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The channel based 3D audio can be compressed to a down-mix signal with side information. In this paper the inter-channel transfer functions (ITF) are estimated through training over fitting convolutional neural networks (CNN) on a specific frame. Perfectly reconstructing the original channel and keeping the spatial cues the same is set as the target of the estimation. By taking this approach, more accurate spatial cues are maintained. The subjective evaluation experiments were carried out on stereo signals to evaluate the proposed method.
Author (s): Huang, Qingbo;
Wu, Xihong;
Qu, Tianshu;
Affiliation:
Peking University, Beijing, China
(See document for exact affiliation information.)
AES Convention: 145
Paper Number:10126
Publication Date:
2018-10-06
Session subject:
Spatial Audio
DOI:
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Huang, Qingbo; Wu, Xihong; Qu, Tianshu; 2018; A Parametric Spatial Audio Coding Method Based on Convolutional Neural Networks [PDF]; Peking University, Beijing, China; Paper 10126; Available from: https://aes.org/publications/elibrary-page/?id=19852
Huang, Qingbo; Wu, Xihong; Qu, Tianshu; A Parametric Spatial Audio Coding Method Based on Convolutional Neural Networks [PDF]; Peking University, Beijing, China; Paper 10126; 2018 Available: https://aes.org/publications/elibrary-page/?id=19852
@inproceedings{Huang2018a,
title={{A Parametric Spatial Audio Coding Method Based on Convolutional Neural Networks}},
author={Huang, Qingbo and Wu, Xihong and Qu, Tianshu},
year={2018},
month={oct},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 10126; AES Convention 145; October 2018},
number={10126},
organization={AES},
}
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