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Yuanchao Liu, Bo Pang, Bingquan Liu
Abstract:
In the pursuit of crafting eloquent essays, the strategic incorporation of idioms can significantly elevate their sophistication. However, students often struggle with this task due to difficulties in memorizing and effectively using a diverse range of expressions. This study addresses the challenge by leveraging a neural translation framework, hypothesizing that idioms could be written as pseudo-target language translations. To support our investigation, we have collected two real-life datasets.
The experimental outcomes demonstrate that our proposed approach outperforms other baseline methods in idiom recommation tasks.
Key points:
: We utilize neural translation techniques to facilitate the recommation of idioms. By treating idioms as pseudo-target language translations, our model can generate relevant and contextually appropriate expressions.
Dataset Development: Two real-life datasets are developed to trn and evaluate our approach comprehensively. These datasets provide a diverse range of text samples that include essays where idioms could be used for enhancement purposes.
Performance Evaluation: Our experimental results show promising improvements over baseline methods, indicating the effectiveness of our neural-based idiom recommation system in enhancing essay elegance through the strategic use of idioms.
Implications: This study not only contributes to the field of computational linguistics but also has practical applications for education and writing improvement programs. It suggests that with technological support like ours, students can more effectively learn and apply idiomatic expressions to elevate their essays' sophistication.
Our findings highlight the potential of neural translation frameworks in facilitating language learning and creative expression, offering a novel approach to addressing challenges faced by learners when incorporating idioms into their compositions.
This article is reproduced from: https://aclanthology.org/P19-1552
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