Toward Cross-Lingual Definition Generation for Language Learners
This work addresses the problem of providing accessible dictionary definitions for language learners, though it is incremental as it builds on existing pretrained models.
The paper tackles cross-lingual definition generation by proposing a method to generate English definitions for words in other languages, such as Chinese, using pretrained language models, and shows that the generated definitions are simpler and more suitable for language learners.
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.