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J. Vilkamo, T. Bäckström, and A. Kuntz, "Optimized Covariance Domain Framework for Time–Frequency Processing of Spatial Audio," J. Audio Eng. Soc., vol. 61, no. 6, pp. 403-411, (2013 June.). doi: J. Vilkamo, T. Bäckström, and A. Kuntz, "Optimized Covariance Domain Framework for Time–Frequency Processing of Spatial Audio," J. Audio Eng. Soc., vol. 61 Issue 6 pp. 403-411, (2013 June.). doi:
Abstract: This research proposes a generalized and optimized framework for time–frequency processing of spatial audio using a signal covariance matrix. This framework is relevant for a wide variety of spatial applications, such as perceptual spatial coding, stereo upmixing, decorrelation, and so on. The matrix, which represents interchannel dependencies, is perceptually relevant for the transmission of the listener’s spatial experience. In a typical application, the original time–frequency covariance matrix is transformed into the target matrix, optimizing the sound quality using a least mean square metric. In an example of upmixing stereo music, informal listening tests confirmed the validity of the framework.

@article{vilkamo2013optimized,
author={vilkamo, juha and bäckström, tom and kuntz, achim},
journal={journal of the audio engineering society},
title={optimized covariance domain framework for time–frequency processing of spatial audio},
year={2013},
volume={61},
number={6},
pages={403-411},
doi={},
month={june},} @article{vilkamo2013optimized,
author={vilkamo, juha and bäckström, tom and kuntz, achim},
journal={journal of the audio engineering society},
title={optimized covariance domain framework for time–frequency processing of spatial audio},
year={2013},
volume={61},
number={6},
pages={403-411},
doi={},
month={june},
abstract={this research proposes a generalized and optimized framework for time–frequency processing of spatial audio using a signal covariance matrix. this framework is relevant for a wide variety of spatial applications, such as perceptual spatial coding, stereo upmixing, decorrelation, and so on. the matrix, which represents interchannel dependencies, is perceptually relevant for the transmission of the listener’s spatial experience. in a typical application, the original time–frequency covariance matrix is transformed into the target matrix, optimizing the sound quality using a least mean square metric. in an example of upmixing stereo music, informal listening tests confirmed the validity of the framework.},}

TY - paper
TI - Optimized Covariance Domain Framework for Time–Frequency Processing of Spatial Audio
SP - 403 EP - 411
AU - Vilkamo, Juha
AU - Bäckström, Tom
AU - Kuntz, Achim
PY - 2013
JO - Journal of the Audio Engineering Society
IS - 6
VO - 61
VL - 61
Y1 - June 2013 TY - paper
TI - Optimized Covariance Domain Framework for Time–Frequency Processing of Spatial Audio
SP - 403 EP - 411
AU - Vilkamo, Juha
AU - Bäckström, Tom
AU - Kuntz, Achim
PY - 2013
JO - Journal of the Audio Engineering Society
IS - 6
VO - 61
VL - 61
Y1 - June 2013
AB - This research proposes a generalized and optimized framework for time–frequency processing of spatial audio using a signal covariance matrix. This framework is relevant for a wide variety of spatial applications, such as perceptual spatial coding, stereo upmixing, decorrelation, and so on. The matrix, which represents interchannel dependencies, is perceptually relevant for the transmission of the listener’s spatial experience. In a typical application, the original time–frequency covariance matrix is transformed into the target matrix, optimizing the sound quality using a least mean square metric. In an example of upmixing stereo music, informal listening tests confirmed the validity of the framework.