Machine Translation (MT) or Automated Translation technology allows you to automatically translate text from one language to another. The quality of machine translation depends much on the training.
memoQ does not have its own machine translation engine but it is connected to the main engines through plugins. We currently support plugins from the following machine translation vendors, including the neural MT engines from Google and Microsoft Translator:
IntentoIntento is an Information Technology company which enables access to various vendors via a single API. Besides machine translation, Intento offers optical character recognition sentiment analysis, speech transcription, among others.
DeepLDeepL Translator is a translation service launched in August 2017 by DeepL GmbH, a start up company backed up by Linguee. The service currently supports translations between seven major European languages.
Amazon MTAmazon MT uses neural machine translation to offer high quality and fast language translation. Two key benefits of Amazon MT are customization and scalability, making it ideal for all projects, whether they’re easy or tricky, big or small.
Google Cloud Translation BasicGoogle Machine Translation or Google Translate API is probably the best known machine translation service available. Their translate.google.com service is free but there is an API call charge for using it for large amount of text translated or using it within another tool.
KantanMTKantanMT.com is a machine translation platform that enables its users to develop and manage customized MT engines in the cloud.
CrossLangCrosslang is a consulting and development company which specializes in MT, translation management and translation automation. The CrossLang Gateway is middleware that ensures easy and stable access to machine translation.
AltLangAltLang is an automatic language variety converter that helps you deliver content into different varieties of the same language, i.e. from American English into British English.
Omniscien TechnologiesOmniscien Technologies is a leading global supplier of high-performance and secure high-quality Language Processing, Machine Learning and Machine Translation (MT) technologies and services for use in data intensive applications.
Iconic Translation MachinesIconic Translation Machines Ltd. specialises in providing machine translation solutions for specific domains such as patent creation. It is a cloud based SMT system.
Tilde MTTilde specializes in developing custom MT systems for complex languages such as Nordic, Baltic, Russian, Central and Eastern European languages.
Microsoft TranslatorMicrosoft Translator is the free version of Microsoft’s MT engine available to the public. Microsoft MT is a statistical machine translation platform and web service, developed by Microsoft Research.
PangeaMTPangeaMT is an AI technology company offering machine translation development, deep learning, and machine learning services and consultancy.
SystranSYSTRAN is one of the oldest and best established machine translation solutions provider.
Mirai TranslatorTMMirai Translate provides a customizable translation solution that utilizes the advanced technology of machine translation and optimum learning data.
TexTra MT"みんなの自動翻訳＠TexTra®" is a machine translation site developed by the National Institute of Information and Communications Technology (NICT).
TmxmallTmxmall MT plugin integrates various MT engines and enables users to obtain machine translation results via a single API.
Alexa Translations A.I. MTAlexa Translations provide a neural MT service specialized in the Canadian legal and finance sectors.
ModernMTModernMT is a self-learning machine translation service that improves from your corrections as you keep using it.
Google Cloud Translation AdvancedGoogle Machine Translation Advanced (or Google Translate API v3) can do everything the Basic API can, but also allows usage of glossaries and custom MT models that can be quickly trained using the AutoML (Automated Machine Learning) feature
Machine translation post-editing
Machine translation evaluation and deployment
There are many vendors and many metrics for machine translation evaluation. We believe that post-edited machine translation is a productivity booster, and allow the quantification of productivity through reporting on the time. Editing time analysis allows you to quantify the productivity gain over processes without machine translation, and makes different vendors comparable. Edit distance analysis allows you to analyze your post-editors, those who make too many changes to the text versus those who make just enough changes to meet your quality goals. memoQ gives you all the tools to successfully evaluate and deploy machine translation software, and offers the infrastructure for machine translated workflows.
One of the biggest issues in deploying post-editing is the lack of a general post-editing business model. We propose to set up post-editing compensation based on the actual productivity gains achieved, and regularly review the productivity gains to allow for a fair compensation that can be estimated before the post-editing project starts. It is also an accepted practice to pay for the actual amount of editing done, which is to be calculated after the job is delivered, or on an hourly basis. memoQ allows you to get the underlying data for all three calculation methods.
memoQ’s LQA model allows users to define error typologies and offer the relevant data to improve the output of machine translated texts as part of the standard workflow. This means that there are no extra resources needed to analyze the quality of individual segments and collect examples, and the most frequent error types can be easily quantified. Retraining and reevaluating of machine translation engines is also easy with memoQ.
The entire toolset for users who have previously worked with other tools
Through memoQ’s compatibility with other translation tools, you can easily migrate to memoQ and get all the tools to successfully deploy machine translation in your organization. You can use memoQ only for machine translated projects or deploy it across the organization for all projects.