal
preferences

8. Quality
Dynamic
selec>on
of
segments
for
quality
control
• Edi>ng
history
• Time
spent
• Automa>c
QA
results
Dynamic
selec>on
of
process
stages
• Adjust
your
process
based
on
sta>s>cs
and
confidence

9. Our
plans
• Integrated
term
extrac>on
and
sugges>on
• Adding
more
context
informa>on
• More
QA
checks
• Deeper
integra>on
of
more
metrics
into
the
process