A method for improving a listening experience of a user wearing a hearing device of a hearing system includes providing an audio sample based on a generated audio signal; determining, whether the audio sample comprises audio content matching a predetermined sound pattern indicative of an original version of the audio content; comparing the audio sample with the original version of the audio content, if the audio sample is determined to comprise the audio content matching the predetermined sound pattern; determining at least one acoustic property of current surroundings of the user depending on the comparison; determining at least one parameter for modifying the audio signal depending on the determined acoustic property; modifying the audio signal generated by the sound input component by the sound processing module, in accordance with the determined parameter; and outputting the modified audio signal to the user.

A method of defining and setting a nonlinear signal processing of a hearing device, e.g. a hearing aid, by machine learning is provided. 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, determining optimised training parameters by machine learning, where determining optimised training parameters comprises iteratively adjusting the training parameters, and 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, 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. A hearing device is further provided.

A hearing aid system configured to compensate for a hearing impairment of a use comprises A) a wearable device adapted for being worn by the user and comprising a1) an input stage comprising at least one input transducer for converting sound around the user to at least one electric input signal representing said sound, and a2) an input stage for providing stimuli representative of a processed version of said least one electric input signal to said user, said stimuli being perceivable by said user as sound; and B) a non-wearable device comprising b1) a processor, and b2) a power supply interface for providing power to the processor. The wearable device and the non-wearable device comprise respective transceiver circuitry for establishing a low latency wireless audio communication link between them. The processor of the non-wearable device comprises an audio processor configured to process said at least one electric input signal, or a signal originating therefrom, to at least partially compensate for the hearing impairment of the user and to provide said processed version thereof. The power supply interface of the non-wearable device is electrically connected to an electricity network. Thereby an improved processing power of a hearing aid may be provided. The invention may e.g. be used in flexible hearing aid systems with a situation-dependent configurable processing power.

Systems and methods for assisting user with hearing by amplifying sound using an amplifier with gain and amplitude controls for a plurality of frequencies; and applying a learning machine to identify an aural environment and adjust the amplifiers for optimum hearing.

For the fitting of a hearing instrument, an audio signal of an ambient sound, recorded by way of an input transducer, is modified according to a multiplicity of signal processing parameters. Via a first classifier, a user of the hearing instrument is offered a plurality of problem descriptions for the user to select. By way of a second classifier, a proposed solution for modified values of the signal processing parameters is determined based on the user's selection of one of the offered problem descriptions.

A hearing aid system comprising at least a first hearing aid, wherein the first hearing aid is configured to establish a communication link over the internet with a remote entity based on a protocol stack, wherein the protocol stack includes an internet protocol, and the protocol stack is implemented in the first hearing aid.

Presented herein are techniques for extracting features from sound signals received at a hearing prosthesis at least partially based on an environmental classification of the sound signals. More specifically, one or more sound signals are received at a hearing prosthesis and are converted in to stimulation control signals for use in delivering stimulation to a recipient of the hearing prosthesis. The hearing prosthesis determines an environmental classification of the sound environment associated with the one or more sound signals and is configured to use the environmental classification in the determination of a feature-based adjustment for incorporation into the stimulation control signals.

A hearing device is disclosed, comprising a main microphone, M auxiliary microphones, a transform circuit, a processor, a memory and a post-processing circuit. The transform circuit transforms first sample values in current frames of a main audio signal and M auxiliary audio signals from the microphones into a main and M auxiliary spectral representations. The memory includes instructions to be executed by the processor to perform operations comprising: performing ANC over the first sample values using an end-to-end neural network to generate second sample values; and, performing audio signal processing over the main and the M auxiliary spectral representations using the end-to-end neural network to generate a compensation mask. The post-processing circuit modifies the main spectral representation with the compensation mask to generate a compensated spectral representation, and generates an output audio signal according to the second sample values and the compensated spectral representation.

A system is provided. The system includes an analyzer for determining a plurality of binaural room impulse responses, and a loudspeaker signal generator for generating at least two loudspeaker signals depending on the plurality of binaural room impulse responses and depending on the audio source signal of at least one audio source. The analyzer is configured to determine the plurality of the binaural room impulse responses such that each of the plurality of the binaural room impulse responses considers an effect that results from a headphone being worn by a user.

Systems and methods for assisting user with hearing by amplifying sound using an amplifier with gain and amplitude controls for a plurality of frequencies; and applying a learning machine to identify an aural environment and adjust the amplifiers for optimum hearing.