TY - JOUR
T1 - Is cross-lingual readability assessment possible?
AU - Madrazo Azpiazu, Ion
AU - Pera, Maria Soledad
N1 - Publisher Copyright:
© 2019 ASIS&T
PY - 2020/6/1
Y1 - 2020/6/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85070974106
U2 - 10.1002/asi.24293
DO - 10.1002/asi.24293
M3 - Article
AN - SCOPUS:85070974106
SN - 2330-1635
VL - 71
SP - 644
EP - 656
JO - Journal of the Association for Information Science and Technology
JF - Journal of the Association for Information Science and Technology
IS - 6
ER -