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Wavelet based spectral smoothing for head-related transfer function filter design
Date
2002-01-01
Author
Hacıhabiboğlu, Hüseyin
Günel Kılıç, Banu
Murtagh, F
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Three wavelet-based spectral smoothing techniques are presented in this paper as a pre-processing stage for head-related transfer function (HRTF) filter design. These wavelet-based methods include wavelet denoising, wavelet approximation, and redundant wavelet transform. These methods are used with time-domain parametric filter design methods to reduce the order of the IIR filters which is useful for real-time implementation of immersive audio systems. Results of a subjective listening test are then presented in order to justify the perceptual validity of the investigated smoothing methods. Results show that wavelet based spectral smoothing methods are beneficial in reducing the filter order and increasing the perception of localization without introducing noticeable effect on timbre.
URI
https://hdl.handle.net/11511/54533
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Graduate School of Informatics, Conference / Seminar
