Oticon A/s

Asger Heidemann Andersen

Jesper Bruun Jensen

Michael Syskind Pedersen

Jan Mark De Haan

Nels Hede Rohde

Thomas Bentsen

Michael Smed Kristensen

Anders Brødløs Olsen

Svend Oscar Petersen

Andreas Thelander Bertelsen

David Thorn Blix

Zuzana Jelcicová

Rasmus Jones

Zheng-Hua Tan

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.

Hearing device comprising a speech intelligibility estimator

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 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&#x2014;at a given time instance t&#x2014;to calculate changes &#x394;x(i,t)=x(i,t)&#x2212;{circumflex over (x)}(i,t&#x2212;1), and &#x394;h(j,t&#x2212;1)=h(j,t&#x2212;1)&#x2212;&#x125;(j,t&#x2212;2) to an input vector x(t) and to the hidden state vector h(t&#x2212;1), respectively, from one time instance, t&#x2212;1, to the next, t, and where {circumflex over (x)}(i,t&#x2212;1) and &#x125;(j,t&#x2212;2) are estimated values of x(i,t&#x2212;1) and h(j,t&#x2212;2), respectively, where indices i, j refers to the iinput neuron and the jneuron of the hidden state, respectively, where 1&#x2264;i&#x2264;Nand&#x2264;j&#x2264;N, wherein Nand Nis 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 Nand said Nprocessing channels of the modified gated recurrent unit for said input vector x(t) and said hidden state vector h(t&#x2212;1), respectively, at said given time instance t is limited to a number of peak values N, and N, respectively, where Nis smaller than N, and N, is smaller than N.

Hearing device comprising a recurrent neural network and a method of processing an audio signal

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 of training an algorithm for optimizing intelligibility of speech components of a sound signal in hearing aids, headsets, etc., comprises a) providing a first database comprising a multitude of predefined time segments of first electric input signals representing sound and corresponding measured speech intelligibilities; b) determining optimized first parameters of a first algorithm by optimizing it with said predefined time segments and said corresponding measured speech intelligibilities, the first algorithm providing corresponding predicted speech intelligibilities; c) providing a second database comprising a multitude of time segments of second electric input signals representing sound, d) determining optimized second parameters of a second algorithm by optimizing it with said multitude of time segments, said second algorithm being configured to provide processed second electric input signals exhibiting respective predicted speech intelligibilities estimated by said first algorithm, said optimizing being conducted under a constraint of maximizing said predicted speech intelligibility.

Method of operating a hearing device and a hearing device providing speech enhancement based on an algorithm optimized with a speech intelligibility prediction algorithm

The application relates to a binaural hearing system comprising left and right hearing devices, e.g. hearing aids, each comprising a) a multitude of input units, each providing a time-variant electric input signal x(t) representing sound received at an iinput unit, t representing time, the electric input signal x(t) comprising a target signal component s(t) and a noise signal component v(t), the target signal component originating from a target signal source; b) a configurable signal processing unit for processing the electric input signals and providing a processed signal y(t); c) an output unit for creating output stimuli to the user, d) transceiver circuitry allowing information to be exchanged between the hearing devices, and e) a binaural speech intelligibility (SI) prediction unit for providing a binaural SI-measure of the predicted speech intelligibility of the user when exposed to said output stimuli, based on processed signals y(t), y(t) from the signal processing units of the respective left and right hearing devices. This allows the hearing devices to control the processing of the respective electric input signals based on said binaural SI-measure.

Hearing system comprising a binaural speech intelligibility predictor

A monaural intrusive speech intelligibility predictor unit comprises: first and second input units for providing time-frequency representations s(k,m) and x(k,m) of noise-free and noisy and/or processed versions of a target signal, respectively, k being a frequency bin index, k=1, 2, . . . , K, and m being a time index; first and second envelope extraction units for providing time-frequency sub-band representations of the signals s(m) and x(m), j being a frequency sub-band index, j=1, 2, . . . , J; first and second time-frequency segment division units for dividing the time-frequency sub-band representations s(m) and x(m) into time-frequency segments Sand Xcorresponding to a number N of successive samples of the sub-band signals; an intermediate speech intelligibility calculation unit adapted for providing intermediate speech intelligibility coefficients destimating an intelligibility of said time-frequency segment X, based on said time-frequency segments Sand Xor normalized and/or transformed versions {tilde over (S)}, and {tilde over (X)}thereof; and a final monaural speech intelligibility calculation unit for calculating a final monaural speech intelligibility predictor d estimating an intelligibility of said noisy and/or processed version x of the target signal by combining said intermediate speech intelligibility coefficients d, or a transformed version thereof, over time. A hearing aid comprises a monaural, intrusive intelligibility predictor unit, and a configurable signal processor adapted to control or influence the processing of one or more electric input signals representing environment sound to maximize the final speech intelligibility predictor d. A binaural hearing aid system comprises first and second hearing aids.

Monaural intrusive speech intelligibility predictor unit, a hearing aid and a binaural hearing aid system

Signal processing methods for predicting the intelligibility of speech, e.g., in the form of an index that correlate highly with the fraction of words that an average listener (amongst a group of listeners with similar hearing profiles) would be able to understand from some speech material are proposed. Specifically, solutions to the problem of predicting the intelligibility of speech signals, which are distorted, e.g., by noise or reverberation, and which might have been passed through some signal processing device, e.g., a hearing aid are described. In summary, the disclosure present solutions to the following problems:

Monaural speech intelligibility predictor unit, a hearing aid and a binaural hearing system

An intrusive binaural speech intelligibility predictor system receives a target signal comprising speech in left and right essentially noise-free and noisy and/or processed versions at left and right ears of a listener. The system comprises a) first, second, third and fourth input units for providing time-frequency representations of said left and right noise-free and noisy/processed versions of the target signal, respectively; b) first and second Equalization-Cancellation stages adapted to receive and relatively time shift and amplitude adjust the left and right noise-free and noisy/processed versions, respectively, and to provide resulting noise-free and noisy/processed signals, respectively; and c) a monaural speech intelligibility predictor unit for providing final binaural speech intelligibility predictor value SI-Measure based on said resulting noise-free and noisy/processed signals. The Equalization-Cancellation stages are adapted to optimize the SI-Measure to indicate a maximum intelligibility of said noisy/processed versions of the target signal by said listener. The invention may e.g. be used in development systems for hearing aids.

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Smørum, Denmark

Asger Heidemann Andersen