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Application of dimensionality reduction techniques to HRTFS for interactive virtual environments

Published: 13 June 2007 Publication History

Abstract

Fundamental to the generation of 3D audio is the HRTF processing of acoustical signals. Unfortunately, given the high dimensionality of HRTFs, incorporating them into dynamic/interactive virtual environment and gaming applications is computationally very demanding. This greatly limits the performance of such applications that incorporate real-time 3D audio. This paper examines the application of data reduction models to HRTFs. In particular, the locally linear Isomap, Locally Linear Embedding (LLE), and the globally linear Principal Components Analysis (PCA) dimensionality reduction tools are applied to the MIT HRTF dataset. Our motivation is to project the inherently high-dimensional space inherent in HRTF measurements onto a lower dimensionality such that they can be incorporated into interactive virtual environments and gaming applications.

References

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R. Begault. 3-D Sound for Virtual Reality and Multimedia. Academic Press, MA. USA, 1994.
[2]
W. G. Gardner and K. D. Martin. HRTF Measurements of a KEMAR. J Acoust Soc Am, 97:3907--3908, 1995.
[3]
D. J. Kistler and F. L. Wightman. A Model of Head-Related Transfer Functions based on Principle Components Analysis and Minimum Phase Reconstruction.allJ Acoust Soc Am, 91:1637--1647, 1992.
[4]
S. T. Roweis and L. K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500)2323--2326, 2000.
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J. B. Tenenbaum V. de Silva and J. C. Langford. A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science, 290(5500)2319--2323, 2000.

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  • (2025)A Survey on Machine Learning Techniques for Head-Related Transfer Function IndividualizationIEEE Open Journal of Signal Processing10.1109/OJSP.2025.35283306(30-56)Online publication date: 2025
  • (2023)AuditionStepping into Virtual Reality10.1007/978-3-031-36487-7_9(173-182)Online publication date: 12-Aug-2023
  • (2021)On the Exploitation of 5G Multi-Access Edge Computing for Spatial Audio in Cultural Heritage ApplicationsIEEE Access10.1109/ACCESS.2021.31287869(155197-155206)Online publication date: 2021
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    cover image ACM Conferences
    ACE '07: Proceedings of the international conference on Advances in computer entertainment technology
    June 2007
    324 pages
    ISBN:9781595936400
    DOI:10.1145/1255047
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 13 June 2007

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    Author Tags

    1. 3D sound
    2. HRTF
    3. dimensionality reduction
    4. isomap
    5. local linear embedding (LLE)
    6. principal components analysis (PCA)

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    Overall Acceptance Rate 36 of 90 submissions, 40%

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    Cited By

    View all
    • (2025)A Survey on Machine Learning Techniques for Head-Related Transfer Function IndividualizationIEEE Open Journal of Signal Processing10.1109/OJSP.2025.35283306(30-56)Online publication date: 2025
    • (2023)AuditionStepping into Virtual Reality10.1007/978-3-031-36487-7_9(173-182)Online publication date: 12-Aug-2023
    • (2021)On the Exploitation of 5G Multi-Access Edge Computing for Spatial Audio in Cultural Heritage ApplicationsIEEE Access10.1109/ACCESS.2021.31287869(155197-155206)Online publication date: 2021
    • (2019)Implementation of improved 3D interpolation technique on HRIR models using PCAIOP Conference Series: Materials Science and Engineering10.1088/1757-899X/508/1/012078508(012078)Online publication date: 2-May-2019
    • (2016)A manifold learning approach for personalizing HRTFs from anthropometric featuresIEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)10.1109/TASLP.2016.251756524:3(559-570)Online publication date: 1-Mar-2016
    • (2014)Anthropometric-based customization of head-related transfer functions using Isomap in the horizontal plane2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2014.6854448(4473-4477)Online publication date: May-2014
    • (2008)Dimensionality reduced HRTFsProceedings of the 2008 International Conference on Advances in Computer Entertainment Technology10.1145/1501750.1501763(59-62)Online publication date: 3-Dec-2008
    • (2008)Spatial sound for video games and virtual environments utilizing real-time GPU-based convolutionProceedings of the 2008 Conference on Future Play: Research, Play, Share10.1145/1496984.1497012(166-172)Online publication date: 3-Nov-2008

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