Abstract
Automatic generation systems for language learning, as well as computer-assisted language learning (CALL) systems have evolved according to the demands of teachers and students. For those systems, it is important to review Natural Language Processing (NLP) techniques aimed at that task, considering other disciplines such as Computational Sciences, Computational Linguistics and Creativity for teaching and learning other languages. This work is twofold. First, it presents an effort to review the main characteristics, methods and techniques used for its implementation, relevance and profitability of the systems developed in recent years; considering the importance to develop the abilities to recognize literal use of language as well as its non literal use, particularly metaphorical expressions in the natural process of learning a new language. For the second part, it presents a system that, based on the Trofi dataset (Gao G. et al. 2018), is able to generate different exercises to strengthen the students’ abilities to read and recognize the use of some verbs in literal and non-literal contexts.
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Becerril, E.O., Calvo, H. (2022). Techniques for Generating Language Learning Resources: A System for Generating Exercises for the Differentiation of Literal and Metaphorical Context. In: Pichardo Lagunas, O., Martínez-Miranda, J., Martínez Seis, B. (eds) Advances in Computational Intelligence. MICAI 2022. Lecture Notes in Computer Science(), vol 13613. Springer, Cham. https://doi.org/10.1007/978-3-031-19496-2_14
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