Ion Madrazo Azpiazu and Maria Soledad Pera. 2019. “Is cross‐lingual readability assessment possible?”. In Journal of the Association for Information Science and Technology (JASIST 2019).
Most research efforts related to automatic readability assessment focus on the design of strategies that apply to a specific language. These state‐of‐the‐art strategies are highly dependent on linguistic features that best suit the language for which they were intended, constraining their adaptability and making it difficult to determine whether they would remain effective if they were applied to estimate the level of difficulty of texts in other languages. In this article, we present the results of a study designed to determine the feasibility of a cross‐lingual readability assessment strategy. For doing so, we first analyzed the most common features used for readability assessment and determined their influence on the readability prediction process of 6 different languages: English, Spanish, Basque, Italian, French, and Catalan. In addition, we developed a cross‐lingual readability assessment strategy that serves as a means to empirically explore the potential advantages of employing a single strategy (and set of features) for readability assessment in different languages, including interlanguage prediction agreement and prediction accuracy improvement for low‐resource languages.