Technologies We Use

 Translation Memory Alignment (TMA) is a method by matching same text  (sentences, phrases, words) using alignment tools. It creates a database  of text segments in two different languages. TMA allows for clients to  provide two files (source and target languages) representing the same  text and align the sentences matching them to generate a translation  memory (TM). These aligned bilingual memories allow clients to reuse  identical and similar text segments that have previously been  translated, to aid human translators in translation projects. A TM is  invaluable when translating and localizing great volumes of content. A  term or sentence once translated doesn’t need to be translated again. It  is automatically substituted in a new document. The translation process  using TM preserves the linguistic consistency of corporate documents  across platforms and versions. This proves to be invaluable in  translating content that includes many repetitions like technical  specifications, financial statements, and legal terminology. With TM as a  base, translation of documents goes much faster. Instead of starting  from scratch with translation, TMA allows you to build a repository of  translation segments that are saved and can be utilized immediately. 

 CMS connectors enable you to connect our translation management system  with your own CMS, ERP, or other business software. This enables greater  automation of the translation process, saves time, and aligns  everything in one uninterrupted flow. With experience of working with  international organisations using a variety of software, often  non-integrated, we know the challenges involved in keeping everything in  sync with the latest approved version. That's why we ensure that, in  dealing with enterprise content management, we have the right tools and  integration capabilities to provide comprehensive support. 

 Machine or automated translation is the process whereby computer  software takes an original (source) text, splits it into words and  phrases (segments), and finds and replaces these with words and phrases  in another language (target).  Using various algorithms, patterns, and large databases of existing  translations, machine translation technology can quickly produce large  quantities of translated texts without any human involvement at all.    

There are three types of machine translation system: rules-based, statistical and neural:

• Rules-based systems use a combination of language and grammar rules plus dictionaries for  common words. Specialist dictionaries are created to focus on certain  industries or disciplines. Rules-based systems typically deliver  consistent translations with accurate terminology when trained with specialist dictionaries.
• Statistical systems have no knowledge of language rules. Instead they "learn" to translate  by analysing large amounts of data for each language pair. They can be  trained for specific industries or disciplines using additional data  relevant to the sector needed. Typically statistical systems deliver  more fluent-sounding but less consistent translations.
• Neural Machine Translation (NMT) is a new approach that makes machines learn to translate through one  large neural network (multiple processing devices modeled on the brain).  The approach has become increasingly popular amongst MT researchers and  developers, as trained NMT systems have begun to show better  translation performance in many language pairs compared to the  phrase-based statistical approach.