Hearing device comprising a noise reduction system

Patent metadata

Field	Value
Publication number	US-12574689-B2
Application number	US-202117562612-A
Country	US
Kind code	B2
Filing date	Dec 27, 2021
Priority date	Feb 8, 2019
Publication date	Mar 10, 2026
Grant date	Mar 10, 2026

Abstract

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) a target signal estimator for providing an estimate of the target signal; b2) a noise estimator for providing an estimate of the noise; b3) a gain estimator for providing respective gain values in said time frequency representation in dependence of said target signal estimate and said noise estimate, wherein said gain estimator comprises a neural network, wherein the weights of the neural network have been trained with a plurality of training signals, and wherein the outputs of the neural network comprise real or complex valued gains, or separate real valued gains and real valued phases. The invention may e.g. be used in audio devices, such as hearing aids, headsets, mobile telephones, etc., operating in noisy acoustic environments.

First claim

The invention claimed is:

1 . A hearing aid 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 aid comprising
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 a signal processor comprising
an SNR estimator for providing a target signal-to-noise ratio (SNR) estimate for said at least one electric input signal in said time frequency representation;
an SNR-to-gain converter for converting said target signal-to-noise ratio estimates to respective gain values in said time frequency representation, wherein said SNR-to-gain converter comprises a neural network, wherein the weights of the neural network have been trained with a plurality of training signals, and wherein the outputs of the neural network comprise complex valued gains, or separate real valued gains and real valued phases,
wherein said time frequency representation of the at least one electric input signal comprises magnitude information as well as phase information, wherein the inputs to said SNR-to-gain converter or to the neural network comprises changes in phase information over time, and wherein said phase changes over time are provided on a per frequency band basis.

2 . A hearing aid according to claim 1 comprising a combination unit and wherein said gain values are applied to said at least one electric input signal to provide a processed signal representative of said sound for further processing or presentation to the user as stimuli perceivable as sound.

3 . A hearing aid according to claim 1 , wherein the inputs to said SNR-to-gain converter comprises magnitude information as well as phase information.

4 . A hearing device according to claim 1 wherein said neural network comprises a convolutional neural network or a recurrent neural network.

5 . A hearing aid according to claim 1 configured to provide that the inputs to said SNR-to-gain converter comprises changes in phase over time or other features derived from the instantaneous phase across time and frequency.

6 . A hearing aid according to claim 1 comprising an analysis filter bank for providing said at least one electric input signal in a time frequency representation.

7 . A hearing aid according to claim 6 comprising a synthesis filter bank for converting a processed version of said least one electric input signal from a time frequency representation to a time-domain representation.

8 . A hearing aid according to claim 6 wherein the neural network is configured to output one gain for each frequency channel, and one separate phase term in radians.

9 . A hearing aid 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 aid comprising
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 a signal processor comprising
a target signal estimator for providing an estimate of the target signal in said time frequency representation;
a noise estimator for providing an estimate of the noise in said time frequency representation;
a gain estimator for providing respective gain values in said time frequency representation in dependence of said target signal estimate and said noise estimate, wherein said gain estimator comprises a neural network, wherein the weights of the neural network have been trained with a plurality of training signals, and wherein the outputs of the neural network comprise real or complex valued gains, or separate real valued gains and real valued phases,
wherein the target and noise estimates are based on a multitude of microphones providing said at least one electric input signal as a multitude of electric input signals, wherein the target and noise estimates are obtained from linear combinations of the multitude of electric input signals, and wherein the target and noise estimates are obtained from a) a target-enhancing beamformer and b) a target cancelling beamformer having a minimum sensitivity direction pointing approximately towards the target source or sources, said beamformers being provided by said linear combinations of said multitude of electric input signals.

10 . A hearing aid according to claim 9 wherein the magnitudes, or the squared magnitudes, or the logarithm of the magnitudes of the target and the noise estimates are input to the neural network.

11 . A hearing aid according to claim 9 wherein the target and noise estimates are based on a single microphone providing said at least one electric input signal.

12 . A hearing aid according to claim 9 , wherein the target-enhancing and/or the target cancelling beamformers are fixed or adaptive.

13 . A hearing aid according to claim 9 , comprising a plurality of target cancelling beamformers simultaneously providing said noise estimate to the input features to the gain estimator, each of said plurality of target cancelling beamformers having a single minimum sensitivity direction pointing towards a different target source.

14 . A hearing aid according to claim 9 configured to provide that the maximum amount of noise reduction provided by the neural network is controlled by level, or modulation, or a degree of sparsity of the inputs to the neural network.

15 . A hearing aid 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 aid comprising
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; a signal processor comprising
an SNR estimator for providing a target signal-to-noise ratio (SNR) estimate for said at least one electric input signal in said time frequency representation;
an SNR-to-gain converter for converting said target signal-to-noise ratio estimates to respective gain values in said time frequency representation, wherein said SNR-to-gain converter comprises a neural network, wherein the weights of the neural network have been trained with a plurality of training signals, and wherein the outputs of the neural network comprise complex valued gains, or separate real valued gains and real valued phases;
an analysis filter bank for providing said at least one electric input signal in a time frequency representation; and a synthesis filter bank for converting a processed version of said least one electric input signal from a time frequency representation to a time-domain representation, wherein the outputs of said SNR-to-gain converter comprises gains as well as phase adjustments, or other output features that can be applied to the at least one electric input signal before the synthesis filter bank in such a way as to change either its magnitude, or phase, or both.

16 . A hearing aid configured to be worn by a user at or in an ear or to be fully or partially implanted in t

Assignees

• Oticon As

Inventors

• Andersen Asger Heidemann
• Jensen Jesper
• Pedersen Michael Syskind
• Rohde Nels Hede
• Olsen Anders Brødløs
• Kristensen Michael Smed
• Bentsen Thomas
• Bertelsen Andreas Thelander

Classifications

• H04R25/407 Primary

  Circuits for combining signals of a plurality of transducers · CPC title

• H04R2225/43

  Signal processing in hearing aids to enhance the speech intelligibility · CPC title

• H04R25/507 Primary

  implemented by neural network or fuzzy logic · CPC title

• H04R1/1083

  Reduction of ambient noise (active noise reduction per se G10K11/175; protective devices for the ear, e.g. providing acoustic protection A61F11/06) · CPC title