Measuring Text Comprehension for People with Reading Difficulties Using a Mobile Application

Säuberli, Andreas

doi:10.1145/3441852.3476474

Cited by 5 publications

(4 citation statements)

References 22 publications

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“…In fact, most participants indicated that both texts looked easy to read. This may reflect the fact that adults with intellectual disabilities' perceptions of reading ease are not necessarily informed by their ability to read texts with comprehension (Säuberli, 2021; Tikka, 2013). Rather, adults with intellectual disability report that visual appeal plays a prominent role in their perceptions of reading ease (Vereenooghe et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Simplified COVID‐19 guidance for adults with intellectual and developmental disabilities

Benson‐Goldberg,

Geist,

Erickson

2024

Research Intellect Disabil

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BackgroundDuring the COVID‐19 pandemic, the United States' Centers for Disease Control and Prevention (CDC) created guidance documents that were too complex to be read and understood by the majority of adults with intellectual and developmental disabilities who often read at or below a third‐grade reading level. This study explored the extent to which these adults could read and understand CDC documents simplified using Minimised Text Complexity Guidelines.MethodThis study involved 20 participants, 18–48 years of age. Participants read texts and responded to multiple‐choice items and open‐ended questions to gather information about how they interacted with and understood the texts.ResultsThe results provide initial evidence that the Minimised Text Complexity Guidelines resulted in texts that participants could read and understand.ConclusionImplications for increasing the accessibility of public health information so that it can be read and understood by adults with extremely low literacy skills are discussed.

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Section: Discussionmentioning

confidence: 99%

Simplified COVID‐19 guidance for adults with intellectual and developmental disabilities

Benson‐Goldberg,

Geist,

Erickson

2024

Research Intellect Disabil

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“…We have decided to train the baseline systems on Simplext because the text genre and the Spanish variety (peninsular Spanish) are similar. We followed Martin et al (2020) and split the corpus in 574 sentences for training, 143 for development, and 693 for testing. We used the training set for finetuning, and the development set for model selection (the test split of Simplext was not used).…”

Section: Methodsmentioning

confidence: 99%

IrekiaLFes: a New Open Benchmark and Baseline Systems for Spanish Automatic Text Simplification

Gonzalez-Dios,

Gutiérrez-Fandiño,

Cumbicus-Pineda

et al. 2022

Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)

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Automatic Text simplification (ATS) seeks to reduce the complexity of a text for a general or a target audience. In the last years, deep learning methods have become the most used systems in ATS research, but these systems need large and good-quality datasets to be evaluated. Moreover, these data are available on a large scale only for English and in some cases with restrictive licenses. In this paper, we present IrekiaLF_es, an open-license benchmark for Spanish text simplification. It consists of a document-level corpus and a sentence-level test set that has been manually aligned. We also conduct a neurolinguistically-based evaluation of the corpus in order to reveal its suitability for text simplification. This evaluation follows the Lexicon-Unification-Linearity (LeULi) model of neurolinguistic complexity assessment. Finally, we present a set of experiments and baselines of ATS systems in a zero-shot scenario.

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“…The first system for Easy Language was proposed by Suter et al (2016) and consisted of a collection of hand-crafted rules, including sentence splitting and paraphrasing. Säuberli et al (2020) published the first neural simplification approach based on the transformer architecture, together with an aligned corpus. They discussed multiple data augmentation strategies, but their results lacked fluency and content preservation.…”

Section: German Text Simplificationmentioning

confidence: 99%

Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training

Anschütz,

Oehms,

Wimmer

et al. 2023

Findings of the Association for Computational Linguistics: ACL 2023

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Automatic text simplification systems help to reduce textual information barriers on the internet. However, for languages other than English, only few parallel data to train these systems exists. We propose a two-step approach to overcome this data scarcity issue. First, we fine-tuned language models on a corpus of German Easy Language, a specific style of German. Then, we used these models as decoders in a sequence-to-sequence simplification task. We show that the language models adapt to the style characteristics of Easy Language and output more accessible texts. Moreover, with the style-specific pre-training, we reduced the number of trainable parameters in text simplification models. Hence, less parallel data is sufficient for training. Our results indicate that pre-training on unaligned data can reduce the required parallel data while improving the performance on downstream tasks.

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Measuring Text Comprehension for People with Reading Difficulties Using a Mobile Application

Cited by 5 publications

References 22 publications

Simplified COVID‐19 guidance for adults with intellectual and developmental disabilities

Simplified COVID‐19 guidance for adults with intellectual and developmental disabilities

IrekiaLFes: a New Open Benchmark and Baseline Systems for Spanish Automatic Text Simplification

Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training

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