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.