Two German Books About Machine Translation
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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.
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translators
and translation companies... have tended to
abandon “Machine Translation” in favor
of “Translation Memory.”
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For
almost fifty years, the promise—even the certainty—of
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 years—or perhaps only the last five—this
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 reality—perhaps 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 answers—it 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 period—they
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 MT’s
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 volume’s 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 Pinker’s “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 tantalizing—though familiar—exercise 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 can’t 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 volume’s 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 cultures—and I believe
many of our readers can as well—where the words
“You,” “are,” and even “beautiful”
might be up for grabs and pose unexpected problems even
for human translators—and certainly for machine
translation systems as well. It could yet turn out that
all—or almost all—of 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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