论文标题

向语言学习者进行跨语性定义生成

Toward Cross-Lingual Definition Generation for Language Learners

论文作者

Kong, Cunliang, Yang, Liner, Zhang, Tianzuo, Fan, Qinan, Liu, Zhenghao, Chen, Yun, Yang, Erhong

论文摘要

自动生成字典定义可以证明对语言学习者有用。但是,这仍然是跨语性定义生成的具有挑战性的任务。在这项工作中,我们建议用英语生成各种语言的单词的定义。为了实现这一目标,我们基于公开可用的审计语言模型提出了一种简单而有效的方法。在这种方法中,在英语数据集中训练后,模型可以直接应用于其他语言。我们证明了这种方法对零发定义生成的有效性。对新建数据集的实验和手动分析表明,我们的模型具有很强的跨语性转移能力,并且可以为中文单词产生流利的英语定义。我们进一步衡量生成和参考定义的词汇复杂性。结果表明,生成的定义要简单得多,更适合语言学习者。

Generating dictionary definitions automatically can prove useful for language learners. However, it's still a challenging task of cross-lingual definition generation. In this work, we propose to generate definitions in English for words in various languages. To achieve this, we present a simple yet effective approach based on publicly available pretrained language models. In this approach, models can be directly applied to other languages after trained on the English dataset. We demonstrate the effectiveness of this approach on zero-shot definition generation. Experiments and manual analyses on newly constructed datasets show that our models have a strong cross-lingual transfer ability and can generate fluent English definitions for Chinese words. We further measure the lexical complexity of generated and reference definitions. The results show that the generated definitions are much simpler, which is more suitable for language learners.

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