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arXiv · 1711.09395

Improved Neural Text Attribute Transfer with Non-parallel Data

Igor Melnyk·Cicero Nogueira dos Santos·Kahini Wadhawan·Inkit Padhi·Abhishek Kumar
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Abstract

Text attribute transfer using non-parallel data requires methods that can perform disentanglement of content and linguistic attributes. In this work, we propose multiple improvements over the existing approaches that enable the encoder-decoder framework to cope with the text attribute transfer from non-parallel data. We perform experiments on the sentiment transfer task using two datasets. For both datasets, our proposed method outperforms a strong baseline in two of the three employed evaluation metrics.

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Igor Melnyk, Cicero Nogueira dos Santos, Kahini Wadhawan, Inkit Padhi, Abhishek Kumar. 2017-11-26. Improved Neural Text Attribute Transfer with Non-parallel Data. https://arxiv.org/abs/1711.09395

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