Rich Goldman
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Publications by Rich Goldman (bibliography)
» 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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» 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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Dai, Liwei, Goldman, Rich, Sears, Andrew and Lozier, Jeremy (2004): Speech-based cursor control: a study of grid-based solutions. In: Sixth Annual ACM Conference on Assistive Technologies 2004. pp. 94-101. Available online
“Speech recognition can be a powerful tool for use in human-computer interaction. Many researchers are investigating the use of speech recognition systems for dictation-based activities, resulting in dramatic improvements in recent years. However, this same experimentation has confirmed that recognition errors and the delays inherent with speech recognition result in unacceptably long task completion times and error rates for cursor control tasks. This study explores the potential of a speech-controlled grid-based cursor control mechanism. An experiment evaluated two alternative grid-based solutions, both using 3-3 grids. One provided a single cursor in the middle of the grid. The second allows users to select a target using any of nine cursors. The results confirm that the nine-cursor solution allowed users to select targets of varying size, distance and direction significantly faster than the one-cursor solution. Overall results are encouraging when compared to earlier evaluations of other speech-based cursor control solutions.”
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Mar 20th, 2010
Changes to this page (author)
26 Feb 2010: Enabled abstracts to be shown on Rich Goldman's author page.12 May 2008: Author was edited 12 May 2008: Author was edited
22 Jun 2007: Author was edited
11 Jun 2007: Author was added to the bibliography
