review · Artificial Intelligence Review
Individuals who rely on sign language face persistent barriers to daily interaction because most people do not understand sign language. Reliable automatic recognition systems are essential to overcome these divides. Recent progress across artificial intelligence, machine learning, and deep learning provides technical foundations to facilitate communication for deaf and non-verbal communities. Examining computational advancements covers key application areas, including automatic sign language interpretation, speech recognition, and text-to-speech synthesis. Evaluating the current state of technical research highlights both the potential and the practical hurdles of deploying these intelligent systems. These insights clarify the role of advanced algorithms in widening access to communication and support the future design of inclusive, accessible technological solutions.
Effective communication is fundamental to social and economic inclusion, yet sign language users routinely face exclusion in everyday interactions. Understanding how artificial intelligence and machine learning can accurately translate gestures and speech provides a vital foundation for building tools that allow non-signing individuals and deaf communities to converse freely and independently.
The evaluated technologies support assistive communication tools, such as automated sign language interpreters, speech recognition devices, and text-to-speech converters for deaf, non-verbal, and hearing users. Intended end users include individuals with communication barriers and organisations providing public services. As the abstract describes a broad survey of research challenges and opportunities rather than a deployed solution, the underlying technologies remain at an exploratory to applied research stage with no specific commercial pathway stated.
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Abstract People who often communicate via sign language are essential to our society and significantly contribute. They struggle with communication mostly because other people, who often do not understand sign language, cannot interact with them. It is necessary to develop a dependable system for automatic sign language recognition. This paper aims to provide a comprehensive review of the advancements in artificial intelligence (AI), deep learning (DL), and machine learning (ML) technologies that have been used to facilitate communication for individuals who are deaf and mute (D–M). This study explores various applications of these technologies, including sign language interpretation, speech recognition, and text-to-speech synthesis. By examining the current state of research and development in AI, ML, and DL for the D–M field, the survey sheds light on the potential and challenges faced in utilizing AI, deep learning, and ML to bridge the communication gap for the D–M community. The findings of this survey will contribute to a greater understanding of the potential impact of these technologies in improving access to communication for individuals who are D–M, thereby aiding in the development of more inclusive and accessible solutions.
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DOI: 10.1007/s10462-024-10816-0
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