US 11,700,473 B2
Methods, apparatus and systems for authentication
Vitaliy Sapozhnykov, Cheltenham (AU); Thomas Ivan Harvey, Northcote (AU); Brenton Potter, Croydon North (AU); and David Watts, Edinburgh (GB)
Assigned to Cirrus Logic, Inc., Austin, TX (US)
Filed by Cirrus Logic International Semiconductor Ltd., Edinburgh (GB)
Filed on Apr. 29, 2020, as Appl. No. 16/861,589.
Claims priority of provisional application 62/839,979, filed on Apr. 29, 2019.
Prior Publication US 2020/0342082 A1, Oct. 29, 2020
Int. Cl. G06F 21/00 (2013.01); H04R 1/10 (2006.01); G06F 21/32 (2013.01); G06F 18/22 (2023.01); G06V 40/10 (2022.01)
CPC H04R 1/1041 (2013.01) [G06F 18/22 (2023.01); G06F 21/32 (2013.01); G06V 40/10 (2022.01); H04R 1/1091 (2013.01); H04R 2460/15 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method for authenticating a user, the method comprising:
obtaining ear biometric data for a user to be authenticated, the ear biometric data comprising one or more features characteristic of the user's ear canal and an associated fit metric indicative of a positioning of a personal audio device relative to the user's ear canal, the personal audio device comprising a transducer for application of acoustic stimulus to the user's ear to obtain the ear biometric data;
determining the one or more features and the associated fit metric from the ear biometric data; and
identifying the user as a particular authorised user using both the determined one or more features and the determined associated fit metric;
wherein identifying the user as a particular authorised user based on the one or more features and the associated fit metric comprises:
determining a target user model set from a plurality of target user model sets based on the fit metric, each target user model set being associated with a particular fit metric of a set of fit metrics and comprising at least one target user model;
determining one or more target user similarity scores indicative of the similarity of the one or more features to a corresponding target user model of the determined target user model set;
determining a non-target user model set from a plurality of non-target user model sets based on the fit metric, each non-target user model set being associated with a particular fit metric of a set of fit metrics and comprising a plurality of non-target user models;
determining a plurality of non-target user similarity scores, each indicative of the similarity of the one or more features to a respective non-target user model of the plurality of the non-target user model of the determined target user model set; and
adjusting the one or more target user similarity scores based on the plurality of non-target user similarity scores.