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WHERE the internet has yet to take firm root, people plump for the next-best thing. In many emerging markets this means text messaging. Customers have embraced the short message service (SMS) not just to communicate with each other, but also to get weather forecasts, bus schedules and traffic information, or to vote in television talent shows. Authorities use it for public announcements. Companies text targeted advertising. India even has a rudimentary SMS-based social network.

The reason texting isn't even more popular in such places has to do with the fact that—despite indignant claims in some quarters that texting is killing literacy—texters must be able to read and write. One could get a phone's text-to-speech program to read incoming text messages out loud, a feature available even on simple devices. But that still leaves out the hard of hearing. In Tunisia, for instance, perhaps 90% of the 200,000 or so deaf are also illiterate, estimates Mohamed Jemni, a computer scientist at the Ecole Supérieure des Sciences et Techniques in Tunis.

So Dr Jemni's team built a system which uses natural-language processing to translate text messages into sign-language animations delivered in the form of a multimedia message (MMS). MMSs work on most phones and the actual data-crunching is performed not on the device but on the EUMEDGrid, a distributed-computing facility.

Dr Jemni claims that around 1,000 people already use his program, MMSSign, on Tunisia Télécom, the country's national operator. Before the system can be adopted in other countries facing a similar illiterate-deaf predicament, though, it has to learn hundreds of signing languages and dialects in use worldwide. In order to make that possible, the team is designing a web interface to make building and updating the text-to-signing dictionaries easier. (Signing-to-text conversion is also in the works, though further off.)

As for personal communication, video streaming would help, but it demands fast mobile-broadband networks and expensive phones. And whereas a choppy or grainy image might be acceptable in a video call optimised for voice, research suggests that signing is hard to read on small screens using existing video-compression algorithms. So another research team at the University of the Western Cape in South Africa, led by William Tucker, is busy figuring out how to optimise mobile communications for the deaf. They are examining how to adapt compression algorithms for video streaming as broadband connections grow more accessible. In the meantime, they too are compiling digital dictionaries on grid computers, with a view to making two-way translation between the written word and sign language possible.

Before long, then, hitherto ill-served customers may at last begin to delight in the joys of texting. They may rejoice less at the inevitable sign-language spam.

Source: The Economist

In Tunisia, researchers are developing easy-to-use web tools to automatically translate written text into sign language.

In developing countries, the majority of deaf people are illiterate and cannot use mobile phone Short Message Service (SMS) or text messages. Their preferred language is sign language according to a research paper by scientists from the University of Tunis.

The WebSign project aims to break the silence of deaf people. “It’s an initiative to help deaf individuals use Information and Communications Technology (ICT) and hearing people to communicate with deaf ones. The project is really exciting, especially when meeting and getting in touch with the target community,” said Mohamed Jemni, head of the research laboratory at the University of Tunis and director of the Al Khawarizmi Computing Center.

One application they’ve already released is called MMS Sign, a free service for deaf people who want to use mobile phones, but cannot read. “There are no studies in the literature concerning projects that handle deaf and hard of hearing issues,” said Jemni.

The application automatically translates an SMS sent from a mobile phone. It converts it into a Multimedia Messaging Service (MMS) that displays a 3D Computer-Generated-Image (CGI) avatar who acts-out the message in sign language.

This is how it works: if someone sends a message to a deaf person, e.g. “I will be late”, this is sent to a telecom operator on the mobile phone. Once this text message is received by the telecom operator, the MMS Sign application converts the SMS into an MMS which is automatically sent to the deaf person. The MMS received by the deaf person contains the sign message, “I will be late”.

“For many deaf people, this is the only way to receive messages and use mobile technology to communicate. This is very important for emergencies, asking for help, or communicating with parents. This service is already available in Tunisia. More than 200 deaf individuals were involved in the testing phase. More than 1,000 users use our products in Tunisia and some Arabic countries,” said Jemni.
Do you like to eat green apples?

The MMS Sign tool requires access to a whole host of resources to manage millions of words. Jemni said, “WebSign needs huge computational resources and also sign language experts, deaf users, and linguists to enrich sign dictionaries.”

The readable-text-to-sign-language translation is done through a machine learning approach. These are algorithms that compare the collection of words within the English language (also known as a corpus), in machine-readable form, with sign language, creating a parallel corpora of languages.
Image of MMS Sign application 3D avatar character.

The 3D avatar character animation is helping around 1,000 illiterate deaf people in Tunisia and other arabic countries. Image courtesy Mohamed Jemni.

A mathematical algorithm takes a given sentence in English and finds the most appropriate translation in sign language. An example of a word string would be: “Do you like to eat green apples?” with the equivalent sign translation being “APPLE, GREEN, YOU LIKE EAT?”

The data volume is enormous; the English language corpus alone has 52 million words. Jemni and his colleagues are using the scientific computing resources of the EUMEDGrid-Support e-infrastructure to greatly reduce the processing time and improve the quality of translations. EUMEDGrid is an e-infrastructure network that supports 25 sites across 13 countries.

“We opted to use the EUMEDGrid infrastructure in order to generate a very big parallel corpus of sign language - the biggest parallel corpus of sign language in the world - to improve the efficiency of the automatic translation. EUMEDGrid reduces processing times from several months to several minutes,” said Jemni.

The WebSign project was presented by Jemni at the Mediterranean e-Infrastructures (EUMED4) conference in Amman, Jordan, on 13 December 2011, in conjunction with the First International Platform on Integrating Arab e-Infrastructure in a Global Environment.

Now, Jemni and his team are working on integrating the WebSign project with the EUMEDGrid science gateway. A science gateway is a pre-configured set of tools, applications, and data integrated into a single portal and accessible via a web browser. More applications are being developed. These include a screen reader that helps deaf people to sign what’s written on their screen, and a sign language course to teach deaf and hearing people sign language.

Eventually, the project will be transferred to a cloud service. Jemni said, “once deployed as a cloud, anyone could access it and translate a written text into sign language regardless of the device, software, or community they belong to.”

“To my knowledge, it is the only example of its kind in the grid world. We are currently brainstorming about how to integrate WebSign in the EUMEDGrid science gateway,” said Roberto Barbera, a senior researcher at the University of Catania.

Source: iSGTW, 1 February 2012

The Workshop on Developing Lebanese National Research and Education Network took place on the 21st of October 2011 in Beirut at the Ministry premises. Hosted by the Ministry, the workshop built on an on-going dialogue with key decision makers at government level and ASREN as well as on the results of the “Grids and Modeling: Application” workshop held at the St-Joseph University on the 28th and 29th of June 2011, in cooperation with EUMEDGRID-Support.

Find out more on the workshop. Download the workshop press release.

Dear EUMEDGRID-Support Community,

Welcome to the EUMEDGRID-Support Final Questionnaire!

Following the 2 previous successful editions of the EUMEDGRID-Support User Survey, the project is currently launching its third and final questionnaire.

The aim of the questionnaire is:

a)  To assess the impact of the EUMEDGRID-Support project
b)  To investigate success factors and trends for future sustainability and expansion of grid use in the Mediterranean and Sub-Sahara African countries.

Please take the last opportunity to have your say: just spend 5 minutes to complete the 10 questions below!

Thank you in advance for your time and contribution to the EUMEDGRID-Support initiative.

EUMEDGRID-Support is glad to announce that today the accreditation process for the HIAST (the Higher Institute of Applied Sciences and Technology, EUMEDGRID-Support syrian partner) CA has been successfully completed.

The accredited CP/CPS is at:

A press release on the Conference on the "Role of e-infrastructures for Climate Change Research" is now available!


All the presentations given during the conference are available for download as well!

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