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US 2026/0031081 A1Published application
Federated learning for audio processing
AssigneeAmazon Technologies, Inc.
InventorsAndrew Morris Werchniak, Ilya Sokolov, Raphael Petegrosso, Aansh Shah, Aaron Challenner, Michael Thomas Peterson, Shuang Wu
Life of this patent
Estimating the term…
Abstract
A system performs federated learning and retraining of a machine learning model used for processing audio detected by a user device. The system uses both gradient data (which may correspond to false-rejects) and audio data (which may correspond to false-positives) received from devices. The system may also use a teacher model to produce labels for data in an automated fashion, thus allowing retraining to happen in an unsupervised manner.
Claims21
-20. (canceled)
A computer-implemented method, comprising:
- receiving first parameter data corresponding to adjustment of at least one parameter of a first machine learning model by a first device as a result of operation, by the first device, of the first machine learning model;
- receiving first input data corresponding to operation of the first machine learning model by a second device;
- processing the first input data using a second machine learning model to determine the first input data corresponds to incorrect processing by the second device using the first machine learning model;
- and
- processing the first parameter data and data corresponding to processing of the first input data by the second machine learning model to determine an updated first machine learning model.
2 more elements
A system comprising:
- at least one processor;
- and
- at least one memory comprising instructions that, when executed by the at least one processor, cause the system to perform operations comprising:
- receiving first parameter data corresponding to adjustment of at least one parameter of a first machine learning model by a first device as a result of operation, by the first device, of the first machine learning model;
- receiving first input data corresponding to operation of the first machine learning model by a second device;
- processing the first input data using a second machine learning model to determine the first input data corresponds to incorrect processing by the second device using the first machine learning model;
- and
- processing the first parameter data and data corresponding to processing of the first input data by the second machine learning model to determine an updated first machine learning model.
5 more elements
Dependencies are inferred from the claim text.