Head-related transfer functions (HRTFs) are central to convincing binaural rendering in virtual and augmented reality applications. While individual HRTFs offer the highest perceptual fidelity, the practical difficulty of personal HRTF acquisition drives widespread use of dummy head (mannequin) measurements as a non-individualized substitute. Despite their ubiquity, systematic perceptual benchmarking of dummy head HRTFs against human HRTFs remains limited, particularly with respect to whether consistent trends emerge across listeners irrespective of individual HRTF preference. This study extends prior work on subjective HRTF evaluation methodologies and perceptual ranking by applying an established trajectory-based quality assessment paradigm to a mixed set of dummy head and human HRTFs. Participants were presented with predefined auditory trajectories rendered via binaural synthesis and asked to rate the perceptual quality of each rendering with respect to adherence to the prescribed trajectory. HRTFs were presented in randomised order across two sets of eight, with repeated items serving as an inter-set normalisation anchors. The HRTF pool encompassed human measurements alongside a range of dummy head types: simplified head-only geometries, head-and-torso simulators (HATS), and models incorporating absorptive materials (hair, clothing analogues). The primary research question is whether, despite well-documented listener-dependent variability in HRTF suitability, population-level trends differentiate dummy head HRTFs from human ones, and further, whether acoustic complexity of the mannequin (torso, absorptive surfaces) correlates with perceptual performance. Results are discussed in terms of implications for HRTF database design and substitute HRTF selection strategies for immersive audio applications.
