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Sasayaki: augmented voice web browsing experience

Published: 07 May 2011 Publication History

Abstract

Auditory user interfaces have great Web-access potential for billions of people with visual impairments, with limited literacy, who are driving, or who are otherwise unable to use a visual interface. However a sequential speech-based representation can only convey a limited amount of information. In addition, typical auditory user interfaces lose the visual cues such as text styles and page structures, and lack effective feedback about the current focus. To address these limitations, we created Sasayaki (from whisper in Japanese), which augments the primary voice output with a secondary whisper of contextually relevant information, automatically or in response to user requests. It also offers new ways to jump to semantically meaningful locations. A prototype was implemented as a plug-in for an auditory Web browser. Our experimental results show that the Sasayaki can reduce the task completion times for finding elements in webpages and increase satisfaction and confidence.

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cover image ACM Conferences
CHI '11: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
May 2011
3530 pages
ISBN:9781450302289
DOI:10.1145/1978942
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 May 2011

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Author Tags

  1. Sasayaki
  2. auditory interface
  3. multiple voices
  4. voice augmented browsing
  5. web accessibility

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CHI '11 Paper Acceptance Rate 410 of 1,532 submissions, 27%;
Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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