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.
Authors:
Huang, Qingbo; Wu, Xihong; Qu, Tianshu
Affiliation:
Peking University, Beijing, China
AES Convention:
145 (October 2018)
Paper Number:
10126
Publication Date:
October 7, 2018
Subject:
Spatial Audio
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.