Here’s Translexy.

Usage

Below are some of the key areas where developers can engage with the platform. For additional information get in contact.

/translate

Translates document immediately. Limitations: size, frequency, number of queued documents, format, ...

Examples

Translate text in file sample.txt from English to German: Translate subtitle sample.vtt from English to Italian:

Detailed instructions are available as pdf.

Note: In order to use the API, you will need an account. Get in touch.

Please note that this service is still under development. Talk to us about current limitations and upcoming features.

About

Translexy solution.

Translexy is an API that enables you to translate your content. It is already integrated into MOOC platforms and video repositories to create new educational experiences. It also offers tools for developers and researchers. Translexy API is the first free and open translation service to use Neural Machine Translation Models (NMT) for educational content, which immensely improves translation results. NMT has recently emerged as a disruptive technology and has become the dominant paradigm in machine translation. Translexy

Discover below how you can use, integrate and customize this service in your own application or MOOC solution. Translexy API can be used on its own or its results can be customized for pre-publishing with our partners.

Translexy API provides translation from English into nine European and two BRIC, languages, namely German (DE), Italian (IT), Portuguese (PT), Dutch (DU), Bulgarian (BG), Greek (EL), Polish (PL), Czech (CS), Croatian (CR), Russian (RU) and Chinese (ZH).

The problem Translexy solves.

Business solution: Education publishers, MOOC providers and Video repositories need to offer high-quality, integrated multilingual educational services to their customers. Translexy provides this service for all types of textual data that is language independent in nature and addresses all types of text genres.

Market solution: The European Digital Single Market is still fragmented by language barriers that hamper a wide penetration of cross-border commerce, social communication and exchange of cultural content. Current machine translation solutions typically perform well only for a limited number of target languages and for a given text type. Therefore, Translexy provides a unique solution to tackle scalable, sustainable translation for the education market.

Science

The project behind Translexy.

In 2015, nine European Institutions joined forces to solve the problem of mass translation in education. They designed a European project called TraMOOC which provides a system and solution that is intended to overcome the language barriers in MOOCs, and is expected to deal with huge volumes, a big variety of languages and text styles, and deliver results in a reasonable time. Special attention was paid to selecting 9 EU and 2 BRIC languages that have "fragmentary" or "weak/no" machine translation support according to the META-net language white papers.

Launched on February 1st, 2015, by a consortium made up of six European universities, Humboldt Universität zu Berlin (UBER), Dublin City University (DCU), University of Edinburgh (UEDIN), Ionian University (IURC), Stichting Katholieke Universiteit (Radboud University), Stichting Katholieke Universiteit Brabant (Tilburg University), two industrial partners, Deluxe Media Europe (DME) and EASN-Technology Innovation Services (BVBA), and a not-for-profit, Knowledge 4 All Foundation Ltd (K4A), it will run until January 31st, 2018.

The science behind Translexy.

Machine translation: The high quality of translations is achieved through a hybrid translation schema that combines automatic processes (i.e. text processing tools and linguistic resources that are adapted to cope with multi-genre MOOC educational texts) together with limited, focused human intervention, i.e. crowdsourcing in a novel time- and cost-efficient setup for evaluating the generated translation.

Implicit and Explicit evaluation: We have established a new, standardized, multi-level evaluation schema for determining the value of the produced machine translation. Taking into account the idiosyncrasies of the particular text type and its multi-genre character, the evaluation schema consists of a human and an automatic aspect, as well as a traditional explicit (direct) and an innovative implicit mode, that will be facilitated via separate text mining and topic identification.

Crowdsourcing: We employ crowdsourcing activities for infrastructure enhancement and translation evaluation where human intervention is required. The choice of crowdsourcing for handling these tasks is supported due to its direct link with Open Innovation, with crowd wisdom and co-creation.

Tools

Translexy’s tools for researchers.

Test the tools and solutions created by the TraMOOC project with appropriate license models (a development license, a research license or an open license for testing purposes), and software packages for the development of state-of-the-art systems for language translation of educational texts.

The translation model training processes, the resource bootstrapping processes, and the text mining methodologies, which are the result of the TraMOOC project, form a library of algorithms that will prove invaluable to the scientific community.

• Open-source TraMOOC MT engine
• The training framework for the marian development repository
• Babelente software for implicit MT evaluation

Benefits from Translexy’s tools.

Developers, Businesses, Educators can use Translexy API to play with language pairs and analyze the value of having their content translated into other languages.

Machine Translation developers can use Translexy as a unified workbench for integrating MT solutions and a platform for promoting, testing and comparing their solutions.

Language Technology Engineers and community can get access to accurate and wide-coverage linguistic infrastructure for less widely spoken languages. This infrastructure includes exploitation, enrichment, and adaptation policies on bootstrapping, cross-language, and interdisciplinary approaches to create new or enrich/adapt available tools and resources.

Case Studies

Serving learners identity in MOOC courses.

MOOC platform use case / openHPI

openHPI , the educational Internet platform of the Hasso Plattner Institute in Potsdam, Germany, runs MOOCs – Massive Open Online Courses – which are one of the most innovative and most flexible forms of e-learning. Available free via the Internet, learners can participate in high-quality online courses on the subject of Information Technology, Digital Transformation, and Innovation. Learning in close contact with their peers by means of fora, collaboration spaces, and interactive exercises is an important part of the concept.

Quick facts:

• Platform with learning videos, self-tests, practical exercises, text, graded assignments, certificates and more
• openHPI: First Original instance of the HPI platform family (openHPI, openSAP, mooc.house, openWHO). More than 160,000* registered users and more than 440,000* enrollments
• openSAP: First enterprise MOOC platform run by HPI. More than 660,000* registered users and more than 2,500,000* enrollments
• openWHO: MOOC platform of the World Health Organization (WHO) to support staff and volunteers as well as population affected of epidemics and pandemics. More than 14,000* registered users and more than 19,000* enrollments (*status of January 2018)

Challenges:

In order to reach new audiences and better support existing, non-english speaking audiences, an automated translation tool is required. Next to the translation of videos, textual content consists of reading material, quizzes and assignments. User contributed content mainly consists of forum posts, allowing multi-lingual discussions would be a nice-to-have option. All translations, currently, are done manually with some tool support for subtitling. The platform’s video player supports the display of transcripts and subtitles in any number of languages.

Providing audiences with multilingual learning experiences

Video platform use case / VideoLectures.Net

The newest breakthroughs in business, technology, and science are disseminated through a rich network of numerous yearly global conferences. However, only a tiny fraction of the interested scientific community has access to this knowledge, which exacerbates both an intellectual and developmental gap among those talented individuals with and without access. VideoLectures.Net fills this gap with its service.

Quick facts:

• Portfolio of 23,000 peer-reviewed lectures
• Collected from over 1000 events
• Presented by over 14,000 authors
• Over 5000 unique visitors daily from academia and industry
• Recipient of United Nations World Summit Award
• Currently provides only EN to Slovene, Spanish, Catalan, French, Italian
• Includes 16,870 transcriptions in English waiting to be translated

Challenge:

VideoLectures.Net is making up-to-date knowledge available to everyone, regardless of their ability to attend expensive scientific events, from all disciplines. This includes video recording the top scientific events world-wide, translating the content into major world languages (through automatic subtitling), and making the content available freely to anyone with an internet connection. The challenge is how to serve the global education and learning community by using open and state-of-the-art translation technologies.