Oticon A/s

Michael Smed Kristensen

Michael Syskind Pedersen

Jesper Bruun Jensen

Svend Oscar Petersen

Nels Hede Rohde

Asger Heidemann Andersen

Thomas Bentsen

Anders Brødløs Olsen

Thomas Kaulberg

Steen Michael Munk

Andreas Thelander Bertelsen

Anders Meng

Jesper Nøhr Hansen

Jesper Hansen

Svend Oscar Pedersen

A hearing device, e.g. a hearing aid, is configured to be arranged at least partly on a user's head or at least partly implanted in a user's head. The hearing device comprises a) at least one input transducer for picking up an input sound signal from the environment and providing at least one electric input signal representing said input sound signal; b) a signal processor connected to the at least one input transducer, the signal processor being configured to analyze the electric input signal and to provide a transmit control signal in dependence thereof; c) a memory buffer, e.g. a cyclic buffer, for storing a current time segment of a certain duration of said at least one electric input signal, or a processed version thereof; and a transmitter for transmitting at least a part of said time segment, or a processed version thereof, to an external device in dependence of said transmit control signal.

Hearing device comprising a transmitter

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.

Hearing device comprising a detector and a trained neural network

A hearing device, e.g. a hearing aid, is configured to be arranged at least partly on a user's head or at least partly implanted in a user's head. The hearing device comprises a) at least one input transducer for picking up an input sound signal from the environment and providing at least one electric input signal representing said input sound signal; b) a signal processor providing a processed signal based on one or more of said at least one electric input signals; c) an output unit for converting said processed signal or a signal originating therefrom to stimuli perceivable by said user as sound; d) a keyword spotting system comprising d1) a keyword detector configured to detect a limited number of predefined keywords or phrases or sounds in said at least one electric input signal or in a signal derived therefrom, and to provide a keyword indicator of whether or not, or with what probability, said keywords or phrases or sounds are detected, and d2) an own voice detector for providing an own voice indicator estimating whether or not, or with what probability, a given input sound signal originates from the voice of the user of the hearing device. The hearing device further comprises e) a controller configured to provide an own-voice-keyword indicator of whether or not or with what probability a given one of said keywords or phrases or sounds is currently detected and spoken by said user, said own-voice-keyword indicator being dependent on said keyword indicator and said own voice indicator.

Hearing device comprising a keyword detector and an own voice detector and/or a transmitter

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&#x2014;in said particular adaptation-mode of operation&#x2014;routing said feature vectors to said transmitter for transmission to said another part or device or server, and&#x2014;in a normal mode of operation&#x2014;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&#x2014;in said particular adaptation-mode of operation&#x2014;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, 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.

Hearing device comprising a noise reduction system

A method detects whether an ear mold of a listening device is correctly mounted in the ear of a user. An indication of whether or not a mold of a listening device is correctly mounted in an ear canal of a user is provided. The method comprises a) providing a long term estimate of the feedback path; b) providing an estimate of the current feedback path; c) comparing the long term feedback path estimate with the current feedback path estimate, and providing a measure of their difference, termed the feedback difference measure FBDM; and optionally d) providing an alarm indication, if the feedback difference measure exceeds a predefined threshold.

Listening device and a method of monitoring the fitting of an ear mould of a listening device

The application relates to a hearing device comprising a) a forward path between an input transducer for converting an input sound to an electric input signal and an output transducer for converting an electric output signal to an output sound, the forward path comprising a signal processing unit for applying a level and/or frequency dependent gain to the electric input signal or a signal originating therefrom and for providing a processed signal, and feeding the processed signal or a signal originating therefrom to the output transducer, an acoustic feedback path being defined from said output transducer to said input transducer; b) a configurable anti-feedback system comprising a feedback estimation unit for providing an estimate of said acoustic feedback path; c) a number of detectors, each providing a detector signal for characterizing a signal of the forward path. The object of the present application is to save power in a hearing device. The problem is solved in that the hearing device further comprises an activation control unit configured to control the anti-feedback system based on said detector signals, and to bring the anti-feedback system into one of at least two predefined modes based on said detector signals, said at least two predefined modes comprising an ON-mode and an OFF-mode. The invention may e.g. be used in hearing aids, headsets, ear phones, active ear protection systems, or similar portable devices, where a need for feedback cancellation and low power consumption is important.

Hearing device comprising an anti-feedback power down detector

The application relates to a hearing assistance device and to a method of performing a real ear measurement. The method comprises providing a first controlled acoustic feedback path from an output transducer to a measurement input transducer via a standard acoustic coupler; generating a first probe signal; estimating and storing a first estimate of the first controlled acoustic feedback path; and providing a second controlled acoustic feedback path from the output transducer to the measurement input transducer via the residual volume between the ITE part of the hearing aid device and the user's eardrum; generating a second probe signal; estimating and storing a second estimate of the second controlled acoustic feedback path; and determining a real ear to coupler difference from said first and second acoustic feedback estimates. An alternative and relatively simple method of determining an RECD-value in hearing assistance device of a particular user is thereby provided.

Method of performing an RECD measurement using a hearing assistance device

A method provides a long term feedback path estimate of a listening device. The method comprises a) providing an estimate of the current feedback path; b) providing a number of detectors of parameters or properties of the acoustic environment of the listening device and/or of a signal of the listening device, each detector providing one or more detector signals; c) providing a criterion for deciding whether an estimate of the current feedback path is reliable based on said detector signals; d) storing said estimate of the current feedback path, if said criterion IS fulfilled and neglecting said estimate of the current feedback path, if said criterion is NOT fulfilled; e) providing a long term estimate of the feedback path based on said stored estimate(s) of the current feedback path.

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Smørum, Denmark

Michael Smed Kristensen