Relevant Phrase Generation for Language Learners
Davide Pinti
Relevant Phrase Generation for Language Learners.
Rel. Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2023
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Abstract
In recent times Artificial Intelligence, Natural Language Processing (NLP) especially, has spread widely. Nowadays, most people use it, either directly or indirectly, and you can find it almost everywhere: from social networks, to generating images based on text prompts, to the automatic grammar checker of written text. In the field of NLP, the generation of text through large language models (LLMs) is becoming more and more dominant, especially since the release of the Transformer in 2017. The objective of this study was to leverage the powerful tools of NLP to generate contextually appropriate English sentences for language learners, when given a specific English keyword as input.
Other papers in the field of Intelligent Computer-Assisted Language Learning (ICALL) have generated examples for language learners by either retrieval- or ranking-based models, but this is the first time generative language models have been used in this context
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