Automatic Approximation of Head-Related Transfer Functions Using Parametric IIR Filters
* Präsentierender Autor
Zusammenfassung:Head-related transfer functions (HRTFs) are used in many applications for 3D spatial audio through headphones. Often, the HRTFs are stored as FIR filters. However, IIR filters give the opportunity to approximate the magnitude of these FIR filters with less coefficients. By using a cascade of parametric IIR filters such as shelving and peak filters, the amount of stored data can be reduced to three parameters (center frequency, gain and quality factor) per filter stage. In a first step, the low and high frequency shelving filters are adjusted. Secondly, peak filters are added consecutively until the error is inside the given tolerance. After including a new peak filter, the cascade of IIR filters is post-optimized in order to yield the best approximation for the current number of peak filters. In this work, the minimum number of peak filters needed to approximate HRTFs with a given error tolerance is evaluated for different directions.