Decomposing Textual Information For Style Transfer

Abstract

This paper focuses on latent representations that could effectively decompose different aspects of textual information. Using a framework of style transfer for texts, we propose several empirical methods to assess information decomposition quality. We validate these methods with several state-of-the-art textual style transfer methods. Higher quality of information decomposition corresponds to higher performance in terms of bilingual evaluation understudy (BLEU) between output and human-written reformulations.

arXiv admin note: substantial text overlap with arXiv:1908.06809

References in corpus (1)

• Generating lyrics with variational autoencoder and multi-modal artist embeddings

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