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Is cross‐lingual readability assessment possible?

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  • Ion Madrazo Azpiazu
  • Maria Soledad Pera

Abstract

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.

Suggested Citation

  • Ion Madrazo Azpiazu & Maria Soledad Pera, 2020. "Is cross‐lingual readability assessment possible?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(6), pages 644-656, June.
    • Handle: RePEc:bla:jinfst:v:71:y:2020:i:6:p:644-656
    DOI: 10.1002/asi.24293
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    References listed on IDEAS

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    1. Bonsall, Samuel B. & Leone, Andrew J. & Miller, Brian P. & Rennekamp, Kristina, 2017. "A plain English measure of financial reporting readability," Journal of Accounting and Economics, Elsevier, vol. 63(2), pages 329-357.
    2. Fang, Bin & Ye, Qiang & Kucukusta, Deniz & Law, Rob, 2016. "Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics," Tourism Management, Elsevier, vol. 52(C), pages 498-506.
    3. Joel Denning & Maria Soledad Pera & Yiu-Kai Ng, 2016. "A readability level prediction tool for K-12 books," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(3), pages 550-565, March.
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