The Morphologically Informed Perceptual Enhancement of Spatial Audio

With the proliferation of immersive technologies in virtual reality (VR), broadcasting and home entertainment, estimating an individual’s head-related transfer functions (HRTFs) conveniently and with a satisfactory perceptual performance is of great topical interest. To facilitate this, a deep understanding of how the head and pinnae form the acoustic cues used to perceive spatial sound is required. This thesis presents the refinement of a powerful research tool, morphoacoustic perturbation analysis (MPA), for advancing knowledge in this field. To simplify analysis a novel method is presented for smoothing HRTFs based on an equivalent rectangular bandwidth (ERB) criterion. The approach is first evaluated using an auditory localisation model and these results are validated by means of listening tests. It is shown that ERB smoothing achieves perceptual transparency using fewer parameters than a similar constant-bandwidth approach. Furthermore, it simplifies the structure of the HRTFs, since additional perceptually irrelevant features are discarded. It has been well established that the boundary element method can satisfactorily generate HRTFs based on a three-dimensional (3D) mesh of a listener’s head and pinnae shape. A proof-of-principle for MPA, upon which this thesis builds, has successfully inverted this process, making it possible to identify the morphological regions of the head and pinnae responsible for creating an HRTF feature. However, first-generation MPA suffered from significant weaknesses including low mesh resolution, restricted frequency range, and topological issues created by the mesh slicing approach used. In this work these issues are addressed through the use of optimised spherical mesh mapping and spherical harmonic deformations. The theory, implementation and validation of the new method is described to the point where the creation of a full MPA database capable of probing in depth the relationship between human morphology and HRTFs is now possible.