Johan Falkenjack


Services for text simplification and analysis
Johan Falkenjack | Evelina Rennes | Daniel Fahlborg | Vida Johansson | Arne Jönsson
Proceedings of the 21st Nordic Conference on Computational Linguistics


Implicit readability ranking using the latent variable of a Bayesian Probit model
Johan Falkenjack | Arne Jönsson
Proceedings of the Workshop on Computational Linguistics for Linguistic Complexity (CL4LC)

Data driven approaches to readability analysis for languages other than English has been plagued by a scarcity of suitable corpora. Often, relevant corpora consist only of easy-to-read texts with no rank information or empirical readability scores, making only binary approaches, such as classification, applicable. We propose a Bayesian, latent variable, approach to get the most out of these kinds of corpora. In this paper we present results on using such a model for readability ranking. The model is evaluated on a preliminary corpus of ranked student texts with encouraging results. We also assess the model by showing that it performs readability classification on par with a state of the art classifier while at the same being transparent enough to allow more sophisticated interpretations.


A multivariate model for classifying texts’ readability
Katarina Heimann Mühlenbock | Sofie Johansson Kokkinakis | Caroline Liberg | Åsa af Geijerstam | Jenny Wiksten Folkeryd | Arne Jönsson | Erik Kanebrant | Johan Falkenjack
Proceedings of the 20th Nordic Conference of Computational Linguistics (NODALIDA 2015)


Classifying easy-to-read texts without parsing
Johan Falkenjack | Arne Jönsson
Proceedings of the 3rd Workshop on Predicting and Improving Text Readability for Target Reader Populations (PITR)


Features Indicating Readability in Swedish Text
Johan Falkenjack | Katarina Heimann Mühlenbock | Arne Jönsson
Proceedings of the 19th Nordic Conference of Computational Linguistics (NODALIDA 2013)