The ATA Chronicle - January/February 2021 - 31

RR
that I could gain a better
understanding and then
make things a bit better.

about your projects first
before moving on.
Samuel, let's start with

the fact that these features
are not yet available to
professional translators. "

Meet the
Interviewees

you. In the Routledge

Nico

I studied computer
science and am

Handbook of Translation
and Technology4, you co-

Naturally, we would all
be interested in finding out
who's to blame, but also
whether you see widespread
changes in a number of
translation environments on
the immediate or mid-term
horizon. If so, what kind of
changes, and will they be easily
embraced by translators?

currently working at the

authored a chapter with

German Research Center for

Spence Green, co-founder

Artificial Intelligence (DFKI)

of Lilt, where you looked at

in Saarbrücken, Germany. I

the aforementioned human-

spend most of my time on the

computer interaction and

Multi-Modal Post-Editing of

evaluated a number of

Machine Translation (MMPE)

different ways to interact

project, which is funded by the

with the suggestions MT

German Research Foundation.

provides. This resulted

Within the project, which is

in highlighting the need

also the primary focus of my

for adaptive MT systems.

PhD, we investigate a broad

Another finding seemed

produce so many inadequate

range of explicit input

to be that translators had

suggestions. Even exact

modalities like handwriting or

a difficult time adopting a

matches often aren't too

speech input to simplify the

new working environment.

exact. Think about linguistic

post-editing process.

Correct me if I'm wrong

properties that are implicit

However, we also look at

on that.

(or undefined) in the source

multi-modal implicit input,

Just a few weeks ago you

Samuel

When you think
about it, TMs

but explicit in the target

such as measuring pupil

gave a talk that, according

language, such as choosing

diameter or skin conductance

to the description below,

the appropriate pronoun

to estimate cognitive load

covered the following:

forms for informal and polite

during post-editing. As this
topic is at the intersection of
human-computer interaction
and language technologies, we
work in tight collaboration
with research departments
lead by Antonio Krüger, chief
executive officer of the DFKI
and scientific director of the
cognitive assistants
department, and Josef van
Genabith, scientific director of
the multilinguality and
language technology
department. To retrieve
input from domain experts,
we ran our studies with
professional translators in a
user-centric approach.

Jost

I think talking to
both of you is

turning out to be an even
better match than I originally
thought! Maybe I can drill a
little deeper with each of you
www.ata-chronicle.online

address when translating

" Having faced tremendous
resistance throughout the
late 1990s and early 2000s,
translation memories (TMs) are
now considered indispensable
productivity tools for
professional translators. TMs
are great at providing (partial)
translation suggestions in
the form of fuzzy or exact
matches, but CAT tools are
currently not too creative in
utilizing these matches: they
just display them to the user.
In this talk, we take a look at
how machine translation (MT)
technology can ingest fuzzy
matches to generate better
and more domain-specific
translation suggestions, or
transform exact matches to
comply with context-dependent
linguistic requirements in the
target language. We also
discuss who's to blame about

from English into German.

Samuel Läubli

Studied computational
linguistics in Zurich, graduated
in 2014 with a master's from
the University of Edinburgh in
artificial intelligence
Received a job offer from
an American software
company to train domainspecific MT systems
Worked for two years
before moving back into the
research field

For example, " you " will be
translated as either " Sie "
(formal) or " du " (informal).

Nico Herbig

But an exact match for " You
can win fantastic prizes " that
results in " Gewinnen Sie
fantastische Preise " ( " Win you
fantastic prizes " ) on the
target side really isn't that
great in an informal context.
Since the level of politeness
can be controlled5 within,

Studied computer science

and partial translations
incorporated into, neural
machine translation (NMT)6,
these " exact matches " could
be adjusted automatically.
However, the NMT system
will need an indication of the
desired level of politeness to
adjust the match.
Since most CAT tools don't
integrate but merely connect
to MT systems, they only

Currently working at the
German Research Center
for Artificial Intelligence in
Saarbrücken, Germany
Investigates multi-modal
input (speech, handwriting,
touch, etc.) for post-editing
machine translation

American Translators Association

31
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