Automatized Generation of Alphabets of Symbols

TL;DR

This paper presents a framework for automatically generating symbols and alphabets tailored to specific user needs, utilizing machine learning and genetic algorithms for optimization, with applications in communication, HCI, and assistive technologies.

Contribution

It introduces a novel framework for alphabet generation based on user requirements and explores the use of AI techniques for optimization and creation of symbols.

Findings

Generated alphabets can be customized for various fields.

Machine learning and genetic algorithms effectively optimize symbol sets.

Potential applications include synthetic languages and assistive interfaces.

Abstract

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.