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Schedule as of Oct 11, 2022 - subject to change

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Thursday, October 27 • 11:00am - 11:15am
Higher order ambisonics compression method based on autoencoder

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The compression of three-dimensional sound field signals has always been a very important issue. Recently, an Independent Component Analysis (ICA) based Higher Order Ambisonics (HOA) compression method introduces blind source separation to solve the shortcomings of discontinuity between frames in the existing Singular Value Decomposition (SVD) based methods. However, ICA is weak to model the reverberant environment, and its target is not to recover original signal. In this work, we replace ICA with autoencoder to further improve the above method’s ability to cope with reverberation conditions and ensure the unanimous optimization both in separation and recovery by reconstruction loss. We constructed a dataset with simulated and recorded signals, and verified the effectiveness of our method through objective and subjective experiments.

Speakers
TQ

Tianshu Qu

Peking University
avatar for Jiahao Xu

Jiahao Xu

Student, Peking University
ZY

Zeyu Yuan

Beijing, China, Peking University
XW

Xihong Wu

Peking University


Thursday October 27, 2022 11:00am - 11:15am EDT
Online Papers
  Applications in Audio
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