Automatized Generation of Alphabets of Symbols
This addresses the need for tailored communication systems in diverse fields, though it appears incremental as it builds on existing optimization techniques without demonstrating concrete results.
The paper tackles the problem of generating custom symbol alphabets based on user requirements like medium and information type, proposing a framework and exploring its application to shorthand writing systems. It suggests using machine learning and genetic algorithms for input gathering and optimization, with potential applications ranging from synthetic languages to multimodal interfaces for elderly care and disability assistance.
In this paper, we discuss the generation of symbols (and alphabets) based on specific user requirements (medium, priorities, type of information that needs to be conveyed). A framework for the generation of alphabets is proposed, and its use for the generation of a shorthand writing system is explored. We discuss the possible use of machine learning and genetic algorithms to gather inputs for generation of such alphabets and for optimization of already generated ones. The alphabets generated using such methods may be used in very different fields, from the creation of synthetic languages and constructed scripts to the creation of sensible commands for multimodal interaction through Human-Computer Interfaces, such as mouse gestures, touchpads, body gestures, eye-tracking cameras, and brain-computing Interfaces, especially in applications for elderly care and people with disabilities.