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dc.contributor.advisorLadner, Richarden_US
dc.contributor.authorAzenkot, Shirien_US
dc.date.accessioned2014-11-06T23:23:04Z
dc.date.available2014-11-06T23:23:04Z
dc.date.submitted2014en_US
dc.identifier.otherAzenkot_washington_0250E_13766.pdfen_US
dc.identifier.urihttp://hdl.handle.net/1773/27220
dc.descriptionThesis (Ph.D.)--University of Washington, 2014en_US
dc.description.abstractI 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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoen_USen_US
dc.rightsCopyright is held by the individual authors.en_US
dc.subjectblind; eyes-free; mobile devices; text entry; touchscreenen_US
dc.subject.otherComputer scienceen_US
dc.subject.othercomputer science and engineeringen_US
dc.titleEyes-Free Input on Mobile Devicesen_US
dc.typeThesisen_US
dc.embargo.termsOpen Accessen_US


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