Using Audio Cues to Support Motion Gesture Interaction on Mobile Devices

摘要: Motion gestures are an underutilized input modality for mobile interaction despite numerous potential advantages. Negulescu et al. found that the lack of feedback on attempted motion made it difficult participants to diagnose and correct errors, resulting in poor recognition performance user frustration. In this article, we describe evaluate a training technique, Glissando, which uses audio characteristics provide system’s interpretation input. This technique enables by verbally confirming notifying users errors addition providing continuous manipulating pitch distinct musical notes mapped each three dimensional axes order both spatial temporal information.