US 12,249,345 B2
Ephemeral learning and/or federated learning of audio-based machine learning model(s) from stream(s) of audio data generated via radio station(s)
Johan Schalkwyk, Scarsdale, NY (US); Blaise Aguera-Arcas, Seattle, WA (US); Diego Melendo Casado, Mountain View, CA (US); and Oren Litvin, New York, NY (US)
Assigned to GOOGLE LLC, Mountain View, CA (US)
Filed by GOOGLE LLC, Mountain View, CA (US)
Filed on Dec. 5, 2022, as Appl. No. 18/074,739.
Claims priority of provisional application 63/401,399, filed on Aug. 26, 2022.
Prior Publication US 2024/0071406 A1, Feb. 29, 2024
Int. Cl. G10L 25/51 (2013.01); G10L 15/00 (2013.01); G10L 15/18 (2013.01)
CPC G10L 25/51 (2013.01) [G10L 15/005 (2013.01); G10L 15/18 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method implemented by one or more processors of a client device, the method comprising:
receiving, from a given radio station, a stream of audio data that captures a stream of spoken utterances in a given language;
generating, based on processing the stream of audio data, an audio-fingerprint for the stream of audio data;
determining, based on comparing the audio-fingerprint for the stream of audio data to a database of audio-fingerprints, whether the stream of audio data has been previously utilized in generating a gradient for updating a global machine learning (ML) model with respect to the given language; and
in response to determining that the stream of audio data has not been previously utilized in generating a gradient for updating the global ML model with respect to the given language:
processing, using an on-device ML model that is stored in on-device storage of the client device and that is an on-device counterpart of the global ML model, the stream of audio data;
generating, using an unsupervised or self-supervised learning technique, and based on processing the stream of audio data using the on-device ML model, the gradient; and
transmitting the gradient to the remote system to be utilized in updating the global ML model with respect to the given language.