Headphone Virtualization: Improved Localization and Externalization of Non-Individualized HRTFs by Cluster Analysis

Tame RP, Barchiese D, Klapuri A. Headphone Virtualization: Improved Localization and Externalization of Non-Individualized HRTFs by Cluster Analysis. In: AES Convention 133. Audio Engineering Society; 2012. Paper 8757. Available from: https://aes.org/publications/elibrary-page/?id=16499

@inproceedings{Tame2012_16499,
  author = {Tame, Robert P. and Barchiese, Daniele and Klapuri, Anssi},
  title = {{Headphone Virtualization: Improved Localization and Externalization of Non-Individualized HRTFs by Cluster Analysis}},
  booktitle = {AES Convention 133},
  note = {Paper 8757},
  year = {2012},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16499}
}

TY  - CPAPER
TI  - Headphone Virtualization: Improved Localization and Externalization of Non-Individualized HRTFs by Cluster Analysis
AU  - Tame, Robert P.
AU  - Barchiese, Daniele
AU  - Klapuri, Anssi
T2  - AES Convention 133
M1  - Paper 8757
PY  - 2012
DA  - 2012/10/06
UR  - https://aes.org/publications/elibrary-page/?id=16499
PB  - Audio Engineering Society
LA  - en
AB  - Research and experimentation is described that aims to prove the hypothesis that by allowing a listener to choose a single non-individualized profile of HRTFs from a subset of maximally different best representative profiles extracted from a database improved localization, and externalization can be achieved for the listener. k-means cluster analysis of entire impulse responses is used to identify the subset of profiles. Experimentation in a controlled environment shows that test subjects who were offered a choice of a preferred HRTF profile were able to consistently discriminate between a front center or rear center virtualized sound source 78.6% of the time, compared with 64.3% in a second group given an arbitrary HRTF profile. Similar results were obtained from virtualizations in uncontrolled environments.
ER  -