US 12,035,106 B2
Machine learning model capability assessment
Aaron Lawson, San Jose, CA (US); Mitchell L McLaren, Everton Park (AU); and Diego Castan Lavilla, Dobbs Ferry, NY (US)
Assigned to SRI INTERNATIONAL, Menlo Park, CA (US)
Filed by SRI International, Menlo Park, CA (US)
Filed on Oct. 22, 2021, as Appl. No. 17/508,365.
Claims priority of provisional application 63/126,117, filed on Dec. 16, 2020.
Prior Publication US 2022/0044077 A1, Feb. 10, 2022
Int. Cl. H04R 25/00 (2006.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 18/2413 (2023.01); G06N 20/00 (2019.01)
CPC H04R 25/453 (2013.01) [G06F 18/214 (2023.01); G06F 18/2185 (2023.01); G06F 18/2413 (2023.01); G06N 20/00 (2019.01); H04R 2225/41 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computing system comprising:
a storage device; and
processing circuitry having access to the storage device and configured to:
receive information indicative of a media dataset comprising at least one of audio data and image data, wherein the media dataset corresponds to an object;
analyze the media dataset to compute a corresponding set of operating condition weight values, wherein each operating condition weight value of the set of operating condition weight values corresponds to a different operating condition of a set of operating conditions;
compare the set of operating condition weight values corresponding to the media dataset with a plurality of sets of reference operating condition weight values that each correspond to a different reference media dataset of a plurality of reference media datasets;
determine, based on the comparison of the set of operating condition weight values with the plurality of sets of reference operating condition weight values, an indication of a capability of a trained machine learning model to correctly verify the object in the media dataset; and
perform an action based on the indication.