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Style Transfer from Non-parallel Text by Cross-Alignment
Tianxiao Shen · Tao Lei · Regina Barzilay · Tommi Jaakkola

Wed Dec 06 05:40 PM -- 05:45 PM (PST) @ Hall C
in Probabilistic Methods, Applications »

This paper focuses on style transfer on the basis of un-paired text. This is an instance of broader family of problems including machine translation, decipherment, and sentiment modification. The key technical challenge is to separate the content from desired text characteristics such as sentiment. We leverage refined cross-alignment of latent representations, across mono-lingual text corpora with different characteristics. We deliberately modify encoded examples according to their characteristics, requiring the reproduced instances to match, as a population, available examples with the altered characteristics. We demonstrate the effectiveness of the method on three tasks: sentiment modification, decipherment of word substitution cyphers, and recovery of word reodering.

Author Information

Tianxiao Shen (MIT)
Tao Lei (MIT)
Regina Barzilay (Massachusetts Institute of Technology)
Tommi Jaakkola (MIT)

Tommi Jaakkola is a professor of Electrical Engineering and Computer Science at MIT. He received an M.Sc. degree in theoretical physics from Helsinki University of Technology, and Ph.D. from MIT in computational neuroscience. Following a Sloan postdoctoral fellowship in computational molecular biology, he joined the MIT faculty in 1998. His research interests include statistical inference, graphical models, and large scale modern estimation problems with predominantly incomplete data.

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