Indoor spatial voice navigation for people with visual impairment and without visual impairment

Kai Yu Tsai, Yu Hsiu Hung, Rain Chen, Eva Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This study adopted Observational Method approach to investigate differences between visually impaired people (Group A) and not visually impaired people (Group B) in voice navigation. The objective here is to find similarities and differences between voice navigation set by the two groups and to develop two voice navigation versions for each group. In this study, indoor spatial voice navigation tasks were performed by four people with visual impairment (Group A) and four people without visual impairment (Group B), and the result showed a significant difference between these two groups in voice navigation. Group A often used signposts in the environment for orientation and descriptions of the indoor environment. Group B, on the other hand, treated themselves as the center for describing their navigation routes. According to the similarities between Groups A and B, this study developed two voice navigation versions, one for Group A and the other for Group B, and will continue investigating the accuracy, efficiency, and user satisfaction of these two versions of voice navigation for people with visual impairment.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
Pages295-300
Number of pages6
ISBN (Print)9781450366397
DOIs
Publication statusPublished - 2019
Event7th International Conference on Information and Education Technology, ICIET 2019 - Aizu-Wakamatsu, Japan
Duration: 2019 Mar 292019 Mar 31

Publication series

NameACM International Conference Proceeding Series
VolumePart F148391

Conference

Conference7th International Conference on Information and Education Technology, ICIET 2019
Country/TerritoryJapan
CityAizu-Wakamatsu
Period19-03-2919-03-31

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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