Volume
3, No. 3
July 1999 |
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Two German Books About Machine Translation
Reviewed by Alex Gross
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These slick, green paperbacks could not be more business-like in their
appearance.
They are clearly serious books intended to deal with serious issues. And
their twenty
assembled authors carry out this intent in an uncompromising fashion without
a hint
of the history behind their subject. And herein perhaps lies the chief fault
in these
competent but circumscribed volumes.
translators and translation companies... have tended to abandon Machine Translation in favor of Translation Memory. |
For almost fifty years, the promiseeven the certaintyof machine
translation
taking over from humans was a recurrent part of the grand computer dream,
merely
one component of an all-enveloping artificial intelligence destined to
organize our
menial tasks, our language problems, and even our daily driving. But during
the past
ten yearsor perhaps only the last fivethis dream has slowly receded, as
even MT
and AI experts have come to grasp the true scope of the problems they had
undertaken.
These two books can barely reflect this overwhelming realityperhaps the
closest
they come to mentioning it is the very first sentence of Volume I:
Machine Translation (MT) has, somewhat unexpectedly, made a
come-back during the 1990s.
What Series Editor Nico Weber most probably means here is that during this
period
MT developers finally gave up on trying to persuade translators to adopt
their
systems and seized the Internet and other publicity outlets to bypass
translators and
make an end run in favor of the uninformed general public. Defeated in their
original aims, they decided to proclaim total victory instead and rope in as
many
ordinary citizens as possible as hobbyist users. Which is not to say that MT
cannot
be integrated into small subsets of language, such as specific knowledge
domains,
parts catalogs, or predetermined questions and answersit may in fact work
best
here, though it is a far cry from the vast scope originally claimed for this
field.
Certainly translators have not been averse to working with computers during
this
periodthey have in fact been among the most avid users, scouring the Web
for all
manner of glossaries, editing tools, and translation aids. But to the extent
that
translators and translation companies have truly switched over to computer
techniques, they have tended to abandon Machine Translation in favor of
Translation Memory, an approach that bears about as much resemblance to MT
as
does a lexicon to a log table.
So essentially what we have in these two books is the account of a solemn
retreat
from MTs bygone days of would-be glory. The main topic of both volumes is
something called MT Evaluation, essentially a euphemism for trying to
discover
and explain why these systems have on the whole performed so poorly. The
entire
second volume is devoted to this topic, with two of the first volumes six
papers
sharing the same theme (and another two aimed in much the same direction).
This leaves only two papers dealing with other topics: one by Isabelle
Schrade on
cognitive aspects of translation, and another by Jürgen Rolshoven about
using
object-oriented programming to improve MT systems. The first is almost a
parody
of Chomskian acolyte Steven Pinkers Cognitive Neuroscience, encouraging
an
author to string profound bromides together almost endlessly, as is done
here.
Translation, Dr. Schrade tells us, embraces seven essential qualities (and
she
devotes a few pages to each of them): Memory, General Knowledge, Linguistic
Knowledge, Understanding and Analyzing, Recipient-Oriented Reformulation,
Human Intuition, and Creativity. As for Prof. Dr. Rolshoven, he treats us to
little
more than a tantalizingthough familiarexercise in Chomskian
diagram-juggling.
None of these criticisms is intended to deny the high seriousness of the
task being
undertaken nor of the authors sense of loyalty to their aims. The reader
watches in
awe as they painstakingly explain their quest for a valid methodology, one
that will
provide the surest and most scientific means of testing and comparing first
six and
later four different off-the-shelf MT systems.
But in what is already an enormous compromise, they decide that their tests
should
be based on a number of grammatical phenomena which are prominent for text
types which in turn are commonly considered typical MT text types (editors
italics). If only they could succeed in their quest, perhaps it might lead
to a small but
significant improvement in MT quality. After much discussion, seven types of
phenomena are proposed for testing, but only three are finally selected,
providing
perhaps some notion of the authors style and rigor:
Request forms, the editors term for typical imperative verb forms
found in computer and automotive documentation;
Compounds, comprising a vast array of noun-verb, verb-noun,
adjective-noun, and noun-noun composite words;
Coordination, their term for converting English ellipticisms into
more structured German forms.
The four categories rejected by the evaluators because of time constraints
were
participial constructions, adjuncts, nominalizations, and idiomatic
expressions.
But how valid are their testing procedures, and how likely are their
findings to reach
their goal? As the editors of the second volume confess in their final
summary,
testing the linguistic coverage of an MT system is a tedious,
time-consuming task.
And a note of unintended comic relief is provided by the one MT developer
invited
to take part, when he points out first of all that:
Methods for evaluating machine translations and machine translation
systems have been proposed, discussed, and applied for more than 40
years now, including numerous attempts at defining objectively
measurable criteria to capture aspects of translation quality.
Nevertheless, a worryingly large number of evaluation reports have
more or less explicit disclaimers as to the absolute value of the results,
or confess to flaws in the procedure.
and then draws the precise conclusion one might expect from an MT developer:
The obvious solution to these problems is of course to avoid
translation quality as a direct object for evaluations and to stay with a
general impression of the role which quality plays for the overall
acceptability of a MT system.
And there are other moments of unintended comic relief. For instance, the
abstract
for one paper tells us that the reason for these labor-intensive researches
is because
these systems require small-scale evaluation methods which can be carried
out
without the developers cooperation. And we learn that the advent of the
latest and
cheapest systems has spurred even the mighty Association for Machine
Translation
in the Americas to discuss a so-called MT Seal of Approval at their 1998
conference.
And amid all the precious examples of MT output, a few more fully certified
gems
emerge:
It is a pity that I cant speak French. becomes in German
Es ist franzözisch ein Mitleid, das ich nicht kann sprechen.
While The dog that had eaten the hamburger ran away. is truly
turned into hamburger:
Der Hamburger lief der Hund, der gefressen hatte, davon. (which in
English might become The man from Hamburg ran the dog...)
It is a relief to report after all these testing procedures, graphs, tables,
and countless
examples, that the editors do finally reach a conclusion about the six
principal
systems that have been evaluated. Based on their experiments, they determine
that
Logos, Personal Translator Plus 98 (Linguatec/IBM), and in many cases
Systran
belong to the top three. T1 Professional (Langenscheidt) is in the middle
field,
sometimes also Systran, and Transcend (Intergraph) and Power Translator Pro
(Globalink) always come last.
The first volume is almost entirely in English, while the second volume
weaves
quite seamlessly between German and English. In so doing the editors
inadvertently
show something of their own basic linguistic orientation by inventing two
new
English abbreviations (or at least new to this reviewer) on the basis of
familiar
German ones. Thus, in Volume 1 we find resp., no doubt a German stab at
respectively, presumably on the basis of German bzw., (beziehungsweise),
while
Volume 2 yields a.o., evidently an attempt to duplicate the German u.a.,
(unter
anderem) for among others. Both of these are certainly good tries and
perhaps
ought to exist in English, but they do raise certain doubts as to the
overall English
capabilities of the authors, especially when they confess that advanced
students of
English (all native German speakers) performed all the English post-editing
in one
task supposedly evaluating how long this should take.
This linguistic orientation is perhaps also revealed in the paper I find
most
interesting, the first volumes final offering: The Automatic Translation of
Idioms:
Machine Translation vs. Translation Memory Systems by Martin Volk. This
piece
comes down firmly on the side of Translation Memory as being superior to MT
for
translating idioms. But I question its basic dichotomy, that there is a
clear and
discernible difference between what we call idioms on the one hand and the
more
predictable parts of language on the other. I am not altogether sure that
this
dichotomy will stand up to any truly close analysis, particularly if we
begin to
consider more exotic languages, which even MT developers claim they will one
day
be able to include by using an Interlingual approach.
It might be supposed that this is merely a linguistic quibble, and that
surely what
appear to be simple sentences of the type You are beautiful must be much
the
same the world around. But I can easily conceive of languages and
culturesand I
believe many of our readers can as wellwhere the words You, are, and
even
beautiful might be up for grabs and pose unexpected problems even for
human
translatorsand certainly for machine translation systems as well. It could
yet turn
out that allor almost allof language is unpredictably and close to
arbitrarily
idiomatic in nature. And that only the coincidence of two languages, such as
English
and German or English and French, growing closely together over several
centuries,
has persuaded us that this may not be the case.
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