a) historical aspects: oral
vs
. written
vs. mechanical
- significance / historical role of TR - contribution to & impact on:
b) TYPES: literary
vs.
non-literary
c) METHODS of ORALTR:simultaneous
vs. consecutive
d) FORM: oral
(always non-literary) vs. written
e) medium in which TR is performed:
mechanical
& computer-aided
vs.
human
- 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
- always written and non-literary
- 50's & 60's – cold war (US/Russia)
- ASSUMPTION:
- 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
- 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. [16]
- 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
. [17]
- 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
- 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
- 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
- UNABLE translate literary texts (esp. poetry)
- pre-translation procedure (computer-aided TR)
- raw material for human refinement
- even: voice recognition - automated transcripts of human speech
- restricted texts: institutional, legal, specific technical (operational / maintenance) instructions; scientific abstracts, etc.
- TR tools (dictionaries, glossaries, lexical & textual databases, wordnet, www)
- corpus linguistics etc.: COBUILD, BNC, Brown, LOB, etc.
- though practically still unusable (except in restricted languages) -
- MT important for the theory of TR: investigation of basic relationships in the process of TR
- algorithmic rigour of MT - clear linguistic descriptions
- investigation of cognitive processes and the process of human TR (brain)
- computers useful in helping humans (speed) in the translation activity rather than in translation itself
- very common and ever-present human activity
- interest in the nature of the process of TR
- what happens in the translator's brain (Think-aloud protocols, Translog
)
- assessment of the product of TR, criticism
- human brain - inaccessible for investigation (psycholinguistics) - only results are accessible and available for research - indirect conclusions
- for teaching purposes
- an exciting new field in translation - a growing professional demand
- dubbing
and voice-over
- surtitling
and subtitling
- http://ics.leeds.ac.uk/papers/llp/exhibits/16/IntroAVTranslation_Adriana_Serban.ppt#257,2,Talk map
- Audiovisual translation (AVT) - subtitling and dubbing:
- one of the commonest forms of translation encountered in everyday life in contemporary societies
- of the 8,108 hours of programming broadcast by the Finnish broadcasting company YLE in 1996, 48%
consisted of foreign-language programmes (including re-runs) (Kontula, Larma and Petäinen 1997:52-53).
- The visibility of AVT is probably one reason why AVT also lends itself to easy and occasionally sharp criticism among viewers
- "subtitles offer the pretext for a linguistic game of 'spot the error'" for those viewers who have a command of both
(Shochat and Stam 1985:46)
- Internet sites devoted to listing subtitling gaffes, e,g, Turun Sanomat
5.7.1998
- It is interesting that in a sense AVT has been a channel for venting ideas on linguistic purism for quite a long while
- E.g.: an angry viewer had written to the editor complaining about the quality of a subtitling in a film. (Paunonen 1996:549):
- he demanded that distributors should take action to improve the quality of translations, or else censorship should intervene.
- http://ethesis.helsinki.fi/julkaisut/hum/engla/pg/jaskanen/ch2.html
- 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.
- Computers are used in many aspects of modern translation (particularly of technical texts).
- Note: a segment is a coherent piece of text larger than a term, usually a sentence.
- General translation & interpretation
- Specialized translation & interpretation
- 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
- 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
- literary translation
- medical translation and interpretation
- scientific translation and interpretation
- technical translation and interpretation
- 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
- The infrastructure for a translation environment is not necessarily translation-specific, but the importanceof infrastructure becomes even more important in multilingual situations.
- Elements of the infrastucture need to be as integratedas possible, both among themselves and with the actual translation process.
- The elements of the infrastructure are:
- Document creation/management system
- Terminology database
- Telecommunications (intranet/Internet, e-mail, ftp, web browsing, etc.)
- Term candidate extraction and terminology research. Term candidate extractionand terminology research are used to determine what words might be candidates for inclusion in a term base.
- After a sourcelanguageterm is identified, by candidate extraction or some other process, terminology research is needed to find an appropriateterm in the target language to designate the concept.
- Terminology research can draw on many resources, including the
- Internet and multilingual text databases.
- The term candidate extractiongoes 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 werepart of a large text, and that thermal layer
were not already in the termbase an extraction tool should propose it as a candidateterm,
- even if both thermal
and layer
were already in the termbase as individual words.
- Automatic terminology lookup:
- could be thought of as the term level equivalent of machine translation. For example, in the bitext on the next page the
- words thermocline
and thermal layer
might be considered terms that should always be translated consistently.
- Automatic terminologylookup would display the preferred target language term (gradiente térmico
and capa térmica
in these cases)
- Withoutthe translator having to look the terms up manually.
- As each segment of source receives the focus,
- preferred targetlanguage 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.
- Terminology consistency check and non-allowed terminology check.
- Terminologyconsistency checkers verify consistent use of terminology after a translation has been completed;
- i.e., they make sure thateach 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 inconsistentuse and flag the term for human attention.
- Non-allowed terminology checkers flag terms which are not allowed (as inthe case of deprecated terms) and bring them to the attention of a human.
- 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 ifpreviously translated text is to be leveraged
(re-used).
- Indexed bitexts are also useful for terminology research.
- Translation memory look-up and machine translation.
- Automatic translationmemory (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 havenot 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 translationsof the unchanged sentences in the output file and return the changed sentence to the translator who could supply atranslation.
- For minor revisions of previously translated documents, tm lookup can provide enormous productivityincreases.
- 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 froma narrow domain
and requires some post-editing
where publication quality output is required.
- mt systems often allow users tomodify their dictionaries.
- The following is raw (unedited) mt output in Spanish of the English source given above (in this casethermocline
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, particularmentedespués de las tormentas violentas.
- Ellos estaban de acuerdo que era infortunado.
- Una capa termalhabría ayudado su evasión.
- Missing segment detection and format and grammar checks.
- These functionsare closely related to #4.
- They check for missing segments, correct grammar, and correct retention of formatting.
- For example,
- if the following translation of the English passage in the bitext were received from a translator, a missing segment detectiontool would let the user know that something was missing (the second sentence):
- Workflow management is not directly part of translation, BUT it isextremely important for tracking the progress of translation projects.
- Workflow management tools keep track of the locationof outsourced translations and their due dates, text modifications, translation priorities, revision dates,
- Thelarger the text and the more texts in process, the more important these features become since the logistics of dealing with allthe variables which may influence a project are compounded with size.
- Billing management also becomes increasinglyimportant 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
. [7]
- 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.
- 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").[1]
- 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
").[2]
E – H
Word translator 97 – default
zona svojeglav ne odrediti nestašan pravo ali nestašan lijevi
intertran
Rat ne [determine] [who’s] pravo ali [who’s] lijevi
E – D
Systran professional:
Krieg stellt nicht fest, wem Recht hat, aber wem verlassen wird
Intertran
Krieg tut nicht ausmachen [who’s] richtig aber [who’s] link
E – I
Systran professional:
La guerra non determina chi č di destra ma chi č andato
Intertran
Guerra fa' non determinare [who’s] giusto solo [who’s] sinistro
| ! |
Как писать рефераты Практические рекомендации по написанию студенческих рефератов. |
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