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Mobile GIS as if field users mattere...
~
Hunter, Andrew James Simpson.
Mobile GIS as if field users mattered: Small is ubiquitous but can speech be recognized?
紀錄類型:
書目-電子資源 : 單行本
正題名/作者:
Mobile GIS as if field users mattered: Small is ubiquitous but can speech be recognized?/
作者:
Hunter, Andrew James Simpson.
面頁冊數:
177 p.
附註:
Source: Masters Abstracts International, Volume: 42-05, page: 1427.
Contained By:
Masters Abstracts International42-05.
標題:
Information Science. -
電子資源:
Download fulltext (下載全文)
ISBN:
061287284X
Mobile GIS as if field users mattered: Small is ubiquitous but can speech be recognized?
Hunter, Andrew James Simpson.
Mobile GIS as if field users mattered: Small is ubiquitous but can speech be recognized?
- 177 p.
Source: Masters Abstracts International, Volume: 42-05, page: 1427.
Thesis (M.Sc.)--University of Calgary (Canada), 2003.
The research asked whether Mobile GIS incorporating speech recognition was a viable tool for locating defects in the streetscape. The Geography Markup Language for encoding spatial information was used to implement an application schema for street condition surveys. Speech accuracy exceeded 95% in environments that were quiet or constantly loud. However, for tests where the noise level varied, recognition accuracy plummeted to 58%. Accuracy of captured defects was determined while "standing", "walking", "cycling" and "driving". Errors ranged from 0.27m to 12.50m at the 95% confidence interval. A web-based questionnaire indicated that municipal geographic information users are unhappy with the quality of their data, and as yet do not require data in real-time. Future research involves investigating alternative ways of capturing spoken commands, the effect that mobile computing has on the cognitive abilities of the user, and wireless connectivity required for real time access to spatial data.
ISBN: 061287284XSubjects--Topical Terms:
1000005592
Information Science.
Mobile GIS as if field users mattered: Small is ubiquitous but can speech be recognized?
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Source: Masters Abstracts International, Volume: 42-05, page: 1427.
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The research asked whether Mobile GIS incorporating speech recognition was a viable tool for locating defects in the streetscape. The Geography Markup Language for encoding spatial information was used to implement an application schema for street condition surveys. Speech accuracy exceeded 95% in environments that were quiet or constantly loud. However, for tests where the noise level varied, recognition accuracy plummeted to 58%. Accuracy of captured defects was determined while "standing", "walking", "cycling" and "driving". Errors ranged from 0.27m to 12.50m at the 95% confidence interval. A web-based questionnaire indicated that municipal geographic information users are unhappy with the quality of their data, and as yet do not require data in real-time. Future research involves investigating alternative ways of capturing spoken commands, the effect that mobile computing has on the cognitive abilities of the user, and wireless connectivity required for real time access to spatial data.
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