5 August 2009 Low-order modelling of head related transfer functions based on spectral smoothing and principal component analysis
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Proceedings Volume 7502, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009; 75021J (2009) https://doi.org/10.1117/12.838134
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009, 2009, Wilga, Poland
Abstract
The article presents wavelet-based spectral smoothing and Principal Component Analysis as a pre-processing step for Head Related Transfer Function (HRTF) filter design. Spectral smoothing of HRTF by means of Stationary Wavelet Transform discards low-value peaks and notches in HRTF which can be treated as noise. The Principal Component Analysis applied to the HRTF data extracts most important frequency components responsible for sound source localization in azimuth and elevation. These methods used in combination are used to reduce the order of filters that are applied in 3D audio rendering system.
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Michal Pec, Pawel Strumillo, "Low-order modelling of head related transfer functions based on spectral smoothing and principal component analysis", Proc. SPIE 7502, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009, 75021J (5 August 2009); doi: 10.1117/12.838134; https://doi.org/10.1117/12.838134
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