Speech-based cursor control using grids: Modelling performance and comparisons with other solutions

Speech recognition can be a powerful tool for use in human-computer interaction, especially in situations where the user's hands are unavailable or otherwise engaged. Researchers have confirmed that existing mechanisms for speech-based cursor control are both slow and error prone. To address this, we evaluated two variations of a novel grid-based cursor controlled via speech recognition. One provides users with nine cursors that can be used to specify the desired location while the second, more traditional solution, provides a single cursor. Our results confirmed a speed/accuracy trade-off with a nine-cursor variant allowing for faster task completion times while the one-cursor version resulted in reduced error rates. Our solutions eliminated the effect of distance, and dramatically reduced the importance of target size as compared to previous speech-based cursor control mechanisms. The results are explored through a predictive model and comparisons with results from earlier studies.