Publications & Research

This literature review overviews sign language and discusses the different technologies used for text-to-sign conversion systems. The paper evaluates computer-based text processing methods, machine translation techniques (rule-based, corpus-based, and neural architectures), and sign synthesis approaches (avatar animation, video concatenation, neural generation). The paper compares each method's strengths and limitations and presents quantitative performance data from recent systems.

This paper presents SignSinhala, a hybrid machine learning framework designed to translate English text into Sinhala Sign Language. This system integrates natural language processing, neural gesture prediction, and video synthesis for sign language generation. Our novel approach incorporates grammar-aligned text preprocessing, synonym searching for out-of-vocabulary tokens, and a fingerspelling dataset leveraged to improve translation robustness.

This paper reviews a past decade of developments in Sri Lankan sign language recognition and translation technology, both in terms of sensor-based and vision-based solutions to sign gesture recognition and Sinhala text and speech to Sri Lankan sign language conversion systems. Additionally, the paper analyzes the unique linguistic features of Sri Lankan sign language and the structure and limitations of available datasets. Comparative analysis highlights the strengths and drawbacks of each system, such as hardware dependency, environmental sensitivity, expressiveness, and scalability.

All human beings need equal opportunities in the world. Communication is one of the essential things for humans to do in their day-to-day activities like learning, expressing their feelings, and exchanging their ideas. However, over 5% of the world’s population, or 430 million individuals, including 34 million children, require healing to manage disabling hearing loss. Commonly referred to as being deaf. (WHO, 2024). They often find it challenging to share their thoughts with hearing people through spoken language. So, they rely on unique forms of communication, including hand gestures and facial expressions known as sign language