Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation
Abstract
Unsupervised text attribute transfer automatically transforms a text to alter a specific attribute (e.g. sentiment) without using any parallel data, while simultaneously preserving its attribute-independent content. The dominant approaches are trying to model the content-independent attribute separately, e.g., learning different attributes' representations or using multiple attribute-specific decoders. However, it may lead to inflexibility from...
Paper Details
Title
Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation
Published Date
Jan 1, 2019
Journal
Volume
32
Pages
11034 - 11044
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