The future of online translators and automatic translation
The Internet has become an essential part of our everyday life:
- As we follow faraway political developments that may still strongly influence our security or prosperity.
- Or as we look for profitable investment opportunities in foreign lands –presented in incomprehensible languages–.
⤷ We increasingly turn to online automated translation to understand what it is all about.
About automatic translation
With all the current deficiencies of automatic translation, this is the only translation tool that:
- is readily available and
- allows us quickly to decide what is worth more thorough digging and possibly employing professional translators.
The quality of even free online translators
It is permanently improving, and one can imagine machines will do time when many human translators lose jobs as the bulk of translation.
Indeed, machine translation, as a practical sub-field of computational linguistics – which studies ways to use translation software for translating texts or speech from one language to another –
⤷ is a rapidly developing area of applied research.
➤ Still, no matter how much the automatic translation technology will evolve.
→ This process is many years away before the translation process will become fully reliable and adequate —not requiring post-editing—which is the human intervention to check for misinterpretations and other errors.
For years to come, the high-quality translation will remain, at best, a hybrid process in which:
- human professionals revise and correct texts generated by translation software,
- as while machine translation’s advantages are low cost and high speed.
→ Automatic translation lacks context interpretation, a necessary ability characteristic of human interpreters, as the meaning of any text is strongly dependent on cultural and situational contexts.
Machine translation over the years
INITIALLY, machine translation was based on:
→ A simple substitution of words in one language for words in another, and even this is not an easy task due to such phenomena as polysemy, homonymy, metaphors, and idioms.
Naturally, such a primitive approach was unable to produce a good translation, as the textual meaning depends on how the translators arrange:
- whole phrases and
- their closest counterparts.
CURRENTLY, data application is partially resolving this problem:
→ And statistical techniques from corpus linguistics produce, on average, much better translations,
⤷ even enabling the translation of:
- natural forms
Machine translation uses gathered corpus data to provide a statistical equivalent of what the best translation may be,
⤷ still leaving much potential for error.
Naturally, this is not yet enough, as anyone who has used online translation tools such as Google Translate or any other virtual translator should have encountered absurd cases of machine translation:
- At best ▸ incorrect or funny.
- But at worst ▸ misleading or offensive.
→ These translation tools are as yet:
- Only suitable for casual translation ▸ intending to grasp a general idea of a text.
- And not ideal for full-fledged documents.
→ Also, they are:
- More satisfactory in case of standardized (official or legal) records
- but inadequate in translating a conversation or a literary text.
Consequences due to the use of online translators and automatic translation
Hardly anyone can afford to have significant mistakes happen when it comes to translation for these particular purposes:
- business purposes
↳ Hence, highly professional translators and interpreters will undoubtedly remain in high demand for a long time.
Glossary applicable to online translators and automatic translation
꧁꧂ Machine translation, automatic translation, automated translation
It is the computer-based technology that uses digital computer systems and translation software to automatically translate texts from one original language into a target language.
➤ A little history of machine translation:
- Britain and the USA were the first to propose the practical idea of using digital computers for the translation of natural words,
- after the end of the World War II (respectively by A. D. Booth, Warren Weaver, and others),
- with the lead taken by:
- the Birkbeck College in London,
- Georgetown University in Washington, DC,
- and the Massachusetts Institute of Technology,
- followed by work in Russia,
- and a few other countries.
➤ CURRENTLY, machine translation is a rapidly developing area of applied studies.
However, the potential of automated translation and the possibility of achieving fully automatic machine translation of high quality have been questioned since its conception ✓
Ⓘ Translation tools
These are any of the systems that:
- PERFORM automatic translation, or
- ASSIST & SUPPORT human translators with language translation ▸ called computer-assisted translation or computer-aided translation
⤷ By offering possible solutions.
Ⓘ Translation software
This term refers to computer programs designed to provide high-quality machine translation.
➤ AT AN EARLY STAGE, translation software simply substituted words in one language for words in another.
⤷ Thus leading to low-quality products due to polysemy, homonymy, metaphors, and idioms.
➤ CURRENTLY, these difficulties are at least partially resolved,
⤷ by applying data and statistical techniques from corpus linguistics, producing, on average, much better translations.
Ⓘ Virtual translator
This translator system does not physically exist but relies on applying machine translation approaches and translation software to appear to do so.
Ⓘ Online translators
These are automatic translation tools available on the Internet, increasing offered by:
- web browsers,
- search engines,
- and other globalized Internet resources.
In most cases, free online translators are readily available, among the most popular tools being Google Translate and Bing Translator, along with many others.
Often online translation is conducted by specialized plug-ins: software components that add specific translation capacity to existing online resources such as web browsers.
Polysemy, homonymy, metaphor, idiom
Related linguistic phenomena such as polysemy are characterized by a word’s multiple meanings (or seems) within certain contiguity of purposes (a semantic field).
While, as a rule, in the case of homonymy, the various meanings of a word are unrelated.
In the case of a metaphor, the term (s) may refer to one thing by mentioning some other, exploiting some form of:
- analogy or
Finally, idiom refers to a fixed expression that, in a given context, conveys a meaning that’s:
- rather than literal.
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