A hearing device component (6) comprises a sensor-unit (8) for receiving an audio-signal (AS), a separation device (9) for separating part-signals (PS.sub.i) from the audio-signal (AS), a classification device (10) for classifying the part-signals (PS.sub.i) separated from the audio-signals (AS), and a modulation device (11) for modulating the part-signals (PS.sub.i), wherein the classification device (10) is communicatively coupled to the modulation device (11) and wherein the modulation device (11) is designed to enable a concurrent modulation of different part-signals (PS.sub.i) with different modulation-functions depending on their classification.

Hearing aid system comprising at least one hearing aid is provided. The hearing aid system further comprising an input unit for receiving an input sound signal from an environment of the hearing aid user and providing at least one electric input signal representing said input sound signal, an output unit for providing at least one set of stimuli perceivable as sound to the hearing aid user based on processed versions of said at least one electric input signal, a processing unit connected to said input unit and to said output unit and comprising signal processing parameters to provide said processed versions of said at least one electric input signal, at least one photoplethysmogram (PPG) sensor configured to provide a PPG signal of the hearing aid user, and a listening effort determination unit configured to provide at least one PPG morphology parameter value based at least on the PPG signal, compare the at least one PPG morphology parameter value with at least one corresponding reference PPG morphology parameter value and determine a morphology comparison measure, and determine a listening effort of the hearing aid user. A hearing aid is further provided.

Disclosed herein, among other things, are systems and methods for a user adjustment interface using remote computing resources. Specifically, a system can include a mobile device in communication with a hearing assistance device or a remote server. The mobile device can interpret an acoustic environment and send information about the environment to a remote server. The remote server can determine and send information to the mobile device for use in a user interface. The mobile device can receive a user selection of hearing assistance parameter information to be sent to the hearing assistance device.

A hearing system performs nonlinear processing of signals received from a plurality of microphones using a neural network to enhance a target signal in a noisy environment. In various embodiments, the neural network can be trained to improve a signal-to-noise ratio without causing substantial distortion of the target signal. An example of the target sound includes speech, and the neural network is used to improve speech intelligibility.

This invention provides a new and improved hearing aid system with high quality noise cancellation method and devices to overcome the limitations and difficulties encountered in conventional technologies. The technical limitations of the noise uncertainty and speech distortion in the hearing aid field are resolved by restoration of the high-quality speech by converting the speech content into an intermediate linguistic representation and by synthesizing the speech of the same speaker with pre-trained using artificial intelligence (AI) modules. In this invention, the noise uncertainties are circumvented by focusing on the target speaker or picking up the dominant speech by choosing the corresponding setting assuming the speech from the target speaker is the dominant speech based on the Lombard effect.

A hearing device, e.g. a hearing aid or a headset, configured to be worn by a comprises an input unit for providing at least one electric input signal in a time-frequency representation; and a signal processor comprising a target signal estimator for providing an estimate of the target signal; a noise estimator for providing an estimate of the noise; and a gain estimator for providing respective gain values in dependence of said target signal estimate and said noise estimate. The gain estimator comprises a trained neural network, wherein the outputs of the neural network comprise real or complex valued gains, or separate real valued gains and real valued phases. The signal processor is configured—at a given time instance t—to calculate changes Δx(i,t)=x(i,t)−{circumflex over (x)}(i,t−1), and Δh(j,t−1)=h(j,t−1)−ĥ(j,t−2) to an input vector x(t) and to the hidden state vector h(t−1), respectively, from one time instance, t−1, to the next, t, and where {circumflex over (x)}(i,t−1) and ĥ(j,t−2) are estimated values of x(i,t−1) and h(j,t−2), respectively, where indices i, j refers to the i.sup.th input neuron and the j.sup.th neuron of the hidden state, respectively, where 1≤i≤N.sub.ch,x and 1≤j≤N.sub.ch,oh, wherein N.sub.ch,x and N.sub.ch,oh is the number of processing channels of the input vector x and the hidden state vector h, respectively, and wherein the signal processor is further configured to provide that the number of updated channels among said N.sub.ch,x and said N.sub.ch,oh processing channels of the modified gated recurrent unit for said input vector x(t) and said hidden state vector h(t−1), respectively, at said given time instance t is limited to a number of peak values N.sub.p,x, and N.sub.p,oh, respectively, where N.sub.p,x is smaller than N.sub.ch,x, and N.sub.p,oh, is smaller than N.sub.ch,oh.

A hearing device comprises an input transducer comprising a microphone for providing an electric input signal representative of sound in the environment of the hearing device, a pre-processor for processing electric input signal and providing a multitude of feature vectors, each being representative of a time segment thereof, a neural network processor adapted to implement a neural network for implementing a detector configured to provide an output indicative of a characteristic property of the at least one electric input signal, the neural network being configured to receive said multitude of feature vectors as input vectors and to provide corresponding output vectors representative of said output of said detector in dependence of said input vectors. The hearing device further comprises a transceiver comprising a transmitter and a receiver for establishing a communication link to another part or device or server, at least in a particular adaptation-mode of operation, and a selector for—in said particular adaptation-mode of operation—routing said feature vectors to said transmitter for transmission to said another part or device or server, and—in a normal mode of operation—to route said feature vectors to said neural network processor for use as inputs to said neural network, a neural network controller connected to said neural network processor for—in said particular adaptation-mode of operation—receiving optimized node parameters, and to apply said optimized node parameters to said nodes of said neural network to thereby implement an optimized neural network in said neural network processor, wherein the optimized node parameters have been selected among a multitude of sets of node parameters for respective candidate neural networks according to a predefined criterion in dependence of said feature vectors. A method of selecting optimized parameters for a neural network for use in a portable hearing device is further disclosed. The invention may e.g. be used in hearing aids or headsets, or similar, e.g. wearable, devices.

A hearing device comprises a) at least one input transducer configured to pick up sound from an acoustic environment around the user when the user is wearing the hearing device, the at least one input transducer providing at least one electric input signal representative of said sound, b) at least one analysis filter bank configured to provide said at least one electric input signal as a multitude of frequency sub-band signals, the at least one analysis filter bank comprising b1) a plurality of M first filters h.sub.m(n), whose impulse responses are modulated from a first prototype filter h(n), where m=0, 1, . . . , M−1 is a frequency band index, and n is a time index, c) a processor for processing said at least one electric input signal provided by said at least one analysis filter bank, or a signal originating therefrom, and providing a processed signal, d) an output transducer configured to provide stimuli perceivable as sound to the user in dependence of said processed signal, and e) a controller for controlling said analysis filter bank by applying a different first prototype filter to said at least one filter bank in dependence of said current acoustic environment. A method of operating a hearing device is further disclosed.

A method and system of audio processing encodes cochlear-simulating spike data into spectrogram data.

A hearing device, e.g. a hearing aid, comprises a) an input unit configured to provide at least one time-variant electric input signal representing sound, the at least one electric input signal comprising target signal components and optionally noise signal components, the target signal components originating from a target sound source; b) a signal processing unit for processing the at least one electric input signal and providing a processed signal; c) an output unit for creating output stimuli configured to be perceivable by the user as sound based on the processed signal from the signal processing unit; d) a speech presence probability prediction unit for repeatedly providing a measure of a predicted speech presence probability of the at least one electric input signal, or of a signal originating therefrom; and e) a speech intelligibility prediction unit for repeatedly providing a current measure of a predicted speech intelligibility of the at least one electric input signal, or of a signal originating therefrom. The speech intelligibility prediction unit is configured to determine said current measure of the predicted speech intelligibility in dependence of said measure of the predicted speech presence probability. A method of operating a hearing device is further disclosed. The invention may e.g. be used in hearing aids, headsets, earpieces (ear buds), etc.