Artificial intelligence and natural language processing for easy-to-read texts

Access to information is a fundamental human right that contributes to freedom of expression and self-determination. However, information availability alone is not enough: the way in which information is expressed and presented on paper or in digital format can be extremely complicated to understand and act upon for a highly diverse set of people with varying ranges of reading, writing and understanding abilities. For a long time, artificial intelligence (AI) and natural language processing (NLP) have dedicated research efforts in the field of automatic text simplification to the development of methods to automate the production of easy-to-read texts. However, in spite of AI hype, the problem persists. Current NLP models such as large language models (LLMs) are still not well understood, and their use in the development of text simplification needs careful assessment. In this paper, having identified the need for easy-to-read, accessible texts, we provide a light overview of current methods in NLP and provide a lay explanation of several techniques applied to lexically and syntactically modified texts to make them simpler to read and understand. We conclude by raising awareness on the use of general tools to address this very challenging problem that can affect contemporary lives.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-12
DOI
https://doi.org/10.5281/zenodo.15673156
Primary Topic
Complex Systems and Time Series Analysis
Type
article
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article

Artificial intelligence and natural language processing for easy-to-read texts

Zenodo (CERN European Organization for Nuclear Research)
Complex Systems and Time Series Analysis
article

Artificial intelligence and natural language processing for easy-to-read texts

article en

Abstract

Access to information is a fundamental human right that contributes to freedom of expression and self-determination. However, information availability alone is not enough: the way in which information is expressed and presented on paper or in digital format can be extremely complicated to understand and act upon for a highly diverse set of people with varying ranges of reading, writing and understanding abilities. For a long time, artificial intelligence (AI) and natural language processing (NLP) have dedicated research efforts in the field of automatic text simplification to the development of methods to automate the production of easy-to-read texts. However, in spite of AI hype, the problem persists. Current NLP models such as large language models (LLMs) are still not well understood, and their use in the development of text simplification needs careful assessment. In this paper, having identified the need for easy-to-read, accessible texts, we provide a light overview of current methods in NLP and provide a lay explanation of several techniques applied to lexically and syntactically modified texts to make them simpler to read and understand. We conclude by raising awareness on the use of general tools to address this very challenging problem that can affect contemporary lives.

Zenodo (CERN European Organization for Nuclear Research)
Universitat Pompeu Fabra (ES)
Quality Education
Openalex Percentile: Top 46%
Complex Systems and Time Series Analysis
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