Hearing aid personalization using machine leaning
Abstract:
Training data are obtained. Each training datum includes environment characteristics obtained based on sensor data. Respective user settings corresponding to the training data are obtained. At least one respective user setting corresponds to one training datum, and a respective user setting is indicative of a user preference of at least one parameter of a hearing aid device. A machine-learning model for the hearing aid device is trained to output values for the at least one parameter. The hearing aid device is reconfigured based on an output of the machine-learning model. Reconfiguring the hearing aid device includes using current environment characteristics as an input to the machine-learning model to obtain at least one current value for the at least one parameter and configuring the hearing aid device to use at least one current value.
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