A method, comprising receiving at least one sound at an electronic device. The at least one sound is enhanced for the at least one user based on a compound metric. The compound metric is calculated using at least two sound metrics selected from an engineering metric, a perceptual metric, and a physiological metric. The engineering metric comprises a difference between an output signal and a desired signal. At least one of the perceptual metric and the physiological metric is based at least in part on input sensed from the at least one user in response to the received at least one sound.

An ear-wearable electronic device is operable to apply a low-pass filter to the digitized voice signal to remove a high-frequency component and obtain a low-frequency component. Speech enhancement is applied to the low-frequency component. Blind bandwidth extension is applied to the enhanced low-frequency component to recover or synthesize an estimate of at least part of the high frequency component. An enhanced speech signal is output that is a combination of the enhanced low-frequency component and the bandwidth-extended high frequency component.

Disclosed herein, among other things, are apparatus and methods for neural network-driven frequency translation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to train a processor to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained processor to control frequency translation of the input signal.

Examples disclosed herein are relevant to monitoring and treating sensory conditions affecting an individual. Sensors and intelligence integrated within a sensory prosthesis (e.g., an auditory prosthesis) can automatically obtain objective data regarding the ability of one or more of an individuals senses during day-to-day activities. A treatment action can be taken based on the objective data. Further disclosed herein are techniques relating to reducing the gathering of irrelevant sensory input and automatically transmitting relevant data to a caregiver device.

Disclosed herein, among other things, are apparatus and methods for neural network-driven feedback cancellation for hearing assistance devices. Various embodiments include a method of signal processing an input signal in a hearing assistance device to mitigate entrainment, the hearing assistance device including a receiver and a microphone. The method includes performing neural network processing to identify acoustic features in a plurality of audio signals and predict target outputs for the plurality of audio signals, and using the trained neural network to control acoustic feedback cancellation of the input signal.

A body worn or implantable hearing prosthesis, including a device configured to capture an audio environment of a recipient and evoke a hearing percept based at least in part on the captured audio environment, wherein the hearing prosthesis is configured to identify, based on the captured audio environment, one or more biomarkers present in the audio environment indicative of the recipient's ability to hear.

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.

Scene and/or state information may be used to facilitate processing an input to separate one or more signals within the input, to shape the signal within the input, and/or for other processing of the input or signal(s) within the input. A scene determination may be made based upon location data, time data, data describing the received input, or other basis. A state determination may be made based upon the scene determination, properties of a signal itself, or other information such as location, time, etc. By determining an appropriate scene and/or state, processing of an input and/or a signal within an input may proceed in a fashion determined to provide the most valuable information for output. Systems and methods in accordance with the invention may be implemented in a wide variety of baseband processing systems, such as hearing aids and energy consumption monitoring systems.

A hearing device, e.g. a hearing aid, is 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 hearing device comprises a) an input unit for providing at least one electric input signal in a time frequency representation k, m, where k and m are frequency and time indices, respectively, and k represents a frequency channel, the at least one electric input signal being representative of sound and comprising target signal components and noise components; and b) a signal processor comprising b1) an SNR estimator for providing a target signal-to-noise ratio estimate for said at least one electric input signal in said time frequency representation; and b2) an SNR-to-gain converter for converting said target signal-to-noise ratio estimate to respective gain values in said time frequency representation. The signal processor comprises a neural network, wherein the weights of the neural network have been trained with a plurality of training signals. A method of operating a hearing aid is further disclosed. The invention may e.g. be used in audio devices, such as hearing aids, headsets, mobile telephones, etc., operating in noisy acoustic environments.

A hearing aid includes an input unit, an output unit, a signal processing unit connected to said input unit and output unit, where the input unit, the signal processing unit and the output unit are forming part of a forward path of the hearing aid, where the signal processing unit is configured to apply a forward gain to the at least one electric input signal or a signal originating therefrom. The hearing aid further includes a feedback control unit configured to reduce a risk of howl due to acoustic, electrical, and/or mechanical feedback of an external feedback path from the output unit to the input unit of said hearing aid, where the hearing aid is configured to receive motion data characterising movement and/or acceleration and/or orientation and/or position of the hearing aid to control processing.