  Generating synthetic images is an art which emulates the natural process of
image generation in a closest possible manner. In this work, we exploit such a
framework for data generation in handwritten domain. We render synthetic data
using open source fonts and incorporate data augmentation schemes. As part of
this work, we release 9M synthetic handwritten word image corpus which could be
useful for training deep network architectures and advancing the performance in
handwritten word spotting and recognition tasks.
