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

Fuente: arXiv
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Autores principales: Gkritzali, Evangelia, Kaliosis, Panagiotis, Galanaki, Sofia, Palogiannidi, Elisavet, Giannakopoulos, Theodoros
Formato: Preprint
Publicado: 2024
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author Gkritzali, Evangelia
Kaliosis, Panagiotis
Galanaki, Sofia
Palogiannidi, Elisavet
Giannakopoulos, Theodoros
author_facet Gkritzali, Evangelia
Kaliosis, Panagiotis
Galanaki, Sofia
Palogiannidi, Elisavet
Giannakopoulos, Theodoros
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2412_12167
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Greek2MathTex: A Greek Speech-to-Text Framework for LaTeX Equations Generation
Gkritzali, Evangelia
Kaliosis, Panagiotis
Galanaki, Sofia
Palogiannidi, Elisavet
Giannakopoulos, Theodoros
Computation and Language
Artificial Intelligence
Audio and Speech Processing
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.
title Greek2MathTex: A Greek Speech-to-Text Framework for LaTeX Equations Generation
topic Computation and Language
Artificial Intelligence
Audio and Speech Processing
url https://arxiv.org/abs/2412.12167