System for automated multitrack mixing
AssigneeDolby Laboratories Licensing Corporation
InventorsChristian James Steinmetz, Joan Serra
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Abstract
A deep-learning-based system for performing automated multitrack mixing based on a plurality of input audio tracks is described herein. The system comprises one or more instances of a deep-learning-based first network and one or more instances of a deep-learning-based second network. Particularly, the first network is configured to, based on the 5 input audio tracks, generate parameters for use in the automated multitrack mixing. The second 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.
Claims21
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.
A deep-learning-based system for performing automated multitrack mixing based on a plurality of input audio tracks, the system comprising:
- a controller network, and
- a transformation network,
- wherein the input audio tracks are provided in parallel to the controller network and the transformation network, and
- wherein the transformation network is configured to apply signal processing and at least one mixing gain to the input audio tracks for generating an output mix of the audio tracks, based on one or more parameters generated by the controller network.
A method of operating 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, the method comprising:
- providing the input audio tracks to the controller network and the transformation network in parallel;
- generating, by the controller network, parameters for use in the automated multitrack mixing, based on the input audio tracks;
- and
- applying, by the transformation network, signal processing and at least one mixing gain to the input audio tracks based on the parameters, for generating an output mix of the audio tracks.
Dependencies are inferred from the claim text.