no code implementations • READI (LREC) 2022 • Evelina Rennes, Marina Santini, Arne Jonsson
The toolkit allows user to selectively decide the types of simplification that meet the specific needs of the target audience they belong to.
no code implementations • NoDaLiDa 2021 • Evelina Rennes, Arne Jönsson
Basic-level terms have been described as the most important to human categorisation.
no code implementations • LREC 2022 • Julius Monsen, Evelina Rennes
We present results from a study investigating how users perceive text quality and readability in extractive and abstractive summaries.
no code implementations • LREC 2022 • Daniel Holmer, Evelina Rennes
Deciding if a word is easy or difficult is not a trivial task, since it depends on characteristics of the word in itself as well as the reader, but it can be facilitated by the help of a corpus annotated with word frequencies and reading proficiency levels.
no code implementations • LREC 2020 • Evelina Rennes
Parallel monolingual resources are imperative for data-driven sentence simplification research.
no code implementations • LREC 2020 • Marina Santini, Arne Jonsson, Evelina Rennes
In this paper, we propose visualizing results of a corpus-based study on text complexity using radar charts.
no code implementations • WS 2016 • Sarah Albertsson, Evelina Rennes, Arne J{\"o}nsson
The first method (M1) was originally developed for the task of text reuse detection, measuring sentence similarity by a modified version of a TF-IDF vector space model.
no code implementations • LREC 2014 • Evelina Rennes, Arne J{\"o}nsson
By the usage of an eye tracking camera, we have studied the nature of four different types of cohesion errors occurring in extraction based summaries.