Method to disrupt generation quality of deep audio generation models
AssigneeSourceAudio Holdings, LLC
InventorsMichalis Papakostas, Brent Phillips, Andrew Harding, Ryan Johnson, Brad-Lee Nichols
Life of this patent
Estimating the term…
Loading patent…
AssigneeSourceAudio Holdings, LLC
InventorsMichalis Papakostas, Brent Phillips, Andrew Harding, Ryan Johnson, Brad-Lee Nichols
Estimating the term…
An audio signal is segmented into a plurality of audio signal segments. A plurality of modified audio signal segments are generated based on processing data from the plurality of audio signal segments using a trained machine learning model. The plurality of modified audio signal segments are indistinguishable from the plurality of audio signal segments to the average human listener. A reconstructed audio signal corresponding to the audio signal is generated by combining the plurality of modified audio signal segments. The reconstructed audio signal is indistinguishable from the audio signal to the average human listener but, when used to train a generative machine learning model, constrains an ability of the trained generative machine learning model to generate new audio signals similar to the audio signal.
A method comprising:
A system comprising:
A non-transitory computer readable medium comprising instructions that, when executed by a processing device, cause the processing device to perform operations comprising:
Dependencies are inferred from the claim text.