A method to estimate sound source orientation in a reverberant room using a microphone array is proposed. We extend the conventional modeling of a room transfer function based on the image method in order to take into account the directivity of a sound source. With this extension, a transfer function between a sound source and a listener (or a microphone) is described by the superposition of transfer functions from each image source to the listener multiplied by the source directivity; thus, the sound source orientation can be estimated by analyzing how the image sources are distributed (power distribution of image sources) from observed signals. We applied eigenvalue analysis to the spatial correlation matrix of the microphone array observation to obtain the power distribution of image sources. Bsed on the assumption that the spatial correlation matrix for each set of source position and orientation is known a priori, the variation of the eigenspace can be modeled. By comparing the eigenspace of observed signals and that of pre-learned models, we estimated the sound source orientation. Through experiments using seven microphones, the sound source orientation was estimated with high accuracy by increasing the reverberation time of a room.
Kenta NIWA
NTT Corporation
Yusuke HIOKA
University of Canterbury
Sumitaka SAKAUCHI
NTT Corporation
Ken'ichi FURUYA
Oita University
Yoichi HANEDA
The University of Electro-Communications
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Kenta NIWA, Yusuke HIOKA, Sumitaka SAKAUCHI, Ken'ichi FURUYA, Yoichi HANEDA, "An Estimation Method of Sound Source Orientation Using Eigenspace Variation of Spatial Correlation Matrix" in IEICE TRANSACTIONS on Fundamentals,
vol. E96-A, no. 9, pp. 1831-1839, September 2013, doi: 10.1587/transfun.E96.A.1831.
Abstract: A method to estimate sound source orientation in a reverberant room using a microphone array is proposed. We extend the conventional modeling of a room transfer function based on the image method in order to take into account the directivity of a sound source. With this extension, a transfer function between a sound source and a listener (or a microphone) is described by the superposition of transfer functions from each image source to the listener multiplied by the source directivity; thus, the sound source orientation can be estimated by analyzing how the image sources are distributed (power distribution of image sources) from observed signals. We applied eigenvalue analysis to the spatial correlation matrix of the microphone array observation to obtain the power distribution of image sources. Bsed on the assumption that the spatial correlation matrix for each set of source position and orientation is known a priori, the variation of the eigenspace can be modeled. By comparing the eigenspace of observed signals and that of pre-learned models, we estimated the sound source orientation. Through experiments using seven microphones, the sound source orientation was estimated with high accuracy by increasing the reverberation time of a room.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E96.A.1831/_p
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@ARTICLE{e96-a_9_1831,
author={Kenta NIWA, Yusuke HIOKA, Sumitaka SAKAUCHI, Ken'ichi FURUYA, Yoichi HANEDA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Estimation Method of Sound Source Orientation Using Eigenspace Variation of Spatial Correlation Matrix},
year={2013},
volume={E96-A},
number={9},
pages={1831-1839},
abstract={A method to estimate sound source orientation in a reverberant room using a microphone array is proposed. We extend the conventional modeling of a room transfer function based on the image method in order to take into account the directivity of a sound source. With this extension, a transfer function between a sound source and a listener (or a microphone) is described by the superposition of transfer functions from each image source to the listener multiplied by the source directivity; thus, the sound source orientation can be estimated by analyzing how the image sources are distributed (power distribution of image sources) from observed signals. We applied eigenvalue analysis to the spatial correlation matrix of the microphone array observation to obtain the power distribution of image sources. Bsed on the assumption that the spatial correlation matrix for each set of source position and orientation is known a priori, the variation of the eigenspace can be modeled. By comparing the eigenspace of observed signals and that of pre-learned models, we estimated the sound source orientation. Through experiments using seven microphones, the sound source orientation was estimated with high accuracy by increasing the reverberation time of a room.},
keywords={},
doi={10.1587/transfun.E96.A.1831},
ISSN={1745-1337},
month={September},}
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TY - JOUR
TI - An Estimation Method of Sound Source Orientation Using Eigenspace Variation of Spatial Correlation Matrix
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1831
EP - 1839
AU - Kenta NIWA
AU - Yusuke HIOKA
AU - Sumitaka SAKAUCHI
AU - Ken'ichi FURUYA
AU - Yoichi HANEDA
PY - 2013
DO - 10.1587/transfun.E96.A.1831
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E96-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2013
AB - A method to estimate sound source orientation in a reverberant room using a microphone array is proposed. We extend the conventional modeling of a room transfer function based on the image method in order to take into account the directivity of a sound source. With this extension, a transfer function between a sound source and a listener (or a microphone) is described by the superposition of transfer functions from each image source to the listener multiplied by the source directivity; thus, the sound source orientation can be estimated by analyzing how the image sources are distributed (power distribution of image sources) from observed signals. We applied eigenvalue analysis to the spatial correlation matrix of the microphone array observation to obtain the power distribution of image sources. Bsed on the assumption that the spatial correlation matrix for each set of source position and orientation is known a priori, the variation of the eigenspace can be modeled. By comparing the eigenspace of observed signals and that of pre-learned models, we estimated the sound source orientation. Through experiments using seven microphones, the sound source orientation was estimated with high accuracy by increasing the reverberation time of a room.
ER -