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US 11,778,393 B2Granted
Method of optimizing parameters in a hearing aid system and a hearing aid system
AssigneeWidex A/S
InventorsJens Brehm Bagger Nielsen, Asger Ougaard, Lasse Lohilahti Molgaard, Caspar Aleksander Bang Jespersen
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Abstract
A hearing aid system (100) adapted to provide improved user personalization and a method of operating such a hearing aid system.
Claims8
A hearing aid system (100) comprising
- a display device (102), wherein a hearing aid (101) of the hearing aid system (100) operate with the display device (102) to:
- display a plurality of machine learning procedure screens adapted to prompt a hearing aid system user (111) to input the user's selection or assessment of one or more hearing aid system settings in order to determine a preferred hearing aid system setting, wherein said plurality of machine learning procedure screens comprises a graphical illustration of an estimate of the progress of a machine learning procedure towards reaching said preferred hearing aid system setting;
- and
- wherein the hearing aid system is configured to receive
- at least one characteristic selected from a group of characteristics comprising a convergence threshold, a minimum number of allowed iterations for the machine learning procedure, a maximum number of allowed iterations, a hyper parameter for a machine learning model adapted to provide the machine learning procedure, a categorization of the machine learning procedure and an estimate of the progress of the machine learning procedure
- from a remote internet server in response to transmitting to the remote internet server at least one of a plurality of observed estimates of progress in a machine learning procedure, selection or assessment inputs provided by the hearing aid system user and the corresponding parameter settings and parameters of the predictive or posterior distribution.
3 more elements
A method of operating a hearing aid system comprising the steps of:
- selecting a first set of hearing aid system parameters;
- providing a first and a second sound based on first and second parameter values;
- prompting a user to compare said first and second sounds and hereby provide an observation;
- prompting the user to provide a multitude of such observations based on a multitude of different parameter value settings;
- determining the likelihood function for a given observation;
- obtaining a prior distribution of the users internal response function;
- deriving an analytical expression for the posterior function of the users internal response function;
- determining an analytical expression for the predictive distribution of the users internal response function;
- determining a measure derived from the expected improvement;
- determining a convergence threshold for the measure derived from the expected improvement;
- estimating the progress towards finding the users preferred parameter values based on the measure derived from the expected improvement and the convergence threshold;
- and
- illustrating the progress towards finding the users preferred parameter values in a graphical user interface.
10 more elements
Dependencies are inferred from the claim text.