Shiri Azenkot (CS, University of Washington)
Thursday, 13.3.2014, 13:00
I will discuss 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 will present 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 will conclude by presenting current work on eyes-free methods for correcting speech recognition errors.
Shiri Azenkot is a PhD candidate in Computer Science at the University of Washington. Her research is in human-computer interaction and accessibility, focusing on eyes-free input on mobile devices using gestures and speech. Shiri received two Best Paper awards from ACM's ASSETS conference and has presented her work at other top HCI conferences (CHI and UIST). She received a National Science Foundation Graduate Research Fellowship and an AT&T Labs Graduate Fellowship. Shiri holds a BA in computer science from Pomona College and an MS in computer science from the University of Washington. You can find out more about her at http://shiriazenkot.com.