Translations of the highest standard call for the professional management of terminology and data. Applying state-of-the-art translation memory systems ensures a smooth workflow and consistent use of specialised terminology while also saving time and money.
In addition to all current Office file formats, we process XML, HTML and InDesign files or can enter our translations directly into your content management system, for example Typo3. We are also happy to offer foreign-language DTP services and deliver the documents in a ready-to-print format.
We use the Plunet professional business and management system for the handling of our translation projects. This highly functional software fulfils all individual requirements, specifically concerning translation-related and business processes. The integrated enquiry portal, to which you have your own password-protected access, enables you to request quotes, place orders, track your ongoing translation projects and securely upload and download project files.
As a rule and at no extra cost, we apply the latest versions of the most common translation software on the market, such as SDL Trados Studio, STAR Transit, across and memoQ, in order to make translation processes faster, more efficient and cheaper for you. These tools are used to build customer-specific translation memories and they support all common file formats, from InDesign through FrameMaker to HTML, PDF and the usual Microsoft Office programs.
The resulting translation consistency on sentence level ensures that your company communicates uniformly in all languages and areas of business.
Individually configurable terminology databases such as MultiTerm, crossTerm and TermStar help to ensure that your company communicates with consistent specialised terminology in all languages and areas of business. We build customer-specific glossaries and dictionaries, which are available to each translator throughout the translation process.
In the age of artificial intelligence, it is possible to produce high-quality machine translations. Be it rule-based, statistical or neural – machine translation has become a matter of course. In recent years, computational linguistics has seen enormous progress and the development of learning “engines”, which can learn how to translate using complex algorithms and are meanwhile achieving an astonishingly reasonable language quality. Their advantage: they save time.
However, machine translation is not suitable for all purposes. A proper learning effect can only be achieved if a large corpus of similar texts is available at the outset – as with the textual adaptation of instruction manuals to new data, for example. How good the results of machine translation actually are always depends on which source and target languages are involved. Simple texts with short sentences and a common language combination such as German/English are a good basis. If, however, a complicated legal text with a lot of specialised terminology and long, convoluted sentences is to be translated into a less commonly used language such as Latvian or a more complex language such as Arabic, the outcome is likely to be faulty and should be treated with caution.
As machine-driven and automated as the process may be, high-quality translation is still inconceivable without human intervention. Prior to machine translation, a source text has to be thoroughly prepared so that the tools can work efficiently. Then the machine-generated raw translation needs to be checked and corrected by a post-editor. This role is filled by a linguist, i.e. a translator or proofreader.
In addition, special data protection and confidentiality rules apply for machine translation.
