Reflection-based Word Attribute Transfer

Abstract

Word embeddings, which often represent analogic relations such as king − man + woman ≈ queen, can be used to change an attribute of a word, including its gender. To transfer the gender attribute of king to obtain queen in this analogy, we subtract a difference vector man − woman from king based on the knowledge that king is male. However, developing such knowledge is significantly costly for words and attributes. In this work, we propose a novel method for word attribute transfer based on reflection mapping without an analogy-based operation. Experimental results show that our proposed method can transfer the word attributes of the given words without changing the words that are invariant with respect to the target attributes.