Accelerated Method for the Reduced-Parameter Modeling of Head-Related Transfer Functions for Customizable Spatial Audio

Many spatial audio (“3D sound”) systems are based on the use of Head-Related Transfer Functions (HRTFs). Since the measurement of these HRTFs for each prospective listener is impractical in many applications, developers frequently use “generic” HRTFs (e.g., from a mannequin), sacrificing the superior spatialization that could be provided by “individual” HRTFs. This paper presents an improved method for decomposing the impulse response of measured HRTFs, known as Head-Related Impulse Responses (HRIRs), into multiple delayed and scaled damped sinusoids, as a means to obtain the parameters that will instantiate a general model in order to produce the same impulse response as the original HRTF. This is the first step in developing alternative functional models of HRTFs that would contain only a few parameters related to anatomical features of the intended listener, which could be estimated for each user, i.e., “customizable” HRTF models. The new decomposition algorithm is based on the use of higher-order (higher than second order) Steiglitz-McBride functional approximations supplemented by frequency-domain selection of the most appropriate damped sinusoid to represent each of the components of the original, measured HRIR under analysis. Key-Words: Head-Related Impulse Responses (HRIR), Prony modeling method, Steiglitz-McBride iterative approximation method, customizable spatial audio.