Abstract
Advances in artificial intelligence over the past decade, combined with increasingly affordable computing power, have made new approaches to accessibility possible. In this chapter we describe three ongoing projects in the Department of Computer Science at North Carolina State University. CAVIAR, a Computer-vision Assisted Vibrotactile Interface for Accessible Reaching, is a wearable system that aids people with vision impairment (PWVI) in locating, identifying, and acquiring objects within reach; a mobile phone worn on the chest processes video input and guides the user’s hand to objects via a wristband with vibrating actuators. TIKISI (Touch It, Key It, Speak It), running on a tablet, gives PWVI the ability to explore maps and other forms of graphical information. AccessGrade combines crowd-sourcing with machine learning techniques to predict the accessibility of Web pages.
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The ellipses in the overview Lenora hears indicate prosodic cues. The prosody of speech output affords speech interface users a familiar way of indicating importance in a long stream of speech. The ellipses, which represent pauses, are also exactly the locations where a small audio tone or click can be inserted for further enforcement [23]. The silencing command is similar to that in Gravitas [17] to pause the focus at the given node, and then begin exploring from that point.
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Bahram, S., Chakraborty, A., Ravindran, S., St. Amant, R. (2013). Intelligent Interaction in Accessible Applications. In: Biswas, P., Duarte, C., Langdon, P., Almeida, L., Jung, C. (eds) A Multimodal End-2-End Approach to Accessible Computing. Human–Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-4471-5082-4_5
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