论文标题
Wordalchemy：基于变压器的反向字典
WordAlchemy: A transformer-based Reverse Dictionary
论文作者
论文摘要
反向字典以目标单词的描述为输入，并返回适合描述的单词。反向字典对于新语言学习者，无症患者和解决常见的丁格语问题（Lethologica）很有用。目前，没有任何反向字典提供商支持任何印度语言。我们提出了一种新颖的开源跨语言反向词典系统，并支持印度语言。在本文中，我们提出了一种基于变压器的深度学习方法，以解决使用MT5模型的现有系统所面临的局限性。该体系结构使用翻译语言建模（TLM）技术，而不是传统的Bert掩盖语言建模（MLM）技术。
A reverse dictionary takes a target word's description as input and returns the words that fit the description. Reverse Dictionaries are useful for new language learners, anomia patients, and for solving common tip-of-the-tongue problems (lethologica). Currently, there does not exist any Reverse Dictionary provider with support for any Indian Language. We present a novel open-source cross-lingual reverse dictionary system with support for Indian languages. In this paper, we propose a transformer-based deep learning approach to tackle the limitations faced by the existing systems using the mT5 model. This architecture uses the Translation Language Modeling (TLM) technique, rather than the conventional BERT's Masked Language Modeling (MLM) technique.
