Press release

New automatic sign language translator with groundbreaking potential developed

24 June 2014

A new intelligent system could be set to transform the lives of deaf and hearing impaired people.  International research published in the Institution of Engineering and Technology’s (IET) The Journal of Engineering highlights an Automatic Sign Language Translator (ASLT) which uses advanced technology to capture, interpret and translate sign language into “readable language”.  

With the potential for use in multiple languages and economical enough for mass production and for use on mobile devices, this (early stage) research could be set to help change the lives of deaf people worldwide.

Everyday communication is a major challenge to a great many hearing-impaired people, as well as those unable to speak, all around the world. Until now, systems devised to remove these barriers to communication have had limited capabilities in terms of target languages or ease of use.

Researchers from Malaysia and New Zealand have developed theoretical fundamentals of sign language interpretation based on image processing and pattern recognition, which they believe will result in a portable, efficient and affordable ASLT for a wide variety of sign and written languages.

The system was tested on gestures and signs representing both isolated words and continuous sentences of Malaysian sign language, with a high degree of recognition accuracy and speed.

“At the heart of the ASLT are real-time image processing and computational intelligence methods,” said researcher Professor Rini Akmeliawati, of Malaysia’s IIUM University.

“We developed a novel approach, leading to efficient detection and tracking of face, hands and upper body trajectories of a signer. By combining it with our tools for artificial intelligence-based matching between these sign trajectories and elements of a large database of images and video recordings of native signers, we have achieved a fast and flexible automatic sign language translation system. The system’s potential lies in its technologically advanced algorithms and structure, which can be adapted to a multitude of the world’s sign languages.”

Media enquiries to:

Hannah Kellett
External Communications Manager

Tel: +44 (0)1438 767336
Mob: +44 (0)7738 602426
Email: HKellett@theiet.org

Notes to editors:

About the authors
Professor Rini Akmeliawati is Chair of Mechatronics at the Faculty (Kulliyyah) of Engineering at the International Islamic University of Malaysia (IIUM). Among her partners were researchers from Massey University’s School of Engineering & Advanced Technology, New Zealand; Vietnam’s RMIT University; IIUM’s Mechatronics Engineering Department, and Monash University Malaysia’s School of Engineering.

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