Dynamic Balanced Model Truncation of the Spherical Transfer Function for Use in Structural HRTF Models

Buchanan CG, Newton MJ. Dynamic Balanced Model Truncation of the Spherical Transfer Function for Use in Structural HRTF Models. In: AES Conference: 2018 AES International Conference on Audio for Virtual and Augmented Reality. Audio Engineering Society; 2018. Paper P9-1. Available from: https://aes.org/publications/elibrary-page/?id=19673

@inproceedings{Buchanan2018_19673,
  author = {Buchanan, Christopher G. and Newton, Michael J.},
  title = {{Dynamic Balanced Model Truncation of the Spherical Transfer Function for Use in Structural HRTF Models}},
  booktitle = {AES Conference: 2018 AES International Conference on Audio for Virtual and Augmented Reality},
  note = {Paper P9-1},
  year = {2018},
  month = aug,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=19673}
}

TY  - CPAPER
TI  - Dynamic Balanced Model Truncation of the Spherical Transfer Function for Use in Structural HRTF Models
AU  - Buchanan, Christopher G.
AU  - Newton, Michael J.
T2  - AES Conference: 2018 AES International Conference on Audio for Virtual and Augmented Reality
M1  - Paper P9-1
PY  - 2018
DA  - 2018/08/06
UR  - https://aes.org/publications/elibrary-page/?id=19673
PB  - Audio Engineering Society
LA  - en
AB  - The Spherical Transfer Function (STF) has previously been used in structural HRTF modelling as an analytical approximation to the human head. Versions based on both spherical and spheroidal solid bodies have been incorporated into a range of systems, such as the well known Brown and Duda [1] structural model. STF-based models provide a way to simulate frequency dependent head shadowing (ILD) and time delay (ITD) effects, which can form the foundation for structural HRTF representation. We derive and implement a customizable approximation of the STF based on Balanced Model Truncation, and utilize its inherent modular characteristics to synthesize binaural signals from monaural input with relatively low cost implications.
ER  -