Greek2MathTex: A Greek Speech-to-Text Framework for LaTeX Equations Generation

TL;DR

Greek2MathTex is an innovative speech-to-text system that converts spoken Greek mathematical expressions into LaTeX code, improving accessibility for users unfamiliar with LaTeX syntax by leveraging ASR and NLP technologies.

Contribution

This paper introduces a novel end-to-end Greek speech-to-LaTeX equations system combining ASR and NLP, with a custom evaluation metric and open-source implementation.

Findings

Successfully converts spoken Greek math to LaTeX

Integrates ASR with NLP for equation generation

Open source system available for community use

Abstract

In the vast majority of the academic and scientific domains, LaTeX has established itself as the de facto standard for typesetting complex mathematical equations and formulae. However, LaTeX's complex syntax and code-like appearance present accessibility barriers for individuals with disabilities, as well as those unfamiliar with coding conventions. In this paper, we present a novel solution to this challenge through the development of a novel speech-to-LaTeX equations system specifically designed for the Greek language. We propose an end-to-end system that harnesses the power of Automatic Speech Recognition (ASR) and Natural Language Processing (NLP) techniques to enable users to verbally dictate mathematical expressions and equations in natural language, which are subsequently converted into LaTeX format. We present the architecture and design principles of our system, highlighting key components such as the ASR engine, the LLM-based prompt-driven equations generation mechanism, as well as the application of a custom evaluation metric employed throughout the development process. We have made our system open source and available at https://github.com/magcil/greek-speech-to-math.