2026-09-19T22:24:11Zhttps://digital.lib.washington.edu/server/oai/request

oai:digital.lib.washington.edu:1773/272202026-02-16T02:07:14Zcom_1773_4888col_1773_4909

Ladner, Richard Azenkot, Shiri 2014-11-06T23:23:04Z 2014-11-06T23:23:04Z 2014-11-06 2014 Azenkot_washington_0250E_13766.pdf http://hdl.handle.net/1773/27220 Thesis (Ph.D.)--University of Washington, 2014 I present new methods and studies that aim to improve eyes-free data entry for blind mobile device users. Currently, mobile devices are generally accessible to blind people, but text entry is almost prohibitively slow. Studies show that blind people enter text on an iPhone at a rate of just 4 words per minute. I describe Perkinput, a chording text entry method where users touch the screen with one to three fingers at a time in patterns based on Braille. Instead of soft keys, Perkinput uses concepts from signal detection theory to determine the user's input. Based on Perkinput, I developed PassChords, a touchscreen authentication method that has no audio feedback. Unlike current eyes-free input methods, PassChords doesn't echo a user's input, so it won't broadcast the user's password for others to hear. Finally, I will discuss another modality for eyes-free input: speech. I conducted a survey and a study to determine the patterns and challenges of the use of speech input for composing paragraphs on mobile devices. I conclude by presenting SpeakNSwipe, an eyes-free speech input method that facilitates correction of speech recognition errors. application/pdf en_US Copyright is held by the individual authors. blind; eyes-free; mobile devices; text entry; touchscreen Computer science computer science and engineering Eyes-Free Input on Mobile Devices Thesis Open Access open.access