A method of defining and setting a nonlinear signal processing of a hearing device, e.g. a hearing aid, by a deep neural network, the hearing device being configured to be worn by a user at or in an ear or to be fully or partially implanted in the head at an ear of the user, the method comprising: - providing at least one electric input signal representing at least one input sound signal from an environment of a hearing device user, - determining a normal-hearing representation of said at least one electric input signal based on a normal-hearing auditory model, - determining a hearing-impaired representation of said at least one electric input signal based on a hearing-impaired auditory model and on at least one provided audiogram, - determining optimised training parameters of the deep neural network by training the deep neural network, where determining optimised training parameters comprises iteratively - comparing the normal-hearing representation with the hearing-impaired representation to determine a degree of matching between the normal-hearing representation and the hearing-impaired representation, and - adjusting the training parameters based on the degree of matching between the normal-hearing representation and the hearing-impaired representation, - until the degree of matching fulfils predetermined requirements, and, - when the degree of matching fulfils the predetermined requirements, determining corresponding signal processing parameters of the hearing device based on the optimised training parameters, - wherein the method further comprises providing at least one supra-threshold measure comprising customised measurements as input to the hearing-impaired auditory model to optimize the ability of the neural network to adjust its parameters until the degree of matching between the normal-hearing representation and the hearing-impaired representation fulfils the predetermined requirements and provide an individualized training, and where determining a hearing-impaired representation of said at least one electric input signal is further based on said at least one supra-threshold measure. - providing at least one electric input signal representing at least one input sound signal from an environment of a hearing device user, - determining a normal-hearing representation of said at least one electric input signal based on a normal-hearing auditory model, - determining a hearing-impaired representation of said at least one electric input signal based on a hearing-impaired auditory model and on at least one provided audiogram, - determining optimised training parameters of the deep neural network by training the deep neural network, where determining optimised training parameters comprises iteratively - comparing the normal-hearing representation with the hearing-impaired representation to determine a degree of matching between the normal-hearing representation and the hearing-impaired representation, and - adjusting the training parameters based on the degree of matching between the normal-hearing representation and the hearing-impaired representation, - comparing the normal-hearing representation with the hearing-impaired representation to determine a degree of matching between the normal-hearing representation and the hearing-impaired representation, and - adjusting the training parameters based on the degree of matching between the normal-hearing representation and the hearing-impaired representation, - until the degree of matching fulfils predetermined requirements, and, - when the degree of matching fulfils the predetermined requirements, determining corresponding signal processing parameters of the hearing device based on the optimised training parameters, - wherein the method further comprises providing at least one supra-threshold measure comprising customised measurements as input to the hearing-impaired auditory model to optimize the ability of the neural network to adjust its parameters until the degree of matching between the normal-hearing representation and the hearing-impaired representation fulfils the predetermined requirements and provide an individualized training, and where determining a hearing-impaired representation of said at least one electric input signal is further based on said at least one supra-threshold measure.