Life was given to us a
billion years ago. During that time we have gradually developed a great set of
abilities, knowledge and skills that allow us to identify ourselves as human
beings. We can feel, think, create, but overall we can express what is in our
minds thanks to language, which is without a doubt the watershed that placed
humanity on a distinct level from the rest of the animal kingdom, since as far
as we know, we are the only ones capable of sharing our life experience by
means of graphic and phonetic linguistic codes.
Sometimes I lose
myself thinking on all the events and circumstances that took place in order
for humans to develop a more or less fixed system that has been transmitted
from one generation to another, and acquired since a very early age as if it
did not represent any difficulty whatsoever. We arrive to this world and become
speakers of a language only through biological predisposition, even if we have
not had any kind of formal instruction. At least for me, that is the most
evident proof of evolution.
However, that
evolutionary process has not been fast one. Many years went by before we came
up with the ability of producing sounds, then understanding each other through
a specific language, then creating a system to represent it graphically, then
coining a set of rules to govern it, and finally putting together a
technological platform that allowed us to be connected with the rest of the
world whenever and wherever we were using written and spoken language as our
major tools.
More recently the
focus has been even more ambitious. Since the mid-20th century, many
linguists and computer scientist have worked together to create the major
wrecking ball that would bring down all language barriers. The dream of a
software capable of translating and even interpreting any form of human
language instantaneously, is an unprecedented project that aims to take over
one of the world’s most ancient professions, with the promise of creating an
intelligible global society that might no longer need a lingua franca.
Nonetheless, the
journey has just started. Despite the fact that we count with technological
enhancements capable of literally moving mountains, it is still very soon to
assure that a computer could be capable of processing language and information just
like a bilingual person would. I have to say that I personally agree with the
stated by Crystal (2003) when saying that machines are still far from reaching
a human-like condition that could carry out the sometimes underestimated task
of translation, as good as we do. From a simplistic perspective, machine translation
only deals with converting a word in one language to another; thus, most people
would probably say: what’s the big problem
then? You grab a bilingual dictionary
and write all the words in it on a computer and voilà, there you have your machine translator. Wrong. Although during
the last decades we have already overcame this obstacle and nowadays we count
with several online dictionaries that are rapidly replacing paper dictionaries;
the unachieved purpose of the still non-existent Fully Automatic High Quality
Machine Translation (FAHQMT) is not only to translate from one language to
another, but to translate complete context-dependent discourses.
I have to admit that online
dictionaries have been a great help for computer-aided translation, and for
those who find themselves in the need of a fast and free translation,
regardless of its lack of accuracy and feasibility. However, the authentic machine translator capable
of translating long texts without any human help, must be able to overcome the
following obstacles before singing our praises.
Disambiguation and
Lexicon
There are countless words in all languages that have
more than one meaning (polysemy). The
problem here is how to explain a computer that ball could be both a round object to play with and a huge dance. Relying
only on statistical word-use without an Interlingua system or some kind of universal encyclopedia is not enough to
process those differences (Bar-Hillel, 1960). Also, other issues regarding
lexicon are the dialectal use and meaning of words, (e.g. how shitty = que cagado {Northern Mexican Spanish}
that’s funny (inf.) = que cagado
{Central Mexican Spanish} as well as cultural concepts in one language that
need a longer description to be fully explained in a foreign language (e.g.
Fremdscham {GER} = Embarrassment felt on behalf of someone else {ENG} = Pena
Ajena {SPA}.
Register
Translation software is normally not so good when it
comes to translate informal or non-standard language uses. Therefore, all those
texts that are written or said in slang or
uncommon dialects, are almost impossible to be translated accurately.
Ontology and Syntax
Ontologies are formal representation of knowledge
which includes concepts in a domain and the relations between them (Vossen,
2003). Most of time we as humans are aware of this relations because we can
rely on the context or situation in which the utterance occurs. For instance, I saw a friend with my glasses, could
mean that you saw your friend wearing
your sunglasses or that you saw him because
you were wearing your glasses.
Morphology
Depending on the language you are translating into,
it is very likely that there will be problems with inflection, derivation, number, compounds, gender, etc.
Based on these
unsolved problems with machine translation, the notion of having a completely
independent translation software capable of translating whatever input you give
it, starts to seem a little distant. Therefore, it might be more feasible to
continue spreading the English as language as an international vehicle for
communication, instead of sitting around waiting for a still utopic software
that would make our lives a lot easier.
Now, in a hypothetic
future in which FAHQMT is available, many scenarios are possible. Honestly, I
would like to live long enough to experience a software that could translate with
the same accuracy that a bilingual/bicultural professional translator would. If
this happens any time soon, there are many factors that will have to be
addressed.
Cost
I have heard many
people who think that translation is an expensive service. Most translators
charge either by page or by word, which might seem expensive when we are
talking about a book or a scientific paper. However, most clients do not see that
each translation each different is complexity and therefore on the time the
translator spends working on it. If we had FAHQMT would it be cheaper to buy
the complete software to translate some texts sporadically, or would it still
be better to pay the old-fashioned human translator to do the work?
Time
The proto-translators to which we have free access
online do the work mostly wrong, but instantaneously. It is hard to hypothesize
if the idyllic error-free Machine Translator, would be able to carry out the
same work a human does in less time. Do you know how long does it take for a 3D
Printer to create a small scale model building? Not less than 8 hours… Quality
Here we go again. Before we can say that the quality
of both human and machine translation is alike, many years and different kinds
of evaluations will go by. Linguists overall are the ones who need to work the
most in order to assure future clients that weather they choose a machine or
human translator the results will be an accurate, feasible, grammatical,
coherent, meaningful and so on.
Domains
There are some
proto-machine translator software today that is mainly bought by big companies
to translate from one language to another in only one specific domain. The same
is true for human translators. There are many specialized translators who have
a specific training in one fields such as law, medicine, literature, etc. The
question here is if a machine translator could translate whatever you give it
regardless of the domain.
Working languages
There are at least 6,000 language in the world.
However, only around 30 are the ones that are normally required for
translation. How possible could it be that a single translation software could
have all those codes in it?
Need of a Bridge Language
Crystal
(2003) also suggests that the
presence of a global language might eliminate the demand for world translation
services, or that the economics of automatic translation will weaken the cost
of global language learning that the latter will become useless. I personally
think that if we had a function translation software, the need of a bridge
language would not fade away. English is today’s lingua franca as French and Latin once were; however, due to the
social inequality when it comes to education, it is very unlikely that English
could be one day written, read, spoken and understood by the whole world’s
population. The way I see it language learning will never be outdated. After
the United States ceases to be most powerful nation, another country will take
over along with its language. And even if we could go around the world using
our iPhone as an interpreter to and from any language, it will just not be as
practical, as actually speaking it.
References
Bar-Hillil,
Y. (1960). The present status of automatic translation of languages. Advances
in Computers, 1(1), 91-163. Retrieved form http://www.mt-archive.info/Bar-Hillel-1960.pdf
Vossen, Piek: Ontologies. (2003). In
Mitkov, Ruslan (ed.) Handbook of
Computational Linguistics. Oxford: Oxford University Press.
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