Writing mathematical notation requires substantial effort, diverting cognitive resources from conceptual understanding to documentation mechanics, significantly impacting individuals with fine motor disabilities (FMDs). Current limits of speech-based math technologies rely on precise dictation of math symbols and unintuitive command-based interfaces. We present a novel voice-powered math workspace, applying neuroscience insights to create an intuitive problem-solving environment. To minimize cognitive load, we leverage large language models with our novel context engine to support natural language interaction. Ultimately, we enable fluid mathematical engagement for individuals with FMDs -- freed from mechanical constraints.
Cite
@article{arxiv.2508.07576,
title = {Phoenix: A Novel Context-Aware Voice-Powered Math Equation Workspace and Editor},
author = {Kenneth Ge and Ryan Paul and Priscilla Zhang and JooYoung Seo},
journal= {arXiv preprint arXiv:2508.07576},
year = {2025}
}