Exploring the Use of Speech Input by Blind People on ... - Washington

3. Error detection – an easier way to detect errors such as
spelling mistakes, letter case errors, and low-confidence
ASR output.
4. Auto-correct – a study <strong>of</strong> how well auto-correct works
for nonvisual use, and a way to make it more effective.
7. Conclusion
We have explored <strong>the</strong> patterns and challenges <strong>of</strong> speech input for
blind mobile device users through a survey and a laboratory
study. We found that speech input is a popular alternative to <strong>the</strong>
on-screen keyboard with VoiceOver, yet people face challenges
when reviewing and editing a speech recognizer’s output, <strong>of</strong>ten
resorting to using <strong>the</strong> keyboard. We hope this work will enable
text entry researchers to better understand <strong>the</strong> patterns and
challenges <strong>of</strong> current nonvisual text entry, and spur fur<strong>the</strong>r
research in <strong>the</strong> on nonvisual speech input.
8. ACKNOWLEDGMENTS
We thank Gina-Anne Levow, Richard Ladner, Rochelle H. Ng,
and Simone Schaffer. This work was supported in part <strong>by</strong> AT&T
Labs and <strong>the</strong> National Science Foundation under grant No.
1116051.
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