6,770 research outputs found
Multilingual Unsupervised Sentence Simplification
Progress in Sentence Simplification has been hindered by the lack of
supervised data, particularly in languages other than English. Previous work
has aligned sentences from original and simplified corpora such as English
Wikipedia and Simple English Wikipedia, but this limits corpus size, domain,
and language. In this work, we propose using unsupervised mining techniques to
automatically create training corpora for simplification in multiple languages
from raw Common Crawl web data. When coupled with a controllable generation
mechanism that can flexibly adjust attributes such as length and lexical
complexity, these mined paraphrase corpora can be used to train simplification
systems in any language. We further incorporate multilingual unsupervised
pretraining methods to create even stronger models and show that by training on
mined data rather than supervised corpora, we outperform the previous best
results. We evaluate our approach on English, French, and Spanish
simplification benchmarks and reach state-of-the-art performance with a totally
unsupervised approach. We will release our models and code to mine the data in
any language included in Common Crawl
Lexical Simplification System to Improve Web Accessibility
People with intellectual, language and learning disabilities face accessibility barriers when reading texts with complex words. Following accessibility guidelines, complex words can be identified, and easy synonyms and definitions can be provided for them as reading aids. To offer support to these reading aids, a lexical simplification system for Spanish has been developed and is presented in this article. The system covers the complex word identification (CWI) task and offers replacement candidates with the substitute generation and selection (SG/SS) task. These tasks have followed machine learning techniques and contextual embeddings using Easy Reading and Plain Language resources, such as dictionaries and corpora. Additionally, due to the polysemy present in the language, the system provides definitions for complex words, which are disambiguated by a rule-based method supported by a state-of-the-art embedding resource. This system is integrated into a web system that provides an easy way to improve the readability and comprehension of Spanish texts. The results obtained are satisfactory; in the CWI task, better results were obtained than with other systems that used the same dataset. The SG/SS task results are comparable to similar works in the English language and provide a solid starting point to improve this task for the Spanish language. Finally, the results of the disambiguation process evaluation were good when evaluated by a linguistic expert. These findings represent an additional advancement in the lexical simplification of texts in Spanish and in a generic domain using easy-to-read resources, among others, to provide systematic support to compliance with accessibility guidelinesThis work was supported in part by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with UC3M in the line of Excellence of University Professors under Grant EPUC3M17, in part by the context of the V PRICIT (Regional Programme of Research and Technological Innovation), and in part by the Accessible Technologies Award-INDRA Technologies and the Fundación Universia (www.tecnologiasaccesibles.com
Lexical simplification for the systematic support of cognitive accessibility guidelines
The Internet has come a long way in recent years, contributing to the proliferation of
large volumes of digitally available information. Through user interfaces we can access
these contents, however, they are not accessible to everyone. The main users affected are
people with disabilities, who are already a considerable number, but accessibility barriers
affect a wide range of user groups and contexts of use in accessing digital information.
Some of these barriers are caused by language inaccessibility when texts contain long
sentences, unusual words and complex linguistic structures. These accessibility barriers
directly affect people with cognitive disabilities.
For the purpose of making textual content more accessible, there are initiatives such
as the Easy Reading guidelines, the Plain Language guidelines and some of the languagespecific
Web Content Accessibility Guidelines (WCAG). These guidelines provide documentation,
but do not specify methods for meeting the requirements implicit in these
guidelines in a systematic way. To obtain a solution, methods from the Natural Language
Processing (NLP) discipline can provide support for achieving compliance with the cognitive
accessibility guidelines for the language.
The task of text simplification aims at reducing the linguistic complexity of a text from
a syntactic and lexical perspective, the latter being the main focus of this Thesis. In this
sense, one solution space is to identify in a text which words are complex or uncommon,
and in the case that there were, to provide a more usual and simpler synonym, together
with a simple definition, all oriented to people with cognitive disabilities.
With this goal in mind, this Thesis presents the study, analysis, design and development
of an architecture, NLP methods, resources and tools for the lexical simplification of
texts for the Spanish language in a generic domain in the field of cognitive accessibility.
To achieve this, each of the steps present in the lexical simplification processes is studied,
together with methods for word sense disambiguation. As a contribution, different
types of word embedding are explored and created, supported by traditional and dynamic
embedding methods, such as transfer learning methods. In addition, since most of the
NLP methods require data for their operation, a resource in the framework of cognitive
accessibility is presented as a contribution.Internet ha avanzado mucho en los últimos años contribuyendo a la proliferación de
grandes volúmenes de información disponible digitalmente. A través de interfaces de
usuario podemos acceder a estos contenidos, sin embargo, estos no son accesibles a todas
las personas. Los usuarios afectados principalmente son las personas con discapacidad
siendo ya un número considerable, pero las barreras de accesibilidad afectan a un gran
rango de grupos de usuarios y contextos de uso en el acceso a la información digital. Algunas
de estas barreras son causadas por la inaccesibilidad al lenguaje cuando los textos
contienen oraciones largas, palabras inusuales y estructuras lingüísticas complejas. Estas
barreras de accesibilidad afectan directamente a las personas con discapacidad cognitiva.
Con el fin de hacer el contenido textual más accesible, existen iniciativas como las
pautas de Lectura Fácil, las pautas de Lenguaje Claro y algunas de las pautas de Accesibilidad
al Contenido en la Web (WCAG) específicas para el lenguaje. Estas pautas
proporcionan documentación, pero no especifican métodos para cumplir con los requisitos
implícitos en estas pautas de manera sistemática. Para obtener una solución, los
métodos de la disciplina del Procesamiento del Lenguaje Natural (PLN) pueden dar un
soporte para alcanzar la conformidad con las pautas de accesibilidad cognitiva relativas al
lenguaje
La tarea de la simplificación de textos del PLN tiene como objetivo reducir la complejidad
lingüística de un texto desde una perspectiva sintáctica y léxica, siendo esta última
el enfoque principal de esta Tesis. En este sentido, un espacio de solución es identificar
en un texto qué palabras son complejas o poco comunes, y en el caso de que sí hubiera,
proporcionar un sinónimo más usual y sencillo, junto con una definición sencilla, todo
ello orientado a las personas con discapacidad cognitiva.
Con tal meta, en esta Tesis, se presenta el estudio, análisis, diseño y desarrollo de
una arquitectura, métodos PLN, recursos y herramientas para la simplificación léxica de
textos para el idioma español en un dominio genérico en el ámbito de la accesibilidad
cognitiva. Para lograr esto, se estudia cada uno de los pasos presentes en los procesos
de simplificación léxica, junto con métodos para la desambiguación del sentido de las
palabras. Como contribución, diferentes tipos de word embedding son explorados y creados,
apoyados por métodos embedding tradicionales y dinámicos, como son los métodos
de transfer learning. Además, debido a que gran parte de los métodos PLN requieren
datos para su funcionamiento, se presenta como contribución un recurso en el marco de
la accesibilidad cognitiva.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José Antonio Macías Iglesias.- Secretario: Israel González Carrasco.- Vocal: Raquel Hervás Ballestero
A Review of Research-Based Automatic Text Simplification Tools
In the age of knowledge, the democratisation of information facilitated through the Internet may not be as pervasive if written language poses challenges to particular sectors of the population. The objective of this paper is to present an overview of research-based automatic text simplification tools. Consequently, we describe aspects such as the language, language phenomena, language levels simplified, approaches, specific target populations these tools are created for (e.g. individuals with cognitive impairment, attention deficit, elderly people, children, language learners), and accessibility and availability considerations. The review of existing studies covering automatic text simplification tools is undergone by searching two databases: Web of Science and Scopus. The eligibility criteria involve text simplification tools with a scientific background in order to ascertain how they operate. This methodology yielded 27 text simplification tools that are further analysed. Some of the main conclusions reached with this review are the lack of resources accessible to the public, the need for customisation to foster the individual’s independence by allowing the user to select what s/he finds challenging to understand while not limiting the user’s capabilities and the need for more simplification tools in languages other than English, to mention a few.This research was conducted as part of the Clear-Text project (TED2021-130707B-I00), funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR
Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts
There are different ways to define similarity for grouping similar texts into
clusters, as the concept of similarity may depend on the purpose of the task.
For instance, in topic extraction similar texts mean those within the same
semantic field, whereas in author recognition stylistic features should be
considered. In this study, we introduce ways to classify texts employing
concepts of complex networks, which may be able to capture syntactic, semantic
and even pragmatic features. The interplay between the various metrics of the
complex networks is analyzed with three applications, namely identification of
machine translation (MT) systems, evaluation of quality of machine translated
texts and authorship recognition. We shall show that topological features of
the networks representing texts can enhance the ability to identify MT systems
in particular cases. For evaluating the quality of MT texts, on the other hand,
high correlation was obtained with methods capable of capturing the semantics.
This was expected because the golden standards used are themselves based on
word co-occurrence. Notwithstanding, the Katz similarity, which involves
semantic and structure in the comparison of texts, achieved the highest
correlation with the NIST measurement, indicating that in some cases the
combination of both approaches can improve the ability to quantify quality in
MT. In authorship recognition, again the topological features were relevant in
some contexts, though for the books and authors analyzed good results were
obtained with semantic features as well. Because hybrid approaches encompassing
semantic and topological features have not been extensively used, we believe
that the methodology proposed here may be useful to enhance text classification
considerably, as it combines well-established strategies
Digital Comprehensibility Assessment of Simplified Texts among Persons with Intellectual Disabilities
Text simplification refers to the process of increasing the comprehensibility
of texts. Automatic text simplification models are most commonly evaluated by
experts or crowdworkers instead of the primary target groups of simplified
texts, such as persons with intellectual disabilities. We conducted an
evaluation study of text comprehensibility including participants with and
without intellectual disabilities reading unsimplified, automatically and
manually simplified German texts on a tablet computer. We explored four
different approaches to measuring comprehensibility: multiple-choice
comprehension questions, perceived difficulty ratings, response time, and
reading speed. The results revealed significant variations in these
measurements, depending on the reader group and whether the text had undergone
automatic or manual simplification. For the target group of persons with
intellectual disabilities, comprehension questions emerged as the most reliable
measure, while analyzing reading speed provided valuable insights into
participants' reading behavior.Comment: Accepted for publication at the 2024 ACM Conference on Human Factors
in Computing Systems (CHI'24
CLEAR.TEXT Enhancing the Modernization Public Sector Organizations by Deploying Natural Language Processing to Make Their Digital Content CLEARER to Those with Cognitive Disabilities
The CLEAR.TEXT project (TED2021-130707B-I00) researches how natural language processing technology can support the authoring of accessible content in Spanish for people with cognitive disabilities. Our main objective is to research, implement, deploy, evaluate, and ultimately provide robust technologies for natural language processing to support the authoring of accessible Spanish content for public sector organisations (at local, regional and national level) that is intelligible to people with cognitive disability, thereby widening their inclusion and empowerment in Europe. It is expected to impact positively the quality of life of people with cognitive disabilities, facilitating their access to educational, vocational, cultural, and social opportunities in public sector organisations.This research work is part of the CLEAR.TEXT project (TED2021-130707B-I00), funded by MCIN/AEI/10.13039/501100011033 and European Union NextGenerationEU/PRTR
Enabling text comprehensibility assessment for people with intellectual disabilities using a mobile application
In research on Easy Language and automatic text simplification, it is imperative to evaluate the comprehensibility of texts by presenting them to target users and assessing their level of comprehension. Target readers often include people with intellectual or other disabilities, which renders conducting experiments more challenging and time-consuming. In this paper, we introduce Okra, an openly available touchscreen-based application to facilitate the inclusion of people with disabilities in studies of text comprehensibility. It implements several tasks related to reading comprehension and cognition and its user interface is optimized toward the needs of people with intellectual disabilities (IDs). We used Okra in a study with 16 participants with IDs and tested for effects of modality, comparing reading comprehension results when texts are read on paper and on an iPad. We found no evidence of such an effect on multiple-choice comprehension questions and perceived difficulty ratings, but reading time was significantly longer on paper. We also tested the feasibility of assessing cognitive skill levels of participants in Okra, and discuss problems and possible improvements. We will continue development of the application and use it for evaluating automatic text simplification systems in the future
Automated Readability Assessment for Spanish e-Government Information
This paper automatically evaluates the readability of Spanish e-government websites. Specifically, the websites
collected explain e-government administrative procedures. The evaluation is carried out through the analysis of
different linguistic characteristics that are presumably associated with a better understanding of these resources.
To this end, texts from websites outside the government websites have been collected. These texts clarify the
procedures published on the Spanish Government"s websites. These websites constitute the part of the corpus
considered as the set of easy documents. The rest of the corpus has been completed with counterpart documents
from government websites. The text of the documents has been processed, and the difficulty is evaluated through
different classic readability metrics. At a later stage, automatic learning methods are used to apply algorithms to
predict the difficulty of the text. The results of the study show that government web pages show high values for
comprehension difficulty. This work proposes a new Spanish-language corpus of official e-government websites.
In addition, a large number of combined linguistic attributes are applied, which improve the identification of the
level of comprehensibility of a text with respect to classic metrics.Work supported by the Spanish Ministry of Economy, Industry and Competitiveness, (CSO2017-86747-R)
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