| | 
| Volume
3, No. 3 July 1999
 |  
 
  
 
 |  |  |  | 
  
 | 
  
 | |   
 |  |   
 
 
 |  
|  Two German Books About Machine Translation
Reviewed by Alex Gross |  | 
 
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. 
 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.|  translators and translation companies... have tended to abandon Machine Translation in favor of Translation Memory.  | 
 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.
 
 
 | 
 |