That's interesting !, Traductions

Some interesting facts about translation history – 2

The word “translation”comes from a Latin term meaning « to bring or carry across ». The Ancient Greek term is ‘metaphrasis’ (« to speak across ») and this gives us the term ‘metaphrase’ (a « literal or word-for-word translation ») – as contrasted with ‘paraphrase’ (« a saying in other words »).  The first known translations are those of the Sumerian epic Gilgamesh into Asian languages from the second millennium BC. Later Buddhist monks translated Indian sutras into Chinese and Roman poets adapted Greek texts.

Translation undertaken by Arabs could be said to have kept Greek wisdom and learning alive. Having conquered the Greek world, they made Arabic versions of its philosophical and scientific works. During the Middle Ages, translations of these Arabic versions were made into Latin – mainly at the school in Spain. These Latin translations of Greek and original Arab works of learning helped underpin Renaissance scholarship. Religious texts have played a great role in the history of translation. One of the first recorded instances of translation in the West was the rendering of the Old Testament into Greek in the 3rd century BC.  Saint Jerome, the patron saint of translation, produced a Latin Bible in the 4th century AD that was the preferred text for the Roman Catholic Church for many years to come. Martin Luther himself is credited with being the first European to propose that one translates satisfactorily only toward his own language: a statement that is just as true in modern translation theory.

Translation today

In the modern world, translation is as important – if not more so – as it was several millennia ago. Officially, there are about 6,800 languages spoken around the world, of which a significant portion have unique scripts and many have shared scripts based on the origins of the language in question. These challenges are compounded by the fact that nearly every culture in the world has interactions with every other culture. This means that there are an incalculable number of translation requirements every second of every minute of every day around the world. It’s no wonder, then, that translation is a dominant part of intercultural interaction.

The slow speed of manual translation has led to technology stepping in. Thus, machine translation (MT) was born. With the dawn of the technological age, the application of software to the field of translation became an interesting subject that was, and continues to be. Although more fallible than purely human translation, machine translation is a useful tool that has found several applications. For example, MT is regularly used for weather reports and other speciality areas where linguistic variables are limited. It is sometimes used for written government or legal communication, too, albeit with a modicum of human intervention. Though currently limited in application, it is a useful tool in the repertoire of any professional translator – if only to make the job a little bit easier or quicker. In its most advanced form, MT may give satisfactory output for unrestricted texts, but it is still best used when domains and variables (such as disambiguation or named entities) are controlled in some way. There is no doubt that the need for human translators will remain, and that even the best MT software can only go so far where sensitive or specialised translation is required. For results of the highest quality and integrity with respect to the source and target material, there is still no adequate substitute for human translator.

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CAT, Langues, Traductions

Machine and manual translation – 1

Machine translation is also known as Computer Aided Translation, is basically the use of software programs which have been specifically designed to translate both verbal and written texts from one language to another.

Trados is one of a few computer-assisted translation tools (CAT tools). Its primary function is to allow translators to reuse translations. SDL purchased Trados a few years ago, and their products are generally branded now under the name of « SDL/Trados ». The advantages of using machine translation include the fact that you can make documents in several languages easily.  Generally, it is rather useful for specialized texts (medical, technical, legal), I think. In my opinion any CAT tool is good for those parts of texts that repeat: if you have to translate extracts from business registers, school-leaving certificates, birth certificates, legal records or other such documents, then a CAT tool will do good. One extremely good thing is that Trados keeps the original formatting, so you usually don´t have to deal with the visual form of a document.  When more people work on large projects, it helps to use the same terminology and thus increase the overall quality of translated documents. One of advantages of CAT-Tools is terminology handling.  A good Multiterm-glossary can be extremely useful for legal documents, too. If you are dealing with repetitive texts that are crawling with specific terminology, then this software is the tool for you too.  Next advantage is that with CAT-tools you cannot accidentally leave out a sentence – something that can all too easily happen when overwriting. Another advantage of Trados  is an excellent way to review other people’s texts.

The main disadvantage of using machine translation is his cost, but you can leverage it in a very short time. I heard several people have said that Trados (or any CAT tool) is no good for creative texts, literary translation etc. The other disadvantage is the accuracy of translated material (text) depending on word ordering of original text.

Nuances, cultural differences, and vocabulary that is very local need to be translated by a person. Systematic and formal rules are followed by machine translation so it cannot concentrate on a context and solve ambiguity and neither makes use of experience or mental outlook like a human translator can.

Interprétariat

What is machine translation?

What Is Machine Translation?

Machine translation (MT) is automated translation. It is the process by which computer software is used to translate a text from one natural language (such as English) to another (such as Spanish).

To process any translation, human or automated, the meaning of a text in the original (source) language must be fully restored in the target language, i.e. the translation. While on the surface this seems straightforward, it is far more complex. Translation is not a mere word-for-word substitution. A translator must interpret and analyze all of the elements in the text and know how each word may influence another. This requires extensive expertise in grammar, syntax (sentence structure), semantics (meanings), etc., in the source and target languages, as well as familiarity with each local region.

Human and machine translation each have their share of challenges. For example, no two individual translators can produce identical translations of the same text in the same language pair, and it may take several rounds of revisions to meet customer satisfaction. But the greater challenge lies in how machine translation can produce publishable quality translations.

Rule-Based Machine Translation Technology

Rule-based machine translation relies on countless built-in linguistic rules and millions of bilingual dictionaries for each language pair.

The software parses text and creates a transitional representation from which the text in the target language is generated. This process requires extensive lexicons with morphological, syntactic, and semantic information, and large sets of rules. The software uses these complex rule sets and then transfers the grammatical structure of the source language into the target language.

Translations are built on gigantic dictionaries and sophisticated linguistic rules. Users can improve the out-of-the-box translation quality by adding their terminology into the translation process. They create user-defined dictionaries which override the system’s default settings.

In most cases, there are two steps: an initial investment that significantly increases the quality at a limited cost, and an ongoing investment to increase quality incrementally. While rule-based MT brings companies to the quality threshold and beyond, the quality improvement process may be long and expensive.

Statistical Machine Translation Technology

Statistical machine translation utilizes statistical translation models whose parameters stem from the analysis of monolingual and bilingual corpora. Building statistical translation models is a quick process, but the technology relies heavily on existing multilingual corpora. A minimum of 2 million words for a specific domain and even more for general language are required. Theoretically it is possible to reach the quality threshold but most companies do not have such large amounts of existing multilingual corpora to build the necessary translation models. Additionally, statistical machine translation is CPU intensive and requires an extensive hardware configuration to run translation models for average performance levels.

Rule-Based MT vs. Statistical MT

Rule-based MT provides good out-of-domain quality and is by nature predictable. Dictionary-based customization guarantees improved quality and compliance with corporate terminology. But translation results may lack the fluency readers expect. In terms of investment, the customization cycle needed to reach the quality threshold can be long and costly. The performance is high even on standard hardware.

Statistical MT provides good quality when large and qualified corpora are available. The translation is fluent, meaning it reads well and therefore meets user expectations. However, the translation is neither predictable nor consistent. Training from good corpora is automated and cheaper. But training on general language corpora, meaning text other than the specified domain, is poor. Furthermore, statistical MT requires significant hardware to build and manage large translation models.

Source: http://www.systran.co.uk/