a) historical aspects: oralvs. written vs. mechanical
significance / historical role of TR - contribution to & impact on:
development an growth of human culture (trade, preachers, military exchanges, diplomatic affairs, transfer of artefacts)
b) TYPES: literaryvs.non-literary
c) METHODS of ORAL TR: simultaneous vs. consecutive
d) FORM: oral (always non-literary) vs. written
e) medium in which TR is performed:
mechanical & computer-aidedvs.human
The role of the Translator
TLR as a linguistic person (knowledge, spatio-temporal restrictions)
Sender, TLR, Receiver as linguistic persons in the communicative act
TLR as a linguistic person in the communicative act:
change as much as necessary - BUT –
as little as possible
MECHANICAL / MACHINE TR (MT)
always written and non-literary
50's & 60's – cold war (US/Russia)
computer - programmed to decode (SL) & encode (TL) !!!?
equivalence between SL and TL (one-to-one correspondence)
1980-ies: initial success and promises (large investments - projects)
human TLR - more efficient
Machine translation (MT) – Wikip.
a procedure whereby a computer program analyses a source text and produces a target text without further human intervention.
however, machine translation typically does involve human intervention, in the form of pre-editing and post-editing
an exception to that rule:
e.g., the translation of technical specifications (strings of technical terms and adjectives), using a dictionary-based machine-translation system.
In regard to texts (e.g., weather reports) with limited ranges of vocabulary and simple sentence structure, machine translation can deliver results that do not require much human intervention to be useful.
Also, the use of a controlled language, combined with a machine-translation tool, will typically generate largely comprehensible translations (AirSpeak)
Relying on machine translation exclusively ignores the fact that
communication in human language is context-embedded and that
it takes a person to comprehend the context of the original text with a reasonable degree of probability.
even purely human-generated translations are prone to error.
such translations must be reviewed and edited by a human
To date, machine translation — a major goal of natural-language processing — has met with limited success. 
Machine translation has been brought to a large public by tools available on the Internet, such as AltaVista's Babel Fish, Babylon, and StarDict, Systran, Trados. These tools produce a "gisting translation" — a rough translation that "gives the gist" of the source text.
With proper terminology work, with preparation of the source text for machine translation (pre-editing), and with re-working of the machine translation by a professional human translator (post-editing), commercial machine-translation tools can produce useful results, especially if the machine-translation system is integrated with a translation-memory or globalization-management system. 
Machine translation (MT)
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 (filters: field, subject matter)
Current machine translation software often allows for customisation by profession (such as weather reports) — improving output by limiting the scope of allowable substitutions.
particularly effective in domains where formal or formulaic language is used
i.e. machine translation of government and legal documents more readily produces usable output than conversation or less standardised text
MT - HAMT
Improved output quality can also be achieved by human intervention:
E.g. some systems are able to translate more accurately if the user has unambiguously identified which words in the text are names.
With the assistance of these techniques, MT has proven useful as a tool to assist human translators, and in some cases can even produce output that can be used "as is".
However, current systems are unable to produce output of the same quality as a human translator, particularly where the text to be translated uses casual language
FAILURE of MT (?)
computers are not human beings - THE NATURE OF TR. (AND HUMAN LANGUAGE) IS NOT AN ALGORITHMIC PROCESS:, esp.:
1. polysemy - on the lexical level
2. connotations, pragmatics etc. (siječanj - januar)
3. unable to account for changes in word order (syntax)
90's - in spite of taggers and parsers & semantic programs/ MT (translators) (whole blocks of language - now algorithmically available for TR
the intellectual activity of facilitating oral and sign-language communication, either simultaneously or consecutively, between two, or among three or more, speakers who neither speak nor sign the same source language.
Functionally, interpreting and interpretation are the descriptive words for the activity;
Functionally, an interpreter orally translates a source language to a target language; likewise in sign language
The interpreter's function is conveying every semantic element (tone and register) and every intention and feeling of the message that the source-language speaker is directing to the target-language listeners
Computer-assisted translation (CAT), also called computer-aided translation or machine-aided human translation (MAHT), is a form of translation wherein a human translator creates a target text with the assistance of a computer program. The machine supports a human translator.
Computer-assisted translation can include standard dictionary and grammar software. The term, however, normally refers to a range of specialized programs available to the translator, including translation-memory, terminology-management, concordance, and alignment programs.
Types of CAT - General
Computers are used in many aspects of modern translation (particularly of technical texts).
the translation or interpretation of non-specific language that does not require any specialized vocabulary or knowledge
However, the best translators and interpreters read extensively in order to be up-to-date with current events and trends so that they are able to do their work to the best of their ability, having knowledge of what they might be asked to convert
good translators and interpreters make an effort to read about whatever topic they are currently working on
Specialized translation or interpretation
refers to domains which require at the very least that the person be extremely well read in the domain.
training in the field (such as a college degree in the subject, or a specialized course in that type of translation or interpretation)
common types of specialized translation:
financial translation and interpretation
legal translation and interpretation
medical translation and interpretation
scientific translation and interpretation
technical translation and interpretation
Translating for legal equivalence
For legal and official purposes, evidentiary documents and other official documentation are usually required in the official language(s) of that jurisdiction. In some countries, it is a requirement for translations of such documents that a translator swear an oath to attest that it is the legal equivalent of the source text. Often, only translators of a special class are authorized to swear such oaths. In some cases, the translation is only accepted as a legal equivalent if it is accompanied by the original or a sworn or certified copy of it
The procedure for translating to legal equivalence differs from country to country
South Africa the translator must be authorized by the High Court, and (s)he must use an original (or a sworn copy of an original) in his physical presence as his source text; the translator may only swear by his own translation; there is no requirement for an additional witness (such as a notary) to attest to the authenticity of the translation.
Croatia: registered by the court; formal qualifications and exam
In the case of Mexico, some local instances, such as the High Superior Court of Justice, establish that a written and oral examination should be taken for a translator to be recognized as an expert or "sworn" / “certified” translator (this kind of translator does not swear before the court to be authorized). http://www.tsjdf.gob.mx/iej/peritos.html)
Even if a translator specializes in legal translation or if (s)he is a lawyer in his country, this does not necessarily make him a sworn translator
Types of CAT
The infrastructure for a translation environment is not necessarily translation-specific, but the importance of infrastructure becomes even more important in multilingual situations.
Elements of the infrastucture need to be as integrated as possible, both among themselves and with the actual translation process.
The elements of the infrastructure are:
Document creation/management system
Telecommunications (intranet/Internet, e-mail, ftp, web browsing, etc.)
2. Term-level before translation:
Term candidate extraction and terminology research. Term candidate extraction and terminology research are used to determine what words might be candidates for inclusion in a term base.
After a source language term is identified, by candidate extraction or some other process, terminology research is needed to find an appropriate term in the target language to designate the concept.
Terminology research can draw on many resources, including the
Internet and multilingual text databases.
As an example,
The term candidate extraction goes beyond what a spell checker can do by identifying candidates for new multi-word terms.
if we assume that the sentences in the bitext on the next page were part of a large text, and that thermal layer were not already in the termbase an extraction tool should propose it as a candidate term,
even if both thermal and layer were already in the termbase as individual words.
words thermocline and thermal layer might be considered terms that should always be translated consistently.
Automatic terminology lookup would display the preferred target language term (gradiente térmico and capa térmica in these cases)
Without the translator having to look the terms up manually.
As each segment of source receives the focus,
preferred target language terms are displayed and the human translator can quickly incorporate them into the target text without risk of misspelling.
Automatic terminology lookup supports terminological consistency for all text types.
4. Term-level after translation:
Terminology consistency check and non-allowed terminology check.
Terminology consistency checkers verify consistent use of terminology after a translation has been completed;
i.e., they make sure that each term is translated consistently, wherever it occurs.
For example, if the preferred term for thermocline is gradiente térmico and a human translator, for whatever reason, returns termoclino, a terminology consistency checker would detect this inconsistent use and flag the term for human attention.
Non-allowed terminology checkers flag terms which are not allowed (as in the case of deprecated terms) and bring them to the attention of a human.
He heard the captains discussing the absence of a thermocline.
Mancusco explained that it was not unusual for the area, particularly after violent storms.
They agreed that it was unfortunate.
A thermal layer would have helped their evasion.
Oyó que los capitanes comentaban la ausencia de gradiente térmico.
Mancusco explicó que no era extraño en la zona, particularmente después de tormentas violentas.
Convinieron en que era mala suerte.
Una capa térmica hubiera facilitado la evasión
5. Segment-level before translation:
New text segmentation, previous source-target text alignment, and indexing.
The preparation of an aligned, indexed source-target bitext is vital for the correct functioning of translation memory tools if previously translated text is to be leveraged (re-used).
Indexed bitexts are also useful for terminology research.
6. Segment-level during translation
Translation memory look-up and machine translation.
Automatic translation memory (tm) lookup applies primarily to revisions of previously translated texts and requires an indexed bi-text to function.
TM lookup compares new versions of texts with the tm database and automatically recalls those segments which have not changed significantly, allowing them to be leveraged.
For example, if the third sentence above were completely rewritten but the surrounding sentences were unchanged, tm lookup could process the text and automatically place retrieved translations of the unchanged sentences in the output file and return the changed sentence to the translator who could supply a translation.
For minor revisions of previously translated documents, tm lookup can provide enormous productivity increases.
Machine translation takes a source text and algorithmically processes it to return a translation in the target language.
Machine translation parses a sentence of source text, identifying words and relationships, selects target language terms, arranges those words in target language word order and inflects them.
mt typically is used for controlled language texts from a narrow domain and requires some post-editing where publication quality output is required.
mt systems often allow users to modify their dictionaries.
The following is raw (unedited) mt output in Spanish of the English source given above (in this case thermocline was returned untranslated since it was not in the system’s dictionary):
Él oyó a los capitanes que discuten la ausencia de un thermocline. Mancusco explicó que no era raro para el área, particularmente después de las tormentas violentas.
Ellos estaban de acuerdo que era infortunado.
Una capa termal habría ayudado su evasión.
7. Segment-level after translation:
Missing segment detection and format and grammar checks.
These functions are closely related to #4.
They check for missing segments, correct grammar, and correct retention of formatting.
if the following translation of the English passage in the bitext were received from a translator, a missing segment detection tool would let the user know that something was missing (the second sentence):
Oyó que los capitanes comentaban la ausencia de gradiente térmico. Convinieron en que era mala suerte. Una capa térmica hubiera facilitado la evasión.
8. Translation workflow and billing management.While
Workflow management is not directly part of translation, BUT it is extremely important for tracking the progress of translation projects.
Workflow management tools keep track of the location of outsourced translations and their due dates, text modifications, translation priorities, revision dates,
The larger the text and the more texts in process, the more important these features become since the logistics of dealing with all the variables which may influence a project are compounded with size.
Billing management also becomes increasingly important as the size of projects increases.
Ideally both parts of this function should be integrated with one another.
In multilingual countries such as Canada, translation of literary works (novels, short stories, plays, poems, etc.) is often considered a literary pursuit in its own right. Figures such as Sheila Fischman, Robert Dickson and Linda Gaboriau are notable in Canadian literature specifically as translators, and the Governor General's Awards present prizes for the year's best English-to-French and French-to-English literary translations.
Writers such as Tadeusz Boy-Żeleński, Vladimir Nabokov, Jorge Luis Borges and Vasily Zhukovsky, Miličević, Kaštelan have also made a name for themselves as literary translators.
Poetry is considered by many the most difficult genre to translate, given the difficulty in rendering both the form and
the content in the target language. In his influential 1959 paper "On Linguistic Aspects of Translation," the Russian-born linguist and semiotician Roman Jakobson went so far as to declare that "poetry by definition [was] untranslatable." In 1974 the American poet James Merrill wrote a poem, "Lost in Translation," which in part explores this. The question was also considered in Douglas Hofstadter's 1997 book, Le Ton beau de Marot.
Translation of sung texts — sometimes called "singing translation" — is closely linked to translation of poetry because most vocal music, at least in the Western tradition, is set to verse, especially verse in regular patterns with rhyme. (Since the late 19th century, musical setting of prose and free verse has also been practiced in some art music, though popular music tends to remain conservative in its retention of stanzaic forms with or without refrains.) A rudimentary example of translating poetry for singing is church hymns, such as the German chorales translated into English by Catherine Winkworth. 
Translation of sung texts is generally much more restrictive than translation of poetry, because in the former there is little or no freedom to choose between a versified translation and a translation that dispenses with verse structure.
One might modify or omit rhyme in a singing translation, but the assignment of syllables to specific notes in the original musical setting places great challenges on the translator.
There is the option in prose, less so in verse, of adding or deleting a syllable here and there by subdividing or combining notes, respectively, but even with prose the process is nevertheless almost like strict verse translation because of the need to stick as closely as possible to the original prosody.
Other considerations in writing a singing translation include repetition of words and phrases, the placement of rests and/or punctuation, the quality of vowels sung on high notes, and rhythmic features of the vocal line that may be more natural to the original language than to the target language.
While the singing of translated texts has been common for centuries, it is less necessary when a written translation is provided in some form to the listener, for instance, as an insert in a concert program or as projected titles in a performance hall or visual medium.
The term ‘translation’
Etymologically, "translation" is a "carrying across" or "bringing across."
The Latin "translatio" derives from the perfect passive participle, "translatum," of "transferre" ("to transfer" — from "trans," "across" + "ferre," "to carry" or "to bring").
The modern Romance, Germanic and Slavic European languages have generally formed their own equivalent terms for this concept after the Latin model — after "transferre" or after the kindred "traducere" ("to bring across" or "to lead across").
Additionally, the Greek term for "translation," "metaphrasis" ("a speaking across"), has supplied English with "metaphrase" — a "literal translation," or "word-for-word" translation — as contrasted with "paraphrase" ("a saying in other words," from the Greek "paraphrasis").
‘War does not determine who’s right but who’s left.”
E – H
Word translator 97 – default zona svojeglav ne odrediti nestašan pravo ali nestašan lijevi
Rat ne [determine] [who’s] pravo ali [who’s] lijevi
E – D
Krieg stellt nicht fest, wem Recht hat, aber wem verlassen wird
Krieg tut nicht ausmachen [who’s] richtig aber [who’s] link
E – I
La guerra non determina chi č di destra ma chi č andato
Guerra fa' non determinare [who’s] giusto solo [who’s] sinistro
Novi list, 17. IV. 2000. - Intertran
Pretjecanje razlog nesreće?
Istraga o uzrocima teške prometne nesreće još je u tijeku
i zasada nema službenih informacija o tom
kako je došlo do tragičnog sudara
Pretjecanje] why [nesreće]?
Learning about [uzrocima] [teške] traffic [nesreće] yet has been into a tenor
plus [zasada] does not have starched information about [tom] on how has been [došlo] up to [tragičnog] collision.