US 12,456,493 B2
System for automated multitrack mixing
Christian James Steinmetz, Barcelona (ES); and Joan Serra, Barcelona (ES)
Assigned to Dolby Laboratories Licensing Corporation, San Francisco, CA (US)
Appl. No. 18/012,245
Filed by Dolby International AB, Dublin (IE)
PCT Filed Jun. 16, 2021, PCT No. PCT/EP2021/066206
§ 371(c)(1), (2) Date Dec. 22, 2022,
PCT Pub. No. WO2021/259725, PCT Pub. Date Dec. 30, 2021.
Claims priority of provisional application 63/092,310, filed on Oct. 15, 2020.
Claims priority of provisional application 63/072,762, filed on Aug. 31, 2020.
Claims priority of application No. P202030604 (ES), filed on Jun. 22, 2020; and application No. 20203276 (EP), filed on Oct. 22, 2020.
Prior Publication US 2023/0352058 A1, Nov. 2, 2023
Int. Cl. H04R 5/00 (2006.01); G06N 3/045 (2023.01); G11B 27/038 (2006.01); H04S 3/00 (2006.01)
CPC G11B 27/038 (2013.01) [G06N 3/045 (2023.01); H04S 3/008 (2013.01); H04S 2400/01 (2013.01); H04S 2400/13 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A deep-learning-based system for performing automated multitrack mixing based on a plurality of input audio tracks, wherein the system comprises:
one or more instances of a deep-learning-based controller network; and
one or more instances of a deep-learning-based transformation network,
wherein the controller network is configured to, based on the input audio tracks, generate parameters for use in the automated multitrack mixing;
wherein the transformation network is configured to, based on the parameters, apply signal processing and at least one mixing gain to the input audio tracks, for generating an output mix of the audio tracks;
wherein the controller network and transformation network are trained separately, and
wherein the controller network is trained based on the pre-trained transformation network.