{"id":{"repo_id":"washington","oai_identifier":"oai:digital.lib.washington.edu:1773/27220"},"canonical_url":"https://search.dev.ndltd.org/etd/washington/oai:digital.lib.washington.edu:1773/27220","repository":{"repo_id":"washington","name":"University of Washington","base_url":"https://digital.lib.washington.edu/server/oai/request"},"display":{"title":"Eyes-Free Input on Mobile Devices","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Azenkot, Shiri"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Ladner, Richard"],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-11-06","date_published":"2014-11-06","updated_at":"2026-07-24T05:58:14Z","subjects":["blind; eyes-free; mobile devices; text entry; touchscreen"],"languages":["en_US"],"rights":["Copyright is held by the individual authors."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1773/27220","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Ladner, Richard"]},{"key":"dc:creator","label":"Author","values":["Azenkot, Shiri"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-11-06T23:23:04Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-11-06T23:23:04Z"]},{"key":"dc:date.issued","label":"Date","values":["2014-11-06"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["blind; eyes-free; mobile devices; text entry; touchscreen"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_US"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright is held by the individual authors."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["Azenkot_washington_0250E_13766.pdf"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1773/27220"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (Ph.D.)--University of Washington, 2014"]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Eyes-Free Input on Mobile Devices"]}]}],"canonical_facts":{"dc:contributor.advisor":["Ladner, Richard"],"dc:creator":["Azenkot, Shiri"],"dc:date.accessioned":["2014-11-06T23:23:04Z"],"dc:date.available":["2014-11-06T23:23:04Z"],"dc:date.issued":["2014-11-06"],"dc:description":["Thesis (Ph.D.)--University of Washington, 2014"],"dc:description.abstract":["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."],"dc:format.mimetype":["application/pdf"],"dc:identifier.other":["Azenkot_washington_0250E_13766.pdf"],"dc:identifier.uri":["http://hdl.handle.net/1773/27220"],"dc:language.iso":["en_US"],"dc:rights":["Copyright is held by the individual authors."],"dc:subject":["blind; eyes-free; mobile devices; text entry; touchscreen"],"dc:title":["Eyes-Free Input on Mobile Devices"],"dc:type":["Thesis"]},"updated_at":"2026-07-24T05:58:14Z"}