The Web provides an abundance of knowledge and information that can reach large populations. However, the way in which information is conveyed in text (vocabulary, syntax, or text organization/structure), or presented, can make it inaccessible for many people, especially for non-native speakers, people with low literacy, and people with some type of cognitive or linguistic impairments. In this context, research on automatic text simplification, textual accessibility, and readability has the potential to produce useful knowledge, tools, and systems to make information more accessible to different populations. In the last few years, the field of Natural Language Processing has contributed considerably with research to this field, however, there are many important aspects of the automatic text simplification that need the attention of our community.
This Research Topic in Text Simplification, Accessibility, and Readability builds upon the recent success of several events in the field including the
CTTS 2021 workshop at SEPLN 2022 and the
TSAR 2022 workshop in conjunction with
EMNLP 2022. The objective of this Research Topic is to bring novel studies addressing, but not limited, to the following aspects of the simplification problem: design of appropriate evaluation metrics, development of context-aware simplification solutions, creation of appropriate language resources to support research and evaluation, deployment of simplification in real environments for real users, study of discourse factors in text simplification, identification of factors affecting the readability of a text and so forth.
We invite contributions (Review, Original Research, Brief Research Report) on the following topics but not limited to:
• Lexical simplification
• Syntactic simplification
• Modular and end-to-end TS
• Sequence-to-sequence and zero-shot TS
• Controllable TS
• Text complexity assessment
• Complex word identification and lexical complexity prediction
• Corpora, lexical resources, and benchmarks for TS
• Evaluation of TS systems