Here you can see the difference between: machine translation, machine
aided translation (aka Computer-assisted translation) and translation
technology (aka Translation)

Machine translation, sometimes referred to by the abbreviation
MT, is a sub-field of computational linguistics that investigates
the use of computer software to translate text or speech from one
natural language to another. At its basic level, MT performs
simple substitution of words in one natural language for words
in another. Using corpus techniques, more complex translations
may be attempted, allowing for better handling of differences in
linguistic typology, phrase recognition, and translation of idioms,
as well as the isolation of anomalies.
Current machine translation software often allows for customisation
by domain or profession (such as weather reports) — improving
output by limiting the scope of allowable substitutions. This technique
is particularly effective in domains where formal or formulaic
language is used. It follows then that machine translation of
government and legal documents more readily produces usable output
than conversation or less standardised text.

Computer-assisted translation,computer-aided translation, or
CAT is a form of translation wherein a human translator translates
texts using computer software designed to support and facilitate the
translation process.
Computer-assisted translation is sometimes called machine-assisted,
or machine-aided.

Translation is the action of interpretation of the meaning of a text,
and subsequent production of an equivalent text, also called a translation,
that communicates the same message in another language. The text to be
translated is called the source text, and the language it is to be translated
into is called the target language; the final product is sometimes called the
“target text.”
Translation must take into account constraints that include context, the rules
of grammar of the two languages, their writing conventions, and their idioms.
A common misconception is that there exists a simple word-for-word
correspondence between any two languages, and that translation is a
straightforward mechanical process. A word-for-word translation does not
take into account context, grammar, conventions, and idioms.

Reference page

We have the same text taken from HERE, in
spanish, in five different languages:

SPANISH

Serie sobre un antipático médico especializado en
enfermedades infecciosas. Gregory House es,
seguramente, el mejor medico del Hospital, pero su
carácter, rebeldía y su honestidad con los pacientes
y su equipo le hacen único. Prefiere evitar el contacto
directo con los pacientes, le interesa por encima de todo
la investigación de las enfermedades. Además de no
cumplir las normas, se niega a ponerse la bata de médico.
Es adicto a los calmantes y a las series de hospitales,
¿contradictorio? No, es House.

ENGLISH

Series on a unpleasant doctor specialized in infectious
diseases. Gregory House is, surely, the best medico of
the Hospital, but their character, revolt and its honesty
with the patients and their equipment him make only. It
prefers to avoid the direct bonding with the patients,
interests to him over all the investigation of the diseases.
In addition to not fulfilling the norms, one refuses to put
the doctor dressing gown. He is addict to the tranquilizers
and the series of hospitals, contradictory? No, it is House.

FRENCH

Une série sur un médecin antipathique spécialisé en
maladies infectieuses. Gregory House est, sûrement,
le meilleur médecin de l’Hôpital, mais son caractère,
une révolte et son honnêteté avec les patients et ils(elles)
lui font son équipe(équipement) unique. Il(elle) préfère
éviter le contact direct avec les patients, l’investigation
des maladies lui intéresse au-dessus de tout. En plus de ne
pas accomplir les normes, il(elle) se refuse à mettre la robe
de chambre de médecin. Il est fidèle aux calmants et aux
séries d’hôpitaux: contradictoire ? Non, c’est House.

CATALAN

Sèrie sobre un antipàtic metge especialitzat en
malalties infeccioses. Gregory House és,
segurament, el millor medico de l’Hospital, però el seu
caràcter, rebel·lia i la seva honestedat amb els pacients
i el seu equip li fan únic. Prefereix evitar el contacte
directe amb els pacients, li interessa per damunt de tot
la investigació de les malalties. A més de no
complir les normes, es nega a posar-se la bata de metge.
És addicte als calmants i a les sèries d’hospitals,
contradictori? No, és House.

GERMAN

Reihe auf einem unangenehmen Doktor spezialisierte sich
auf ansteckende Krankheiten. Gregory Haus ist sicher der
beste Doktor des Krankenhauses, aber ihr Buchstabe,
Aufruhr und seine Ehrlichkeit mit den Patienten und ihren
Geräten, die er nur herstellt. Es zieht es vor, das direkte
Abbinden mit den Patienten, Interessen zu ihm zu vermeiden
überschuß die ganze Untersuchung der Krankheiten. Zusätzlich
zur Erfüllung nicht der Normen, lehnt man ab, den Doktor
Hausmantel zu setzen. Er ist Süchtiger zu den Beruhigungsmitteln
und zur Reihe der Krankenhäuser, unvereinbar? Nr., ist es Haus.

The Framework for Machine Translation Evaluation
in ISLE is a resource that helps MT evaluators define
contextual evaluation plans. FEMTI consists of two
interrelated classifications or taxonomies: the first one
lists possible characteristics of the contexts of use that
are applicable to MT systems. The second one lists the
possible characteristics of an MT system, along with the
metrics that were proposed to measure them.

Evaluators using FEMTI specify the intended context of use
for an MT system using the first classification, and submit it
to FEMTI. In return, FEMTI proposes a set of quality
characteristics that are relevant to that context, using its
embedded knowledge base. Evaluators can modify this set of
quality characteristics and select evaluation metrics for each
of them, by browsing the second classification. Evaluators can
then print the evaluation plan and execute the evaluation.

The main characteristics of the translation task are:

• Assimilation: The ultimate purpose of the assimilation task
  (of which translation forms a part) is to monitor a (relatively)
  large volume of texts produced by people outside the
  organization, in (usually) several languages.
• Dissemination: The ultimate purpose of dissemination is to
  deliver to others a translation of documents produced inside
  the organization.
• Communication: The ultimate purpose of the communication
  task is to support multi-turn dialogues between people who speak
  different languages. The translation quality must be high enough
  for painless conversation, despite possible syntactically ill-formed
  input and idiosyncratic word and format usage.

Reference page

Artificial intelligence (also known as AI) is the intelligence of
machines and the branch of comuter science that aims to
create it. Most of textbooks which talk about AI define it as
“the study and design of intelligent agents“; where an intelligent
agent is a system that perceives the enviroment which is
around it and takes actions that maximize its chances of
success. Artificial Intelligence can be understood as a realization
of an abstract intelligent agent (AIA) wich exhibits the functional
essence of intelligence. Another definition of AI by John
McCarthy is “the science and engineering of making intelligent
machines.“

AI research uses tools and insights from many fields, including,
for instance, computer science, psychology, linguistics, ontology,
economics or logic. Artificial Intelligence research also overlaps
with tasks such as robotics, control systems, logistics, speech or
facial recognition and many others. Among the other names
proposed for the field we have computational intelligence.

In fact, computational intelligence (aka CI) is a successor of
artificial intelligence. It combines elements of learning, adaptation,
evolution and Fuzzy logic to create programs which are, in some
sense, intelligent. CI research does not reject statistical methods,
but often gives a complementary view (that is the case of fuzzy
systems). Artificial neural networks is a branch of computational
intelligence that is closely related to machine learning. Computational
intelligence is further closely associated with soft computing,
connectionist systems and cybernetics.

Reference page

Natural language is only one medium for human-machine interaction, but has several obvious and desirable properties:

1. It provides an immediate vocabulary for talking about the contents of the computer.
2. It provides a means of accessing information in the computer independently of its structure and encodings.
3. It shields the user from the formal access language of the underlying system.
4. It is available with a minimum of training.

Natural Language Processing (NLP) is both a modern computational technology and a method of investigating and evaluating claims about human language itself.

Natural Language Processing (NLP) is the use of computers to process written and spoken language for some practical, useful, purpose: to translate languages, to get information from the web on text data banks so as to answer questions, to carry on conversations with machines, so as to get advice about, say, pensions and so on. These are only examples of major types of NLP, and there is also a huge range of lesser but interesting applications, e.g. getting a computer to decide if one newspaper story has been rewritten from another or not. NLP is not simply applications but the core technical methods and theories that the major tasks above divide up into, such as Machine Learning techniques, which is automating the construction and adaptation of machine dictionaries, modeling human agents’ beliefs and desires etc. This last is closer to Artificial Intelligence, and is an essential component of NLP if computers are to engage in realistic conversations: they must, like us, have an internal model of the humans they converse with.

Reference Page.

Hans Uszkoreit is Professor of Computational Linguistics at Saarland University. At the same time he serves as Scientific Director at the German Research Center for Artificial Intelligence (DFKI) where he heads the DFKI Language Technology Lab. By cooptation he is also Professor of the Computer Science Department.

Uszkoreit studied Linguistics and Computer Science at the Technical University of Berlin and the University of Texas at Austin. During his time in Austin he also worked as a research associate in a large machine translation project at the Linguistics Research Center. In 1984 Uszkoreit received his Ph.D. in linguistics from the University of Texas.

Since 1982 he has been working in many Centers and Institutions related to his studies, for instance: the Artificial Intelligence Center of SRI International in Menlo Park; or at the Language Technology Lab at DFKI.

Furthermore, he is an important member of many Academies, and he serves on several international editorial and advisory boards.

His current ressearch interests are computer models of natural language understanding and production, advanced applications of language and knowledge technologies such as semantic information systems, cognitive foundations of language and knowledge, grammar formalisms and their implementation, syntax and semantics of natural language and the grammar of German.

Reference Page.

A natural language (or ordinary language) is a language that is spoken, written, or signed by humans for general purpose communication, as distinguished from formal languages (such as computer-programming languages or the “languages” used in the study of formal logic, especially mathematical logic) and from constructed languages. Though the exact definition is debatable, natural language is often contrasted with artificial or constructed languages such as Esperanto, Latino Sexione, and Occidental.

Language technology is a multidisciplinary field, which studies technical means and methods that can be used to process natural language with computers.

The capabilities of human language technology (HLT) have grown substantially in recent years, both in the research laboratory and in the commercial marketplace. There is now a wide range of applications for HLT systems such as automatic transcription of meetings, translation between languages (e.g. Arabic and English), automatic answering of questions, text mining (e.g. from the web) and access to information through spoken human-computer dialogue. Systems which use HLT are now in everyday use, through technologies such as internet search engines and mobile phones, and most major international computer and telecoms companies now engage in HLT research and development. As a result, there is strong demand for graduates with the highly-specialised multi-disciplinary skills that are required in HLT, both as practitioners in the development of HLT applications and as researchers into the advanced capabilities required for next-generation HLT systems.

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La escritura es un sistema de representación gráfica de una lengua, por medio de signos grabados o dibujados sobre un soporte. Es un método de intercomunicación humana que se realiza por medio de signos visuales que constituyen un sistema. La escritura ha evolucionado a través del tiempo. Fundamentalmente ha sido de dos maneras:

En cuanto a los hipermedios, primero debemos definir el concepto de “medios” (media en inglés) y después el de “hipertexto”. Pues bien, “media” es la más básica tecnología de comunicación y almacenamiento de información, incluye a los lenguajes humanos como la música, la pintura y el cine. Hipertexto es un término usado para indicar las conexiones entre los documentos de naturaleza textual e hipermedios se refiere a la conexión entre los documentos de diversos tipos de medios [Dale, 1997]. El texto, los gráficos, el audio y el video pueden ahora estar en vivo de forma unificada, respondiendo a las nuevas necesidades que tenemos con las diferentes formas de expresar la información [Nelson, 1987].

REFERENCIAS:

• Oralidad. Wikipedia. La enciclopedia libre. Fecha de consulta: 2-12-2007 http://es.wikipedia.org/wiki/Oralidad
• Escritura. Wikipedia. La enciclopedia libre. Fecha de consulta: 2-12-2007 http://es.wikipedia.org/wiki/Escritura_%28ling%C3%BC%C3%ADstica%29
• Hipermedia. Wikipedia. La enciclopedia libre. Fecha de consulta: 3-12-2007 http://es.wikipedia.org/wiki/Hipermedios
• Obras de Ong y Havelock. Revista de estudios literarios de la Universidad Complutense de Madrid. Autora:Ana Calvo Revilla. Fecha de redacción:1999. Fecha de consulta: 5-12-2007 http://www.ucm.es/info/especulo/numero13/zumthor.html

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