Abstract: The present application relates to a hearing aid adapted to be worn in or at an ear of a hearing aid user and/or to be fully or partially implanted in the head of the hearing aid user.

Abstract: A hearing aid adapted to be worn in or at an ear of a hearing aid user and/or to be fully or partially implanted in the head of the hearing aid user is disclosed. The hearing aid comprises a processing unit connected to said input unit and to said output unit, where the processing unit comprises a neural network, and where the processing unit is configured to determine signal processing parameters of the hearing aid based on weights of the neural network. A hearing system and a corresponding method is furthermore disclosed.

Abstract: A method of personalizing one or more parameters of a processing algorithm for use in a hearing aid of a specific user comprises Performing a predictive test for estimating a hearing ability of the user when listening to signals having different characteristics; Analyzing results of said predictive test for said user and providing a hearing ability measure for said user; Selecting a specific processing algorithm of said hearing aid, Selecting a cost-benefit function related to said user's hearing ability in dependence of said different characteristics for said algorithm; and Determining, for said user, one or more personalized parameters of said processing algorithm in dependence of said hearing ability measure and said cost-benefit function.

Abstract: A method of defining and setting a nonlinear signal processing of a hearing device, e.g. a hearing aid, by machine learning is provided.

Abstract: A hearing aid comprises a) a multitude of M input transducers each providing an electric input signal representative of environment sound in a time-frequency representation (k, l), and each comprise varying amounts of target (s) and noise (v) signal components; b) a signal processor configured to process said multitude of electric input signals; and comprising a beamformer filter configured to receive said multitude M of electric input signals and to provide a spatially filtered signal and a post-filter configured to receive said spatially filtered signal and to provide an estimate ?(k,l) of a target signal representing said target signal components from said target sound source. The signal processor is configured to provide estimates of power spectral densities ?s(k,l) of said target signal components in dependence of inter-frequency bin relationships between the spectral components enforced by properties of the electric input signals across at least some of said frequency bins.

Abstract: A hearing aid comprises a) an ITE-part adapted for being located at or in an ear canal of the user, b) a forward path for processing sound from the environment of the user. The forward path comprises b1) at least one first input transducer providing at least one first electric input signal representing said sound as received at the respective at least one first microphone, said at least one first input transducer being located to allow picking up sound from the environment of the user, b2) an audio signal processor comprising a gain unit for applying a frequency and/or level dependent prescribed gain to compensate for a hearing impairment of the user to said at least one first electric input signal, or a signal or signals originating therefrom, and configured to provide a processed signal in dependence thereof, b3) an output transducer for providing stimuli perceivable as sound to the user in dependence of said processed signal.

Abstract: A method of defining and setting a nonlinear signal processing of a hearing device, e.g. a hearing aid, by machine learning is provided.

Abstract: The present application relates to a hearing aid adapted to be worn in or at an ear of a hearing aid user and/or to be fully or partially implanted in the head of the hearing aid user.

Abstract: A hearing device adapted for being worn at or in an ear of a user, comprises a) an input unit comprising at last two input transducers each for converting sound around said hearing device to an electric input signal representing said sound, thereby providing at least two electric input signals; b) a beamformer filter comprising a minimum processing beamformer defined by optimized beamformer weights, the beamformer filter being configured to provide a filtered signal in dependence of said at least two electric input signals and said optimized beamformer weights; c) a reference signal representing sound around said hearing device; d) a performance criterion for said minimum processing beamformer. The minimum processing beamformer is a beamformer that provides the filtered signal with as little modification as possible in terms of a selected distance measure compared to said reference signal, while still fulfilling said performance criterion.

Abstract: The present application relates to a hearing aid adapted to be worn in or at an ear of a hearing aid user and/or to be fully or partially implanted in the head of the hearing aid user.

Abstract: A method of personalizing one or more parameters of a processing algorithm for use in a hearing aid of a specific user comprises Performing a predictive test for estimating a hearing ability of the user when listening to signals having different characteristics; Analyzing results of said predictive test for said user and providing a hearing ability measure for said user; Selecting a specific processing algorithm of said hearing aid, Selecting a cost-benefit function related to said user's hearing ability in dependence of said different characteristics for said algorithm; and Determining, for said user, one or more personalized parameters of said processing algorithm in dependence of said hearing ability measure and said cost-benefit function.

Abstract: A hearing aid comprises a) a multitude of M input transducers each providing an electric input signal representative of environment sound in a time-frequency representation (k, l), and each comprise varying amounts of target (s) and noise (v) signal components; b) a signal processor configured to process said multitude of electric input signals; and comprising a beamformer filter configured to receive said multitude M of electric input signals and to provide a spatially filtered signal and a post-filter configured to receive said spatially filtered signal and to provide an estimate ?(k, l) of a target signal representing said target signal components from said target sound source. The signal processor is configured to provide estimates of power spectral densities ?s(k, l) of said target signal components in dependence of inter-frequency bin relationships between the spectral components enforced by properties of the electric input signals across at least some of said frequency bins.

Abstract: The present application relates to a hearing aid adapted to be worn in or at an ear of a hearing aid user and/or to be fully or partially implanted in the head of the hearing aid user.

Abstract: A method of defining and setting a nonlinear signal processing of a hearing device, e.g. a hearing aid, by machine learning is provided.

Abstract: A binaural hearing system comprises A) left and right hearing devices, each comprising a1) an input unit providing an electric input signal representing sound; and a2) an output unit, B) a binaural level and/or gain estimator comprising b1) left and right level estimators, each comprising respective fast and slow level estimators configured to provide respective fast and slow level estimates of respective electric input signals, b2) a fast binaural level comparison unit receiving the fast level estimates of the respective left and right fast level estimators and providing a fast binaural level comparison estimate; and b3) a fast binaural level and/or gain enhancer providing respective left and right binaural level and/or gain modification estimates, in dependence of said fast binaural level comparison estimate at said left and right ears, respectively, of the user. The binaural hearing system provides that the interaural level cues are either compressed, maintained or enhanced independent of each other.

Abstract: A system for monitoring the status and/or performance of one or more hearing devices is disclosed. The system comprises a number of access points configured to receive wireless signals transmitted by the hearing devices, wherein the access points are connected to a central unit communicatively connected to the Internet/cloud, wherein the system is configured to automatically monitor the status and/or performance of one or more parameter of the one or more hearing devices received by access points, wherein the monitored parameters are accessible from the central unit and/or from a cloud service.

Abstract: A binaural hearing system comprises A) left and right hearing devices, each comprising a1) an input unit providing an electric input signal representing sound; and a2) an output unit, B) a binaural level and/or gain estimator comprising b1) left and right level estimators, each comprising respective fast and slow level estimators configured to provide respective fast and slow level estimates of respective electric input signals, h2) a fast binaural level comparison unit receiving the fast level estimates of the respective left and right fast level estimators and providing a fast binaural level comparison estimate; and h3) a fast binaural level and/or gain enhancer providing respective left and right binaural level and/or gain modification estimates, in dependence of said fast binaural level comparison estimate at said left and right ears, respectively, of the user. The binaural hearing system provides that the interaural level cues are either compressed, maintained or enhanced independent of each other.

Abstract: A system for monitoring the status and/or performance of one or more hearing devices is disclosed. The system comprises a number of access points configured to receive wireless signals transmitted by the hearing devices, wherein the access points are connected to a central unit communicatively connected to the Internet/cloud, wherein the system is configured to automatically monitor the status and/or performance of one or more parameter of the one or more hearing devices received by access points, wherein the monitored parameters are accessible from the central unit and/or from a cloud service.

Abstract: A binaural hearing system comprises A) left and right hearing devices, each comprising a1) an input unit providing an electric input signal representing sound; and a2) an output unit, B) a binaural level and/or gain estimator comprising b1) left and right level estimators, each comprising respective fast and slow level estimators configured to provide respective fast and slow level estimates of respective electric input signals, b2) a fast binaural level comparison unit receiving the fast level estimates of the respective left and right fast level estimators and providing a fast binaural level comparison estimate; and b3) a fast binaural level and/or gain enhancer providing respective left and right binaural level and/or gain modification estimates, in dependence of said fast binaural level comparison estimate at said left and right ears, respectively, of the user. The binaural hearing system provides that the interaural level cues are either compressed, maintained or enhanced independent of each other.

Abstract: A system for monitoring the status and/or performance of one or more hearing devices is disclosed. The system comprises a number of access points configured to receive wireless signals transmitted by the hearing devices, wherein the access points are connected to a central unit communicatively connected to the Internet/cloud, wherein the system is configured to automatically monitor the status and/or performance of one or more parameter of the one or more hearing devices received by access points, wherein the monitored parameters are accessible from the central unit and/or from a cloud service.