Personalized sentence generation using generative adversarial networks with author-specific word usage

Understand

The author-specific word usage is a vital feature to let readers perceive the writing style of the author.

• In this work, a personalized sentence generation method based on generative adversarial networks (GANs) is proposed to cope with this issue.
• The frequently used function word and content word are incorporated not only as the input features but also as the sentence structure constraint for the GAN training.
• For the sentence generation with the related topics decided by the user, the Named Entity Recognition (NER) information of the input words is also used in the network training.