A Bayesian Framework for Modeling Accents in Handwriting

Accent in speech is defined as a distinctive mode of pronunciation that is unique to a geographical region. In a similar way, we define accent in handwriting as distinctive writing characteristics that are unique to a group of people sharing a common native script. In other words, we postulate that a group of people with a common native script will share certain traits in their handwriting that can be ascertained when they write in a different script. In this paper, we establish the existence of accents in handwriting using a hierarchical Bayesian framework. We then demonstrate that the unique trait in handwriting that arises out of the writer's native script is indigenous to that script, which is perceivable when writing in a different script. As a consequence, the ability to identify a person's native script based on the person's handwriting style in another script is introduced. We validated the approach by performing experiments on the UNIPEN dataset, and the experiments lend credibility to our model.