Kathleen J. Price
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Publications by Kathleen J. Price (bibliography)
» 2008 «
Price, Kathleen J. and Sears, Andrew (2008): Performance-based functional assessment: an algorithm for measuring physical capabilities. In: Tenth Annual ACM SIGACCESS Conference on Assistive Technologies 2008. pp. 217-224. Available online
“The description of users with motor limitations is a significant dilemma for accessibility researchers and system designers alike. Current practice is to use descriptors such as medical diagnoses to represent a person's physical capabilities. This solution is not adequate due to similarities in functional capabilities between diagnoses as well as differences in capabilities within a diagnosis. An alternative is user self-reporting or observation by another person. These solutions are also problematic because they rely on individual interpretation of capabilities. The current research focuses on defining an objective, quantitative and repeatable methodology for assessing a person's physical capabilities in relation to use of computer technology. Results from this initial study are encouraging, including the development of a model which accounts for up to 85% of the variance in user capabilities.”
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» 2007 «
Lin, Min, Goldman, Rich, Price, Kathleen J., Sears, Andrew and Jacko, Julie A. (2007): How do people tap when walking? An empirical investigation of nomadic data entry. In International Journal of Human-Computer Studies, 65 (9) pp. 759-769
“When mobile devices are used on the move, a user's limited visual resources are split between interacting with the mobile devices and maintaining awareness of the surrounding environment. In this study, we examined stylus-based tapping operations on a PDA under three mobility situations: seated, walking on a treadmill, and walking through an obstacle course. The results revealed that Fitts' Law continues to be effective even under the most challenging obstacle course condition. While target selection times did not differ between the various mobility conditions, overall task completion times, error rates, and several measures of workload differed significantly. Diminished performance under the obstacle course condition was attributed to increased demands on attention associated with navigating through the obstacle course. Results showed that the participants in the obstacle course condition were able to tap on a 6.4 mm-diameter target with 90% accuracy, but they reduced their walking speed by 36% and perceived an increased workload. Extending earlier research, we found that treadmill-based conditions were able to generate representative data for task selection times, but accuracy differed significantly from the more realistic obstacle course condition.”
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» 2006 «
Price, Kathleen J., Lin, Min, Feng, Jinjuan, Goldman, Rich, Sears, Andrew and Jacko, Julie A. (2006): Motion does matter: an examination of speech-based text entry on the move. In Universal Access in the Information Society, 4 (3) pp. 246-257
“Desktop interaction solutions are often inappropriate for mobile devices due to small screen size and portability needs. Speech recognition can improve interactions by providing a relatively hands-free solution that can be used in various situations. While mobile systems are designed to be transportable, few have examined the effects of motion on mobile interactions. This paper investigates the effect of motion on automatic speech recognition (ASR) input for mobile devices. Speech recognition error rates (RER) have been examined with subjects walking or seated, while performing text input tasks and the effect of ASR enrollment conditions on RER. The obtained results suggest changes in user training of ASR systems for mobile and seated usage.”
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» 2005 «
Fischer, Arnout R. H., Price, Kathleen J. and Sears, Andrew (2005): Speech-Based Text Entry for Mobile Handheld Devices: An Analysis of Efficacy and Error Correction Techniques for Server-Based Solutions. In International Journal of Human-Computer Interaction, 19 (3) pp. 279-304
“As handheld devices become ubiquitous and the tasks performed become multipurpose in nature, efficient data entry techniques are necessary. This research evaluated several speech-based text entry solutions for handheld devices using server-based speech recognition. Because server-based solutions introduce network delays, an analysis of the relationship among network delays, number of recognition errors, how fast users can correct errors, and overall data entry rates was performed. The analysis and empirical results confirm the importance of minimizing recognition errors. This suggests that a server-based approach that makes more computing resources available may prove effective. Results from two empirical studies are presented. The first compares two error correction mechanisms: a multitap and soft keyboard solution. The second employs a longitudinal investigation of the effects of experience on text entry rates. Users attained an effective mean text entry rate as high as 25.3 words per min, which is higher than or comparable to data entry rates reported for other input techniques for handheld devices. The results of this research have implications for researchers and designers of automatic speech recognition systems and mobile devices.”
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» 2004 «
Price, Kathleen J., Lin, Min, Feng, Jinjuan, Goldman, Rich, Sears, Andrew and Jacko, Julie A. (2004): Data Entry on the Move: An Examination of Nomadic Speech-Based Text Entry. In: Proceedings of the 8th ERCIM Workshop on User Interfaces for All 2004. p. 460. Available online
“Desktop interaction solutions are often inappropriate for mobile devices due to small screen size and portability needs. Speech recognition can improve interactions by providing a relatively hands-free solution that can be used in various situations. While mobile systems are designed to be transportable, few have examined the effects of motion on mobile interactions. We investigated the effect of motion on automatic speech recognition (ASR) input for mobile devices. We examined speech recognition error rates (RER) with subjects walking or seated, while performing text input tasks and the effect of ASR enrollment conditions on RER. RER were significantly lower for seated conditions. There was a significant interaction between enrollment and task conditions. When users enrolled while seated, but completed walking tasks, RER increased. In contrast, when users enrolled while walking, but completed seated tasks, RER decreased. These results suggest changes in user training of ASR systems for mobile and seated usage.”
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Mar 17th, 2010
Changes to this page (author)
20 Feb 2010: Enabled abstracts to be shown on Kathleen J. Price's author page.07 Apr 2009: Author was edited 12 May 2008: Author was edited
12 May 2008: Author was edited
26 Jul 2007: Author was edited
11 Jun 2007: Author was added to the bibliography
