Machine Translation

Our Machine Translation service

Extensive research in Natural Language Processing, technological advancements and computational linguistics training have resulted in the outstanding development of sophisticated translation technology, producing grammatically coherent translated output and showing promising results in a variety of language pairs.

To manage increasing translation volumes and the need for fast turnaround times, we now support a cutting-edge high-quality machine translation solution using Neural Machine Translation (NMT) technology. Thanks to continuous progress in quality and output and seamless integration with our translation environment, Machine Translation is the ideal tool for high-volume, organised, structured content in certain language pairs and documents where timelines and budgets are a concern.

machine translation


Fully automated Machine Translation

By removing human intervention in the translation process, delivery times are drastically faster than human-only translation. Our automated neural machine translation tasks are executed within our Translation Management System (TMS) to ensure safe and seamless integration with any application or workflow and enable a streamlined process and consistent translation outcomes across your organisation. Our data centre is hosted in Australia and complies with strict security and privacy requirements. The Neural Machine Translated (NMT) output occurs through our cybersecurity secure server. The NMT Engine is customised for each client. It applies first the client-specific terminology stored and curated in our Term Base and Translation Memory for that particular client before prepopulating the remainder with NMT output.

This service is the most cost-effective way of translating large volumes of text in short timeframes and our customers can have access to this secure NMT system at any time through our secure Customer Portal, pass their content through the engines themselves and receive automatically the translated content.

Post-edited Machine Translation

When the speed of Machine Translation is required but the output needs to match certain quality requirements, we offer post-edited machine translation. Your machine translated content is reviewed and post-edited by a professional and certified translator for an optimal quality output. We offer light or heavy post-editing as well as highly technical post-editing by domain and subject matter experts

Post-edition can also be realised by country-specific linguists when there is a need for localisation and cultural adaptation. For marketing collateral and creative content, post-editing is not recommended. Translators and copywriters will prefer to re-write content from scratch in the foreign language to ensure effectiveness of messaging, naturalness of language and making sure the narrative gets across.

What is Machine Translation?

It is the translation of content without human involvement. Pioneered in the 1950's machine translation has significantly evolved to include new models that include cutting-edge technologies such as artificial intelligence and machine learning. There are 3 types of machine translation as well as hybrid systems, a mix of them.

The rule-based system functions with a combination of language and grammar rules plus dictionaries for common words. Specific glossaries or term bases are created to focus on certain industries or disciplines or for a certain client. Rules-based systems typically deliver consistent translations with consistent terminology when trained with a specific term base.

Statistical systems do not have implemented 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 terminology 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. The approach has become increasingly popular amongst researchers and developers, as trained NMT systems have begun to show better translation quality in many language pairs compared to the statistical approach.