Abstract
Word embeddings, which often represent such ! analogic relations as kin man+ woman queen, can be used to change a word’s attribute, including its gender. For transferring king into queen in this analogy-based manner, we subtract a difference vector man woman based on the knowledge that king is male. However, developing such knowledge is very costly for words and attributes. In this work, we propose a novel method for word attribute transfer based on reflection mappings without such an analogy operation. Experimental results show that our proposed method can transfer the word attributes of the given words without changing the words that do not have the target attributes.
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CITATION STYLE
Ishibashi, Y., Sudoh, K., Yoshino, K., & Nakamura, S. (2020). Reflection-based word attribute transfer. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 51–58). Association for Computational Linguistics (ACL). https://doi.org/10.5715/jnlp.28.206
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