FORUM ON MACHINE TRANSLATION 
Machine Translation already does Work 
Margaret King 
ISSCO 
54, rte des Acacias 
CH-1227 Geneva, Switzerland 
PANELIST STATEMENT 
The first difficulty in answering a question like "Does 
machine translation work is that the question itself is ill- 
posed. It takes for granted that there is one single thing 
called machine translation and that everyone is agreed about 
what it is. But in fact, even a cursory glance at the systems 
already around, either in regular operational use or under 
development, will reveal a wide range of different types of 
systems. 
If we take first the dimension determined by who/what 
does most of the work, the machine or the translator or 
revisor, at one end of the scale are systems where the human 
does not intervene at all during the process of translation - 
"batch" systems for convenience here. Even amongst the 
batch systems there is considerable variety: the degree of 
pre-editing i~ermitted or required varies greatly, as does the 
amount of post-editing foreseen. Some systems insist that 
anything translated by the machine should require no post- 
editing, and thus (sometimes) reject as unsuitable for 
machine treatment a part of the text. Others take it for 
granted that machine translation will normaly be post-edited, 
just as human translation is normally revised. Some systems 
aim at giving nothing more than a very rough raw trans- 
lation, to be used by the human translator only as a starting 
point for producing his own translation. Some systems re- 
quire that the document to be translated conform to a 
restricted syntax, others leave the author relatively free. 
Next comes a class of systems that one might style 
"interactive" systems, where the bulk of the work is still 
done by the machine, but where the system interacts with a 
human to a greater or lesser degree. Such systems may ask 
the human, for example, to resolve an ambiguity in the 
source text, to choose between a set of target language 
terms, to decide on correct use of prepositions, or any com- 
bination of the-~e and other similar tasks. 
Shifting towards the end of the scale where the bulk of 
the work is done by a human translator aided by a computer 
system, there are. systems which will automatically insert 
identified technical terms, or replace a phrase occurring 
repeatedly in the text by its translation wherever it appears, 
leaving the rest of the translation to be done by the human 
translator, systems where the translator as he produces the 
translation can consult specialist or general dictionaries, ei- 
ther constructed by the translator himself for the particular 
needs of the text, or supplied by the system manufacturer. 
Many -indeed most- such systems are allied with clever text- 
processing systems specially designed for use by translators. 
Finally, although perhaps not strictly machine translation 
systems, but certainly of potentially great practical utility to 
the working translator, are independent packages, not neces- 
sarily integrated into a translator's work station type of en- 
vironment. These include automated terminology banks, dic- 
tionary look-up facilities, and general tools such as spelling or 
grammar checkers. 
In all this, I have quite deliberately omitted consideration 
of machine translation systems conceived of as primarily 
research tools, intended to test the validity of a particular 
theory or to experiment with some new proposal, since I take 
it that the worry lying behind the original question -and be- 
hind the moderator's statement- concerns systems which are 
in some way subject to external evaluation, and which can 
therefore lead to dissatisfaction. The status of research and 
experimental systems as valuable research tools seems quite 
uncontentious. 
Now, just as machine translation is not a single in- 
divisible whole, but rather a range of systems sharing only 
the common characteristic that they are used in one way or 
another in performing the task of translation, so the need for 
machine translation is different, depending on the particular 
characteristics of individual situations. 
Here, so many factors come into determining what the 
real need is that I shall not even attempt to give an exhaus- 
tive list, limiting myself instead to a handful of indicative, 
but necessarily over-simplified, examples. Take first the ex- 
ample of a large translation service, translating documents 
essentially very similar to one another, but in great volume 
and frequently at very short notice. This is the typical situa- 
tion in which what is needed is a batch service, producing 
reasonable quality translation which can if necessary be 
revised, where the degree of revision to be done depends on 
the use to which the translated document is to be put. (If the 
point of the document is to inform its readers in very general 
terms of what was discussed in a particuler meeeting, per- 
haps no revision at all is necessary, if it is to serve as the 
basis of discussion in a subsequent meeting, it may require 
quite a lot of revision, if it is to serve as the basis of a treaty 
or an agreement, it should never have been allowed near a 
machine translation system in the first place, and the trans- 
lation should be thrown away). In such a situation, an inter- 
active system, on the other hand, is likely to be unsuitable, 
since the main problem is the bulk of work to be done, and 
the translator or revisor is better occupied dealing with those 
documents unsuitable for machine treatment or revising 
where necessary than in sitting in front of a screen watching 
the machine at work. 
In a different situation, however, where what is required 
is very high quality translation, and where the volume of 
translation to be done is a less pressing problem, so that the 
main concern is in rationalising the translator's work whilst 
contingently increasing his productivity, an interactive sys- 
tem may prove to be the ideal choice, especially if the text 
type is a mixture of repetitive material which it is boring 
(and time-wasting) to translate manually each time it ap- 
pears and quite delicate text requiring great care. 
In yet another situation the major problem may be the 
typical length of documents, combined with a need for speed 
and a need for terminological accuracy, so that a single docu- 
ment is split over a number of translators working indepen- 
dently, but all must use the same translation for certain 
terms. Here, the ideal system might well be simply to provide 
all the translators with access to a clever text-processor from 
within which they could access easily a common term bank, 
with all the rest being left to the translator. 
There is no need to labour the point: different set-ups 
have different problems to solve, and therefore, whether they 
know it or not, need different kinds of machine translation 
systems. 
Now we can return to the original question: machine 
translation works when the machine translation system is 
able to resolve in a significant measure the particuler trans- 
269 
lation problems in a particular situation. To put this more 
crudely, no-one should try to persuade the translator of 
Faust that a batch trunslation system will do him any good 
at all, and no-one should try to persuade the translation ser- 
vice that churns out several hundred invitations to meetings 
every day that an automated dictionary look-up facility will 
solve their problems. 
Once this is realized, the puzzle contained in people as- 
king questions like whether it is a good idea to work on 
machine translation in a world where it is demonstrably the 
case that machine translation systems exist and are counted 
satisfactory by their users begins to go away. The succesful 
systems are those where what is provided by the system 
matches what is required to solve the real problem, where 
the system developers realistically assessed what they could 
offer, went ahead and provided that, and where those who 
commissioned the construction or purchase of a system had 
expectations matched by what was actually delivered. 
A final question to those who claim that it is somehow 
dangerous or irresponsible to promise to produce a machine 
translation system. If one promises and fails (apart of course 
from the general principle that one should always try to fulfil 
one's promises and not to promise what one cannot deliver), 
why is that more damaging to the field than working on 
speech-recognition and failing? 
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