Ooze - Handwritten Text Generator

Abstract

In this paper we show how Generative Adversarial Network (Goodfellow et al., 2014), more specifically Cycle-GAN(Zhu et al., 2017), can be used for Human like handwriting generation with output size up to a text line. The methodology used in Cycle-GAN is to establish translation between two different domains (e.g., connection between image of horse and zebra), extending this methodology to establishment of translation between machine printed text and handwritten text is mentioned in this paper. The neural network used in this paper is trained for dataset created by the author and can be trained with another dataset.