UKZN Graduate Develops AI System to Translate South African Sign Language into Speech
Read more
IOL
iol.co.za

UKZN Graduate Develops AI System to Translate South African Sign Language into Speech

A graduate of the University of KwaZulu-Natal (UKZN) has created an artificial intelligence-based system capable of translating South African Sign Language (SASL) into real-time voice accompaniment.

The goal of this development is to assist people with hearing impairments in overcoming communication barriers. Akhil Hansraj developed the SASL-to-Speech Translation System as part of his undergraduate degree project in Computer Engineering.

This computer vision-based system utilizes a specially designed AI model alongside an established machine learning framework to track body landmarks and recognize signs in real time. The system was trained on a specialized dataset pertaining to SASL and can identify individual letters and words before converting interpreted signs into speech via a speech synthesis model.

Overcoming Difficulties

According to Hansraj's academic supervisor, Dr. Sulaiman Patel, this project is one of the first assistive technology projects in the Electrical, Electronic, and Computer Engineering (EECE) discipline at UKZN that specifically focused on the dialect of South African Sign Language.

SASL was recently recognized as the eleventh official language of South Africa, while many international sign language translation systems focus on American Sign Language. For Hansraj, this project held deep personal motivation, as both of his parents were born with hearing impairments and faced communication challenges in daily life.

Hansraj noted: 'My parents face communication barriers in everyday settings such as banks, government offices, and municipal offices. My sister and I often had to accompany them to speak on their behalf.'

He emphasized that a fully ready version of the technology could allow people to communicate more independently. 'A production-ready system would enable these individuals to communicate more easily and effectively, without the need for the other party to learn SASL,' he added.

Despite this outstanding achievement, Hansraj's path to graduation was not easy. Patel reported that in the second semester of 2025, Hansraj experienced mental health issues and required an extension for his first project submission. With Patel's support, including referrals to student counseling and regular check-ins, Hansraj was able to regain momentum on the project. His efforts ultimately earned him high praise from EECE for his final project.

Hansraj also shared that he enjoyed the design modules the most during his studies because they allowed him to apply theoretical knowledge to practical, meaningful projects. He also named the 'Data Communications' and 'Internet Engineering' modules, taught by Professor Tahmid Qazi, as his favorites.

Facing financial difficulties and having one final module in 2026, Hansraj received a recommendation from Qazi for an interview at a local company. He found a job and balanced it with his studies.

Future Plans for Technology Development

After obtaining his bachelor's degree in engineering, Hansraj intends to continue working on his sign language translation project. His primary focus will be on improving the system's ability to recognize words and generate more coherent and fluid speech.

In the long term, he plans to build a career in software, network technologies, or artificial intelligence and machine learning. Hansraj expressed gratitude to his parents, uncle, sister, Patel, friend Amil Maharaj, and his roommate, girlfriend, and university colleagues for their support throughout the journey. Besides his studies, he enjoys gaming, keeping up with technological developments, and working on his own programming projects. He also thanks UKZN for the lessons learned and the opportunity to experience university life.

Similar stories

Kenyan innovators use robotics to provide sign language education access
Read more
cgtn.com

Kenyan innovators use robotics to provide sign language education access

In Kenya, a young team of innovators is applying robotics to overcome one of the obstacles faced by hearing-impaired students: access to education in sign language.

Although this technology is still in the development stage, its creators believe that in the future it could make technical subjects more accessible for students with hearing loss.

In the classroom in Nairobi, communication largely occurs through gestures. However, for deaf students, mastering complex disciplines presents a particular challenge, especially when the vocabulary needed to explain mathematics, science, or technology is absent from the signs they know.

Eva Avino, a teacher at the secondary school for the deaf Kasarani Treeside Secondary School for the Deaf, noted: 'I teach physics, and most of the time we understand that the concepts we teach and the way I can express the concept become problematic at some point due to the signs and vocabulary required to express that concept.'

This is the problem that the Kenyan startup ZeroBionic is trying to solve. In their laboratory in Nairobi, engineers are training machines to communicate in sign language.

For co-founder Nora Kimati, the idea started with something much simpler. Kimati said: 'We started with basic robotic arms. Since sign language is entirely based on hands, we decided to start with hands and see how it would go. Then we received feedback that a lot in sign language depends on it.'

She continued: 'For example, performing this means more than five different things in a specific sign language, depending on your facial expressions. That's when we decided to build a full humanoid, including the face, including the eyes, including everything, to capture all the non-verbal cues that are currently present.'

However, teaching a machine signs requires more than just hardware; it requires data. When ZeroBionic began searching for African sign language datasets, the team reported that there was very little material available for work.

In the lab, every movement is captured, recorded, and converted into data that can train the system. ZeroBionic claims that the current task is to make the technology smarter, more accurate, and more useful in the real world. For students watching this technology develop, it symbolizes something more than just a machine.

Popular