Hands-free speech-based technology can be a useful alternative for individuals that find traditional input devices, such as keyboard and mouse, difficult to use. Various speech-based navigation techniques have been examined, and several are available in commercial software applications. Among these alternatives, grid-based navigation has demonstrated both potential and limitations. In this article, we discuss an empirical study that assessed the efficacy of two enhancements to grid-based navigation: magnification and fine-tuning. The magnification capability enlarges the selected region when it becomes sufficiently small, making it easier to see the target and cursor. The fine-tuning capability allows users to move the cursor short distances to position the cursor over the target. The study involved one group of participants with physical disabilities, an agematched group of participants without disabilities, and a third group that included young adults without disabilities. The results confirm that both magnification and fine-tuning significantly improved the participants' performance when selecting targets, especially small targets. Providing either, or both, of the proposed enhancements substantially reduced the gaps in performance due to disability and age. The results will inform the design of speech-based target selection mechanism, allowing users to select targets faster while making fewer errors.
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Computer Science Applications