Abstract
This research is dedicated to the simplification of Spanish-language financial texts to enhance accessibility for screen readers. We present a qualitative and quantitative analysis of the text simplification process, employing a set of Spanish simplification rules and metrics. Our study evaluates the outcomes resulting from the application of three distinct financial datasets to four pre-trained models. The primary objective is to identify the most effective models for text simplification and determine those warranting further investment through fine-tuning and training. This study contributes to improving the accessibility and comprehensibility of financial documents for individuals with visual impairments.
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