A hearing device includes a feedback control system that applies an adaptive filtering algorithm. The adaptive algorithm provides a filter control signal to adaptively control filter coefficients based on first and second algorithm input signals of a forward path. The feedback control system further includes first and second transform units for transforming the first and second algorithm input signals to the transform domain, and an inverse transform unit to convert an estimate of the current feedback path in the transformed domain to a time domain estimate, and a combination unit in the forward path to subtract the estimate of the current feedback signal from a signal of the forward path to provide a feedback corrected signal.

A method operates a hearing aid, in particular a classic hearing aid. The hearing aid includes an input transducer, a signal processing device, and an output transducer. Wherein an occurrence of a comb filter effect is determined by the signal processing device, and wherein a countermeasure is controlled by the signal processing device as a function of the determined occurrence of the comb filter effect.

A listening system includes a first microphone device and a second microphone device that generate a first electronic signal and a second electronic signal corresponding to sound within audio detection range. Control logic of the first microphone device detects a crosstalk audio signal from a direction of the second microphone device that matches the second electronic signal. The first electronic signal includes a mixture that includes the crosstalk audio signal. An ear playback device is associated with the second microphone device. A processing device receives the first electronic signal and the second electronic signal, removes the second electronic signal from the first electronic signal to generate a cleansed first electronic signal, and processes the cleansed first electronic signal to integrate the cleansed first electronic signal into an output signal to the ear playback device.

A hearing aid includes an input unit, an output unit, a signal processing unit connected to the input unit and output unit, where the input unit, the signal processing unit and the output unit form 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 reduction unit configured to reduce risk of howl due to acoustic, electrical, and/or mechanical feedback of an external feedback path from the output unit to the input unit. The feedback reduction unit is configured to modulate the forward gain in time to provide that the forward gain exhibits an increased or unchanged forward gain in one or more first time periods and a reduced forward gain in one or more second time periods.

An illustrative wearable hearing device or hearing aid includes: a speaker that converts a reproduced signal into reproduced audio; a microphone that converts ambient audio into a receive signal, the ambient audio potentially including a feedback component; a feedback filter that filters the reproduced signal to obtain an estimated feedback component; a combiner that derives the reproduced signal from the receive signal at least in part by subtracting the estimated feedback component; and a controller that, subject to an adaptation rate, adjusts coefficients of the feedback filter to at least partially cancel the feedback component, the controller varying the adaption rate based at least in part on one or more proximity sensor signals.

A hearing device includes a microphone that produces an audio input signal and a loudspeaker that outputs an amplified audio signal into an ear canal. A signal processing path is coupled to the microphone and the loudspeaker. The signal processing path includes a deep neural network configured to predict an instantaneous gain margin of the hearing device based on a set of inputs. The set of inputs includes a first parameter of the audio input signal, a second parameter of the amplified audio signal, and a gain of the signal processing path. A feedback reduction module of the device receives the predicted instantaneous gain margin and adjusts feedback reduction parameters to reduce an onset of feedback in the hearing device

The disclosure generally relates to a method, system and apparatus to improve a user's understanding of speech in real-time conversations by processing the audio through a neural network contained in a hearing device. The hearing device may be a headphone or hearing aid. In one embodiment, the disclosure relates to an apparatus to enhance incoming audio signal. The apparatus includes a controller to receive an incoming signal and provide a controller output signal; a neural network engine (NNE) circuitry in communication with the controller, the NNE circuitry activatable by the controller, the NNE circuitry configured to generate an NNE output signal from the controller output signal; and a digital signal processing (DSP) circuitry to receive one or more of controller output signal or the NNE circuitry output signal to thereby generate a processed signal; wherein the controller determines a processing path of the controller output signal through one of the DSP or the NNE circuitries as a function of one or more of predefined parameters, incoming signal characteristics and NNE circuitry feedback.

A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user's voice, storing the user's voice in a memory of an earpiece device, or storing the user's voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.

A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user's voice, storing the user's voice in a memory of an earpiece device, or storing the user's voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.

A method including obtaining data based on a current and/or anticipated future state of a hearing prosthesis and adjusting a set gain margin of the hearing prosthesis based on the current or anticipated future state of the hearing prosthesis.