🤖 AI Summary
This study investigates the design of six-degree-of-freedom (6DoF) gestures for music mixing in extended reality (XR) that align with professional mixing practices while minimizing cognitive load. Through design workshops, professional mix engineers contributed gesture concepts for core tasks—including gain adjustment, compression, equalization, and automation—which were subsequently implemented in an XR prototype. A user study was conducted to evaluate the ecological validity, cognitive load, and user experience of these gestures. This work presents the first systematic mapping of real-world mixing workflows into a 6DoF gesture space, enhancing users’ sense of control without compromising ecological validity. Findings indicate that the proposed gestures were widely perceived as intuitive, immersive, and well-matched to their respective tasks, with negligible differences in cognitive load; user preferences were primarily influenced by familiarity with existing workflows and perceived control.
📝 Abstract
Extended reality (XR) enables new music-mixing workflows by moving beyond 2D faders toward embodied, spatial interaction. However, it remains unclear which six-degree-of-freedom (6DoF) gestures align with real-world mixing practices and whether such interactions support manageable cognitive load and positive user experience. We conducted a design workshop with experienced mixers to elicit gesture concepts for core audio tasks gain, compression, equalization, and automation, and implemented these in an XR prototype. A user study (n=12) evaluated the ecological validity of the gestures using cognitive load measures, user-experience ratings, and interviews. Participants generally found 6DoF gestures intuitive and well-mapped to mixing tasks, reporting strong immersion and a sense of connection with the audio environment. Cognitive load differences across gestures were minimal, though participants expressed preferences shaped by workflow familiarity and perceived control. We discuss implications for designing XR mixing tools that balance expressiveness, precision, and ecological validity.