Machine Translation: Towards New Metaphors
1. Is Machine Translation possible?
The question whether Machine Translation (MT) is possible, is a
very delicate one for a researcher to answer. If the answer is
'yes' we need evidence that this is indeed the case, i.e. that
there are Machine Translation systems out in the world that can
produce adequate translations, or at least some sort of evidence
that this will be the case in the foreseeable future. If, on the
other hand, the answer is 'no', a large number of academic and
industrial researchers will have to justify the millions they
have spent over the last 40 years, and are still spending, on the
Let us first have a closer look at the answer, and then at the
1.1. The answer
Those who have ever been confronted with the unedited output of
an MT system, will easily admit that the result contained
errors, ranging from small, stylistic deviations, to an absolute
distortion of the meaning of the text in the best case and
absolute nonsense in the worst case. Some of the errors may look
rather superficial, and easy to repair in a next version of the
system (e.g. unknown words), but others might be much more
difficult to tackle.
Let us take the following two sentences (inspired by an example
from Jerry Hobbs) as our starting point:
(a) The policemen fired at the demonstrating students because
they FEARED violence.
(b) The policemen fired at the demonstrating students because
they WANTED revolution.
From a purely syntactic and lexical point of view the two
sentences are almost identical: the underlying syntactic
structure is the same, and the only real change is that 'feared'
in sentence (a) has been replaced by 'wanted' in sentence (b).
But there is a difference in interpretation, which goes further
than just changing the verb. In sentence (a) most native speakers
would interpret 'they' as to refer to the policemen, whereas in
sentence (b) 'they' refers to the demonstrating students.
The reason is obvious: we have a common understanding of the
roles of policemen and students in society (at least in our part
of the world), and there policemen are supposed to protect us
against dramatic changes in our way of living, such as
revolutions, whereas students have the reputation to be amongst
the first ones to adopt a critical attitude, and to advocate
No human translator would ever have any difficulty in assigning
the correct interpretation and translation to sentences (a) and
(b), whereas it is difficult to imagine how one could set up an
MT system in such a way that it would make the right choice here.
Linguistic knowledge, however deep, will not give any clue, and
the sort of knowledge that is needed, is very hard to encode and
apply in any systematic way.
Some may want to argue that there is no need for the MT system to
resolve the anaphoric ambiguity here, as e.g. translation into
French would not depend on the choice made here, but it is easy
to see that if we replace 'policemen' by 'police women' there is
no way to get around the problem.
The necessary conclusion is that however far we get in building
MT systems, we will never be able to guarantee that we get it
1.2. The question
Answering the question we asked above, turns out to bring us in a
slightly difficult position, so it might be wiser to ask
ourselves whether the question itself is a reasonable one to ask.
Traditionally, the objective of any MT effort has been to provide
a possibly perfect, cheaper and faster imitation of the human
translator. Success was measured on the basis of the extent to
which this simulation was successful, and as we all know, this
success has never been very impressive.
As an alternative way of looking at things, we can ask ourselves
whether the simulation of the human translator is a meaningful
purpose in itself. And the answer is a clear no. Although it may
be an interesting intellectual challenge, the ultimate goal of
any translation activity is to solve a communication problem,
where two parties who want to exchange information happen to
speak different languages.
From this point of view we can describe the purpose of an MT
system as a solution for a communication problem. This allows us
to define the notion 'success of a translation system' as the
degree to which the intended communication has been made
2. A new metaphor
We propose to adopt a new metaphor, instead of the human
translator, as the starting point for the construction and the
use of MT systems. Our metaphor is "the traveling tourist and
We all know from our travels abroad that communication in a
different language community poses problems, which can sometimes
be solved by one of the parties (e.g. one person decides to speak
the other person's language), or sometimes by cooperative
This leads us to the introduction of two types of tourists (or
guests) and hosts: adaptive and unadaptive. The adaptive party is
the party that accepts that communication across languages is
problematic, and makes a special effort to facilitate
communication. The unadaptive party is not prepared to
compromise, and insists on using his own language the way he
would do at home.
We can now make the following grid, based on the two parties'
adaptiveness, and investigate what sort of solutions MT or in a
broader sense language and speech technology could offer:
| adaptive host | adaptive host |
| adaptive guest | unadaptive guest |
| unadaptive host | unadaptive host |
| adaptive guest | unadaptive guest |
3. A war or a series of battles
The traveling tourist metaphor breaks down the MT problem into at
least four subproblems, the solution of which may require
different types of approaches and technologies. It may look less
elegant to have four different solutions to four different
instantiations of the MT problem, rather than one magic formula
that does all the work, but on the other hand one should realize
that just like in e.g. transportation (where airplanes are faster
than bikes, but more difficult to park in cities), in
communication every situation is different, and may have
different constraints and success criteria. Therefore, even
within the four boxes of the grid one may have to further
subdivide the problem into subproblems of a size and complexity
that we can manage.
The MT problem should not be seen as a single war, aimed at
solving the MT problem in one go, but rather as a series of local
battles, each of which should serve to reduce, in specific
situations, the communication problems caused by the fact that
people speak different languages.
3.1. The adaptive host and the adaptive guest
If both parties are equally adaptive, the chances to get the
communication problem solved, are by far the greatest. A typical
solution is for both parties to resort to a third language, known
by both. The use of English as a lingua franca in tourism,
international transportation and in science is a very well known
example. It is important to note that, although neither party may
have a perfect command of the foreign language, the communication
is normally successful, even if it may be less efficient than it
would have been between two native speakers of the language
(although even there no 100% guarantee for success can be given).
There is still a role for language and speech technology here,
such as language learning facilities, or electronic dictionaries
and foreign language authoring aids.
If none of the parties has a good command of the common language,
other facilities may come into play. An excellent example is
offered by the Verbmobil project, where a German and a Japanese
speaker use their own language to make meeting arrangements via
the phone, and where English is used as an interlingua to sort
3.2. The adaptive guest and the unadaptive host
This is a very normal situation for e.g. tourists who speak a
minority language, and who are traveling in a country where
either the native language belongs to the majority languages, or
where most people have received no foreign language education.
If the tourist has some managed to acquire some moderate
knowledge of the language, he might still be able to communicate
successfully, even if some of the details of the communication
may escape him. In such a situation a small electronic dictionary
might be of help. If the language gap is wider, more
sophisticated facilities are needed. An interesting example is
the DIPLOMAT system, designed to help UN soldiers in Bosnia to
communicate with the local population, which helps asking
questions in a foreign language, and translating the answers.
For electronic travel obvious (and already existing) facilities
are e.g. a translating browser (even if the translations are not
perfect, cf the way AltaVista makes use of the SYSTRAN
translation system), or an information extractor, which extracts
the key information from a foreign language text and presents it
in the user's own language.
3.3. The unadaptive guest and the adaptive host.
Typically this applies to situations where mass tourism moves
people who may have received no foreign language training to
places where they can enjoy sun, sea, food and drinks, and who
don't want to be confronted with the language barriers.
Hosts who want to please their guests have to be adaptive, e.g.
by learning their language, or by employing staff with the right
From a language and speech technology point of view, obvious
facilities to support this are the use of controlled languages in
authoring messages from host to guests (as long as the author
sticks to the rules, error-free translation can be guaranteed),
or by means of multilingual generation from tabular information
(e.g. generating weather or avalanche reports in various
languages from tables).
3.4. The unadaptive guest and the unadaptive host.
This is a fairly extreme situation, and it is clear that ideally
one would have to resort to either e human translator or
interpreter, or to Fully Automated High Quality Machine
Translation -- if only it existed.
As a long term research topic, this should certainly be kept high
on the agenda, together with the interpreting phone which would
ideally allow me to speak my own language over the phone, and to
be heard by my Japanese conversation partner as speaking fluent
Japanese, in my own voice.
For the shorter term the best option seems to be to develop tools
that increase the productivity of human translators, or the
quality of their output.
Typical examples are electronic term banks, on-line dictionaries
and thesauri, or translation memories.
4. Concluding remarks
First of all it should be clear that MT is not one single
simulation problem, but a complex of communication problems, each
of which may require a different approach and solution. Each of
the subproblems can (and even: should) be further subdivided.
The adaptivity grid we have presented here, can also help us in
raising new questions, such as "is there a tool for an adaptive
guest who wants to express himself in a foreign language unknown
to him?". Note that an affirmative answer to such a question will
not automatically imply that there will also be a market for the
In the spirit of the above, it may not come as a surprise that
for the future we would like to advocate the development of
domain dependent, goal dependent, and discourse dependent MT
facilities. In order to exploit the fact that these systems are
constrained, it is important that they should not only be based
on what we know about language (the rules, which express what we
understand), but also on what we know about how language is used
in specific communication contexts (i.e. statistical data which
we can measure and extrapolate from).