ARM Based Eyes-Free Interaction Model for Mobile Reading Devices

Mobile reading devices that scan a document image and perform text to speech processing to make documents more accessible to those with visual impairments have been on the market for a few years. Interaction with these devices relies on the users understanding of the device and its position in space. Typically, the user feedback is based on the devices position and the user must interpret how to compensate based on the feedback. Blind users of technology must rely heavily on auditory and tactile interfaces to provide a robust user experience. Unfortunately, a blind users interaction with mobile devices is often limited due to the icons, buttons, and other sight-oriented expectations that designers build into such systems. The focus of this study is the development of an eyes-free interaction model that supports a voice user interface (VUI) of a mobile reading device for the blind. Research into eyes-free mobile reading devices has grown in recent years. This research has focused mainly on the image processing required by such a device, with a lower emphasis on the user interaction. In this paper, a model of a voice user interface (VUI) for a mobile reading device is presented. Three field studies with blind participants were conducted to develop and refine the model. A formal grammar is used to describe the VUI, and a stochastic Petri net was developed to model the complete user-device interaction. Evaluation and analysis of the user testing of a prototype led to empirically derived probabilities of grammar token usage for the commands that comprise the VUI.