The application of natural language processing to augmentative and alternative communication

Area of Science:

• Computer Science
• Rehabilitation Engineering
• Speech and Language Pathology

Background:

• Augmentative and Alternative Communication (AAC) devices assist individuals with communication impairments.
• Natural Language Processing (NLP) offers potential for enhancing AAC functionalities.
• Current AAC systems face limitations in naturalness and efficiency.

Purpose of the Study:

• To review the current state-of-the-science of NLP applications in AAC.
• To identify key advancements in NLP for AAC interface design and word prediction.
• To explore future directions for NLP in developing next-generation AAC technologies.

Main Methods:

• Systematic literature review of NLP techniques applied to AAC.
• Analysis of research focusing on NLP-driven interface design.
• Examination of studies on NLP-based word prediction algorithms for AAC.

Main Results:

• NLP has significantly improved AAC interface intuitiveness and user experience.
• Advanced NLP models enhance word prediction accuracy and speed in AAC.
• Emerging NLP applications show promise for more context-aware and personalized AAC.

Conclusions:

• NLP is a transformative technology for AAC, enhancing current capabilities.
• Continued research in NLP will drive the development of more sophisticated AAC systems.
• Future AAC technologies will likely leverage sophisticated NLP for seamless communication.