SUMMARY

The present application relates to hearing devices, e.g. hearing aids, in particular to noise reduction in a hearing device. The present application relates to the use of machine learning or artificial intelligence methods, e.g. utilizing neural networks and e.g. supervised learning, in the task of providing improvements in reduction of noise in a noisy sound signal picked up by a hearing device, e.g. a hearing aid.

A Hearing Device:

In an aspect of the present application, a hearing device, e.g. 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 is provided. The hearing device comprisesan 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; anda signal processor comprisinga (first) SNR estimator for providing a (first) target signal-to-noise ratio estimate for said at least one electric input signal in said time frequency representation;an SNR-to-gain converter for converting said (first) target signal-to-noise ratio estimate (or a second target signal-to-noise ratio estimate derived therefrom) to respective gain values in said time frequency representation.

The hearing device is configured to provide that said signal processor comprises a neural network, wherein the weights of the neural network have been trained with a plurality of training signals.

Thereby a hearing device, e.g. a hearing aid, with improved noise reduction may be provided.

The hearing device comprises at least one SNR estimator.

The SNR estimator and/or the SNR-to-gain converter may comprise a neural network.

The hearing device may comprise at least two SNR estimators. The SNR estimator may comprise first and second SNR estimators. The first and second signal-to-noise ratio (SNR) estimators, may provide respective first and second signal-to-noise ratio (SNR) estimates. The target signal-to-noise ratio may be based on the first and second signal-to-noise ratio estimates. The first and second signal-to-noise ratio (SNR) estimators may be sequentially coupled (see e.g.FIG. 13A) or coupled in parallel with respect to the SNR-to-gain converter (or both, see e.g.FIG. 14).

In an embodiment, the hearing device comprises two or more SNR estimators.

The first and second SNR estimators may be sequentially coupled, so that the output of the first SNR estimator is used by the second SNR estimator to provide an improved SNR estimate. The target signal-to-noise ratio estimate may be equal to (or configured to influence) the improved signal SNR estimate. The output of said second SNR estimator may be used as input to the SNR-to-gain converter.

The output of said second SNR estimator may be used as input to said SNR-to-gain converter.

The outputs of the first and second SNR estimators may be used in parallel as inputs to the SNR-to-gain converter. The SNR estimates may be derived in different ways. In an embodiment, the second SNR estimate is an adaptively smoothed version of the first SNR estimate. (see e.g. US20170345439A1). The first SNR may e.g. be based on spatial properties of the input signal, or it may be based on other features such as modulation or tonality. In an embodiment, the SNR estimate is based on spatial features obtained from at least two microphone signals. In an embodiment, the first SNR estimate is estimated from modulation in the input signal (distance to noise floor). The first and second SNR may e.g. be based on different features. More than two SNR estimates can be envisioned.

The first SNR estimator (cf. e.g. SNR-EST′ in the drawings) may be configured to provide the first (target) signal-to-noise ratio estimate independently in each frequency channel (i.e. e.g. NOT being implemented by a neural network).

The signal processor may comprise a second SNR estimator (an ‘SNR improver’) for converting the first (target) signal-to-noise ratio estimate to a second (target) signal-to-noise ratio estimate. The second SNR estimator (‘SNR improver’) (cf. e.g. SNR2SNR′ in the drawings) may comprise the neural network, wherein the weights of the neural network have been trained with a plurality of training signals.

SNR-to-gain conversion has been a weak spot in hearing aids, partly because theoretically based (‘mathematically optimal’) solutions are typically not well received with respect to loudness perception (it does not sound pleasant). The present disclosure proposes to introduce learned determination of gain based on SNR, e.g. using machine learning techniques, e.g. a neural network, where gain of a given frequency band is influenced by SNR values of other frequency bands than the given frequency band. In a hearing device, e.g. a hearing aid, the computational capacity is naturally limited, and hence calculations must be carefully managed. Hence, the introduction of large neural networks (e.g. deep neural networks) with large numbers of nodes and many layers is not realistic due to size/battery capacity limitations alone. However, the computational load of SNR-to-gain conversion is relatively small (compared to other tasks of an audio processing hearing device), so the use of a neural network for this task is realistic as well as desirable.

The SNR-to-gain converter (cf. e.g. SNR2G in the drawings) may comprise the neural network, wherein the weights of the neural network have been trained with a plurality of training signals (cf. e.g.FIG. 17). The SNR estimator providing inputs to the SNR-to-gain converter may be implemented by conventional methods, e.g. NOT be implemented using an artificial neural network or other algorithms based on supervised or unsupervised learning.

The neural network implementing the SNR-to-gain converter may e.g. be a recurrent neural network. The input vector to the neural network may comprise a single frame of SNR-values at a given point in time (e.g. for K frequency bands, K being e.g. smaller than or equal to 128, e.g. smaller than or equal to 64, e.g. smaller than or equal to 24). The output vector may e.g. be a single frame of gain-values (e.g. for K frequency bands). The number of hidden layers may e.g. be smaller than or equal to 10, such as smaller than or equal to 5, smaller than or equal to 2.

The input to the neural network implementing the SNR-to-gain converter may be based on a simple (‘a posteriori’) SNR or other (e.g. easily determined) estimate of a target signal quality. In the present context ‘an a posteriori signal to noise ratio’, SNRpost, is taken to mean a ratio between the observed (available) noisy signal (target signal S plus noise N, Y(t)=S(t)+N(t)), e.g. a picked up by one or more microphones, such as the power of the noisy signal, and the noise N(t), such as an estimate ({circumflex over (N)}(t)) of the noise, such as the power of the noise signal, at a given point in time t, i.e. SNRpost(t)=Y(t)/{circumflex over (N)}(t), or SNRpost(t)=Y(t)2/{circumflex over (N)}(t)2. The ‘a posteriori signal to noise ratio’, SNRpost, may e.g. be defined in the time-frequency domain as a value for each frequency band (index k) and time frame (index m), i.e. SNRpost=SNRpost(k,m, i.e. e.g. SNRpost(k,m)=|Y(k,m)|2/|{circumflex over (N)}(k,m)|2.

In an more general aspect, the SNR-to-gain converter may implement a non-linear function G(k,m), k=1, . . . , K, where G is gain, and wherein gain G(k,m) in the kthfrequency-channel depends on said (e.g. first or second) target signal-to-noise ratio estimates of one or more further, such as all K, frequency-channels at time index m, and optionally on previous values of said estimates, and wherein said non-linear function is implemented by said neural network. The G(k,m) in the kthfrequency-channel may thus depend on previous values G(k,m−1), G(k, m−2), . . . , G(k, m−Np), where Np is number of previous values, and correspondingly also of historic values of one or more of the neighboring frequency channels, k+1, k−1, e.g. all frequency channels k=1, . . . , K. The nonlinear function may e.g. be implemented as a neural network, or using any other method of the field of machine learning or artificial intelligence.

The neural network may be optimized towards only partly attenuating the noise component of the noisy input signal(s). The signal neural network may be optimized in a training procedure wherein the target signal used in the training may contain noise, which has been attenuated by e.g. 10 dB or 15 dB or 20 dB. Hereby, as the gain variations become smaller, a smaller neural network may be utilized. The is advantageous in a limited power capacity device as a portable hearing device, e.g. a hearing aid, where power consumption is a primary design parameter.

The SNR estimator and/or the SNR-to-gain estimator may be configured to receive additional inputs from oner or more sensors or detectors. The one or more sensor or detectors may provide one or more ofa (single or multichannel) voice activity flag,a (single or multichannel) own voice activity flag,a different SNR estimate,an onset flagestimated Direction of Arrival (DoA) information,a camera based input capturing lip-reading or throat movement information.

A different SNR estimate may be based on signal modulation (e.g. from a single microphone), or spatial properties utilizing at least two microphone signals, or binaural SNR estimates.

The onset flag may e.g. be provided by an onset or transient detector derived directly from a time domain input signal. The purpose of the time domain transient detector is to circumvent the time delay in the analysis filter bank, thus getting a small look into the future as seen from the perspective of processing taking place after the analysis filter bank

The level of noise is an important driver for applying noise reduction. The SNR-to-gain estimator may be configured to provide a maximum amount of noise reduction. The hearing device (e.g. the SNR-to-gain estimator) may be configured to provide that the maximum amount of noise reduction is dependent on the type and level of noise.

The hearing device may be constituted by or comprise a hearing aid, a headset, an earphone, an ear protection device or a combination thereof.

The hearing device may be adapted to provide a frequency dependent gain and/or a level dependent compression and/or a transposition (with or without frequency compression) of one or more frequency ranges to one or more other frequency ranges, e.g. to compensate for a hearing impairment of a user. In an embodiment, the hearing device comprises a signal processor for enhancing the input signals and providing a processed output signal.

In an embodiment, the hearing device comprises an output unit for providing a stimulus perceived by the user as an acoustic signal based on a processed electric signal. In an embodiment, the output unit comprises a number of electrodes of a cochlear implant (for a CI type hearing device) or a vibrator of a bone conducting hearing device. In an embodiment, the output unit comprises an output transducer. In an embodiment, the output transducer comprises a receiver (loudspeaker) for providing the stimulus as an acoustic signal to the user (e.g. in an acoustic (air conduction based) hearing device). In an embodiment, the output transducer comprises a vibrator for providing the stimulus as mechanical vibration of a skull bone to the user (e.g. in a bone-attached or bone-anchored hearing device).

The hearing device may comprise an input unit for providing an electric input signal representing sound. In an embodiment, the input unit comprises an input transducer, e.g. a microphone, for converting an input sound to an electric input signal. In an embodiment, the input unit comprises a wireless receiver for receiving a wireless signal comprising or representing sound and for providing an electric input signal representing said sound. The wireless receiver may e.g. be configured to receive an electromagnetic signal in the radio frequency range (3 kHz to 300 GHz). The wireless receiver may e.g. be configured to receive an electromagnetic signal in a frequency range of light (e.g. infrared light 300 GHz to 430 THz, or visible light, e.g. 430 THz to 770 THz).

In an embodiment, the hearing device comprises a directional microphone system adapted to spatially filter sounds from the environment, and thereby enhance a target acoustic source among a multitude of acoustic sources in the local environment of the user wearing the hearing device. In an embodiment, the directional system is adapted to detect (such as adaptively detect) from which direction a particular part of the microphone signal originates. This can be achieved in various different ways as e.g. described in the prior art. In hearing devices, a microphone array beamformer is often used for spatially attenuating background noise sources. Many beamformer variants can be found in literature. The minimum variance distortionless response (MVDR) beamformer is widely used in microphone array signal processing. Ideally the MVDR beamformer keeps the signals from the target direction (also referred to as the look direction) unchanged, while attenuating sound signals from other directions maximally. The generalized sidelobe canceller (GSC) structure is an equivalent representation of the MVDR beamformer offering computational and numerical advantages over a direct implementation in its original form.

The hearing device may comprise antenna and transceiver circuitry (e.g. a wireless receiver) for wirelessly receiving a direct electric input signal from another device, e.g. from an entertainment device (e.g. a TV-set), a communication device, a wireless microphone, or another hearing device. In an embodiment, the direct electric input signal represents or comprises an audio signal and/or a control signal and/or an information signal. In an embodiment, the hearing device comprises demodulation circuitry for demodulating the received direct electric input to provide the direct electric input signal representing an audio signal and/or a control signal e.g. for setting an operational parameter (e.g. volume) and/or a processing parameter of the hearing device. In general, a wireless link established by antenna and transceiver circuitry of the hearing device can be of any type. In an embodiment, the wireless link is established between two devices, e.g. between an entertainment device (e.g. a TV) and the hearing device, or between two hearing devices, e.g. via a third, intermediate device (e.g. a processing device, such as a remote control device, a smartphone, etc.). In an embodiment, the wireless link is used under power constraints, e.g. in that the hearing device is or comprises a portable (typically battery driven) device. In an embodiment, the wireless link is a link based on near-field communication, e.g. an inductive link based on an inductive coupling between antenna coils of transmitter and receiver parts. In another embodiment, the wireless link is based on far-field, electromagnetic radiation. In an embodiment, the communication via the wireless link is arranged according to a specific modulation scheme, e.g. an analogue modulation scheme, such as FM (frequency modulation) or AM (amplitude modulation) or PM (phase modulation), or a digital modulation scheme, such as ASK (amplitude shift keying), e.g. On-Off keying, FSK (frequency shift keying), PSK (phase shift keying), e.g. MSK (minimum shift keying), or QAM (quadrature amplitude modulation), etc.

In an embodiment, the communication between the hearing device and the other device is in the base band (audio frequency range, e.g. between 0 and 20 kHz). Preferably, communication between the hearing device and the other device is based on some sort of modulation at frequencies above 100 kHz. Preferably, frequencies used to establish a communication link between the hearing device and the other device is below 70 GHz, e.g. located in a range from 50 MHz to 70 GHz, e.g. above 300 MHz, e.g. in an ISM range above 300 MHz, e.g. in the 900 MHz range or in the 2.4 GHz range or in the 5.8 GHz range or in the 60 GHz range (ISM=Industrial, Scientific and Medical, such standardized ranges being e.g. defined by the International Telecommunication Union, ITU). In an embodiment, the wireless link is based on a standardized or proprietary technology. In an embodiment, the wireless link is based on Bluetooth technology (e.g. Bluetooth Low-Energy technology).

In an embodiment, the hearing device has a maximum outer dimension of the order of 0.15 m (e.g. a handheld mobile telephone). In an embodiment, the hearing device has a maximum outer dimension of the order of 0.08 m (e.g. a head set). In an embodiment, the hearing device has a maximum outer dimension of the order of 0.04 m (e.g. a hearing instrument).

In an embodiment, the hearing device is a portable (i.e. configured to be wearable) device, e.g. a device comprising a local energy source, e.g. a battery, e.g. a rechargeable battery. The hearing device is e.g. a low weight, easily wearable, device, e.g. having a total weight less than 100 g (or less than 10 g).

The hearing device may comprise a forward or signal path between an input unit (e.g. an input transducer, such as a microphone or a microphone system and/or direct electric input (e.g. a wireless receiver)) and an output unit, e.g. an output transducer. In an embodiment, the signal processor is located in the forward path. In an embodiment, the signal processor is adapted to provide a frequency dependent gain according to a user's particular needs. In an embodiment, the hearing device comprises an analysis path comprising functional components for analyzing the input signal (e.g. determining a level, a modulation, a type of signal, an acoustic feedback estimate, etc.). In an embodiment, some or all signal processing of the analysis path and/or the signal path is conducted in the frequency domain. In an embodiment, some or all signal processing of the analysis path and/or the signal path is conducted in the time domain.

In an embodiment, an analogue electric signal representing an acoustic signal is converted to a digital audio signal in an analogue-to-digital (AD) conversion process, where the analogue signal is sampled with a predefined sampling frequency or rate fs, fsbeing e.g. in the range from 8 kHz to 48 kHz (adapted to the particular needs of the application) to provide digital samples xn(or x[n]) at discrete points in time tn(or n), each audio sample representing the value of the acoustic signal at tnby a predefined number Nbof bits, Nbbeing e.g. in the range from 1 to 48 bits, e.g. 24 bits. Each audio sample is hence quantized using Nbbits (resulting in 2Nbdifferent possible values of the audio sample). A digital sample x has a length in time of 1/fs, e.g. 50 μs, for ƒs=20 kHz. In an embodiment, a number of audio samples are arranged in a time frame. In an embodiment, a time frame comprises 64 or 128 audio data samples. Other frame lengths may be used depending on the practical application.

The hearing device may comprise an analogue-to-digital (AD) converter to digitize an analogue input (e.g. from an input transducer, such as a microphone) with a predefined sampling rate, e.g. 20 kHz. In an embodiment, the hearing devices comprise a digital-to-analogue (DA) converter to convert a digital signal to an analogue output signal, e.g. for being presented to a user via an output transducer.

In an embodiment, the hearing device, e.g. the input unit, and or the antenna and transceiver circuitry comprise(s) a TF-conversion unit for providing a time-frequency representation of an input signal. In an embodiment, the time-frequency representation comprises an array or map of corresponding complex or real values of the signal in question in a particular time and frequency range. In an embodiment, the TF conversion unit comprises a filter bank for filtering a (time varying) input signal and providing a number of (time varying) output signals each comprising a distinct frequency range of the input signal. In an embodiment, the TF conversion unit comprises a Fourier transformation unit for converting a time variant input signal to a (time variant) signal in the (time-) frequency domain. In an embodiment, the frequency range considered by the hearing device from a minimum frequency fminto a maximum frequency fmaxcomprises a part of the typical human audible frequency range from 20 Hz to 20 kHz, e.g. a part of the range from 20 Hz to 12 kHz. Typically, a sample rate fsis larger than or equal to twice the maximum frequency fmax, fs≥2fmax. In an embodiment, a signal of the forward and/or analysis path of the hearing device is split into a number NI of frequency bands (e.g. of uniform width), where NI is e.g. larger than 5, such as larger than 10, such as larger than 50, such as larger than 100, such as larger than 500, at least some of which are processed individually. In an embodiment, the hearing device is/are adapted to process a signal of the forward and/or analysis path in a number NP of different frequency channels (NP≤NI). The frequency channels may be uniform or non-uniform in width (e.g. increasing in width with frequency), overlapping or non-overlapping.

The hearing device may be configured to operate in different modes, e.g. a normal mode and one or more specific modes, e.g. selectable by a user, or automatically selectable. A mode of operation may be optimized to a specific acoustic situation or environment. A mode of operation may include a low-power mode, where functionality of the hearing device is reduced (e.g. to save power), e.g. to disable wireless communication, and/or to disable specific features of the hearing device.

The hearing device may comprise a number of detectors configured to provide status signals relating to a current physical environment of the hearing device (e.g. the current acoustic environment), and/or to a current state of the user wearing the hearing device, and/or to a current state or mode of operation of the hearing device. Alternatively or additionally, one or more detectors may form part of an external device in communication (e.g. wirelessly) with the hearing device. An external device may e.g. comprise another hearing device, a remote control, and audio delivery device, a telephone (e.g. a smartphone), an external sensor, etc.

In an embodiment, one or more of the number of detectors operate(s) on the full band signal (time domain). In an embodiment, one or more of the number of detectors operate(s) on band split signals ((time-) frequency domain), e.g. in a limited number of frequency bands.

In an embodiment, the number of detectors comprises a level detector for estimating a current level of a signal of the forward path. In an embodiment, the predefined criterion comprises whether the current level of a signal of the forward path is above or below a given (L-) threshold value. In an embodiment, the level detector operates on the full band signal (time domain). In an embodiment, the level detector operates on band split signals ((time-) frequency domain).

In a particular embodiment, the hearing device comprises a voice detector (VD) for estimating whether or not (or with what probability) an input signal comprises a voice signal (at a given point in time). A voice signal is in the present context taken to include a speech signal from a human being. It may also include other forms of utterances generated by the human speech system (e.g. singing). In an embodiment, the voice detector unit is adapted to classify a current acoustic environment of the user as a VOICE or NO-VOICE environment. This has the advantage that time segments of the electric microphone signal comprising human utterances (e.g. speech) in the user's environment can be identified, and thus separated from time segments only (or mainly) comprising other sound sources (e.g. artificially generated noise). In an embodiment, the voice detector is adapted to detect as a VOICE also the user's own voice. Alternatively, the voice detector is adapted to exclude a user's own voice from the detection of a VOICE.

In an embodiment, the hearing device comprises an own voice detector for estimating whether or not (or with what probability) a given input sound (e.g. a voice, e.g. speech) originates from the voice of the user of the system. In an embodiment, a microphone system of the hearing device is adapted to be able to differentiate between a user's own voice and another person's voice and possibly from NON-voice sounds.

In an embodiment, the number of detectors comprises a movement detector, e.g. an acceleration sensor. In an embodiment, the movement detector is configured to detect movement of the user's facial muscles and/or bones, e.g. due to speech or chewing (e.g. jaw movement) and to provide a detector signal indicative thereof.

The hearing device may comprise a classification unit configured to classify the current situation based on input signals from (at least some of) the detectors, and possibly other inputs as well. In the present context ‘a current situation’ is taken to be defined by one or more of

a) the physical environment (e.g. including the current electromagnetic environment, e.g. the occurrence of electromagnetic signals (e.g. comprising audio and/or control signals) intended or not intended for reception by the hearing device, or other properties of the current environment than acoustic);
b) the current acoustic situation (input level, feedback, etc.), and
c) the current mode or state of the user (movement, temperature, cognitive load, etc.);
d) the current mode or state of the hearing device (program selected, time elapsed since last user interaction, etc.) and/or of another device in communication with the hearing device.

In an embodiment, the hearing device further comprises other relevant functionality for the application in question, e.g. compression, feedback control, etc.

In an embodiment, the hearing device comprises a listening device, e.g. a hearing aid, e.g. a hearing instrument, e.g. a hearing instrument adapted for being located at the ear or fully or partially in the ear canal of a user, e.g. a headset, an earphone, an ear protection device or a combination thereof. In an embodiment, the hearing assistance system comprises a speakerphone (comprising a number of input transducers and a number of output transducers, e.g. for use in an audio conference situation), e.g. comprising a beamformer filtering unit, e.g. providing multiple beamforming capabilities.

A Further Hearing Device:

In an aspect of the present disclosure, a hearing device is configured to provide that a maximum amount of noise reduction may depend on the type of noise (see e.g.FIG. 16B, 16C). As the artefacts (e.g. resulting from noise reduction) may be different depending on the noise type, the maximum amount of attenuation may depend on (e.g. be adjusted according to) the type of background noise, such as depending on the amount of modulation. If, for example, the background noise is modulated, a higher amount of attenuation may be tolerated compared to an unmodulated background. The maximum attenuation allowed by the system may be frequency dependent (or, alternatively, uniform over frequencies). The hearing device may be a hearing device as described above, in the detailed description of embodiments or in the claims, or it may be any other hearing device, e.g. a hearing aid, comprising a configurable noise reduction system.

A Still Further Hearing Device:

In an aspect of the present disclosure, a hearing device, e.g. 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 is provided by the present disclosure. The hearing device may comprise: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; anda signal processor comprisingan 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 recurrent neural network, wherein the weights of the neural network have been trained with a plurality of training signals.

The SNR to gain converter may be configured to implement a noise reduction algorithm.

The hearing device may comprise 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.

The hearing device may be configured to provide said time frequency representation of the at least one electric input signal comprises magnitude information as well as phase information.

The hearing device may be configured to provide that the inputs to said SNR-to-gain converter comprises magnitude information as well as phase information.

The hearing device may be configured to provide that the inputs to said SNR-to-gain converter comprises changes in phase information over time. Such change over time of phase information is representative of the location of frequency content in a given frequency band and may be used by the neural network (of the SNR-to-gain converter) to locate where in a given frequency sub-band energy is located. Thereby the neural network may allow to process noise components with a larger resolution than the width of the frequency sub-band would normally allow (using only magnitude information as inputs). Thereby a relatively low latency of the filter bank (based on a relatively large bandwidth of the frequency sub-bands) can be implemented without compromising the noise reduction (still allowing an acceptable frequency resolution in noise reduction).

The hearing device may be configured to provide that the outputs of said SNR-to-gain converter comprises magnitude information as well as phase information.

Use:

In an aspect, use of a hearing device as described above, in the ‘detailed description of embodiments’ and in the claims, is moreover provided. In an embodiment, use is provided in a system comprising audio distribution. In an embodiment, use is provided in a system comprising one or more hearing aids (e.g. hearing instruments), headsets, ear phones, active ear protection systems, etc., e.g. in handsfree telephone systems, teleconferencing systems (e.g. including a speakerphone), public address systems, karaoke systems, classroom amplification systems, etc.

A Method:

In an aspect, a method of operating a hearing device, e.g. 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, is provided. The method comprisesproviding 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; andproviding a (first) target signal-to-noise ratio estimate for said at least one electric input signal in said time frequency representation;converting said (first) target signal-to-noise ratio estimate (or a second target signal-to-noise ratio estimate derived therefrom) to respective gain values in said time frequency representation is furthermore provided by the present application; andproviding said (first) target signal-to-noise ratio estimate, (and/or said second target signal-to-noise ratio estimate) and/or said respective gain values using a neural network, wherein the weights of the neural network have been trained with a plurality of training signals.

It is intended that some or all of the structural features of the device described above, in the ‘detailed description of embodiments’ or in the claims can be combined with embodiments of the method, when appropriately substituted by a corresponding process and vice versa. Embodiments of the method have the same advantages as the corresponding devices.

A Computer Readable Medium:

In an aspect, a tangible computer-readable medium storing a computer program comprising program code means for causing a data processing system to perform at least some (such as a majority or all) of the steps of the method described above, in the ‘detailed description of embodiments’ and in the claims, when said computer program is executed on the data processing system is furthermore provided by the present application.

By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media. In addition to being stored on a tangible medium, the computer program can also be transmitted via a transmission medium such as a wired or wireless link or a network, e.g. the Internet, and loaded into a data processing system for being executed at a location different from that of the tangible medium.

A Computer Program:

A computer program (product) comprising instructions which, when the program is executed by a computer, cause the computer to carry out (steps of) the method described above, in the ‘detailed description of embodiments’ and in the claims is furthermore provided by the present application

A Data Processing System:

In an aspect, a data processing system comprising a processor and program code means for causing the processor to perform at least some (such as a majority or all) of the steps of the method described above, in the ‘detailed description of embodiments’ and in the claims is furthermore provided by the present application.

A Hearing System:

In a further aspect, a hearing system comprising a hearing device as described above, in the ‘detailed description of embodiments’, and in the claims, AND an auxiliary device is moreover provided.

In an embodiment, the hearing system is adapted to establish a communication link between the hearing device and the auxiliary device to provide that information (e.g. control and status signals, possibly audio signals) can be exchanged or forwarded from one to the other.

In an embodiment, the hearing system comprises an auxiliary device, e.g. a remote control, a smartphone, or other portable or wearable electronic device, such as a smartwatch or the like.

In an embodiment, the auxiliary device is or comprises a remote control for controlling functionality and operation of the hearing device(s). In an embodiment, the function of a remote control is implemented in a smartphone, the smartphone possibly running an APP allowing to control the functionality of the audio processing device via the smartphone (the hearing device(s) comprising an appropriate wireless interface to the smartphone, e.g. based on Bluetooth or some other standardized or proprietary scheme).

In an embodiment, the auxiliary device is or comprises an audio gateway device adapted for receiving a multitude of audio signals (e.g. from an entertainment device, e.g. a TV or a music player, a telephone apparatus, e.g. a mobile telephone or a computer, e.g. a PC) and adapted for selecting and/or combining an appropriate one of the received audio signals (or combination of signals) for transmission to the hearing device.

In an embodiment, the auxiliary device is or comprises another hearing device. In an embodiment, the hearing system comprises two hearing devices adapted to implement a binaural hearing system, e.g. a binaural hearing aid system.

A Binaural Hearing System:

A binaural hearing system, e.g. a binaural hearing aid system, comprising first and second hearing devices, e.g. hearing aids, as descried above, in the detailed description of embodiments, or in the claims is furthermore provided by the present disclosure. The first and second hearing devices may be adapted to establish a wireless link between them and to exchange data between them. The data may include the target SNR-estimates (e.g. first and second (dependent or independent) SNR estimates). The SNR-to-gain estimator of the first and second hearing devices may be configured to include the target SNR estimates (e.g. respective first and second SNR estimates) of the respective opposite hearing device in the estimation of respective first and second gain values in a time frequency representation.

An APP:

In a further aspect, a non-transitory application, termed an APP, is furthermore provided by the present disclosure. The APP comprises executable instructions configured to be executed on an auxiliary device to implement a user interface for a hearing device or a hearing system described above in the ‘detailed description of embodiments’, and in the claims. In an embodiment, the APP is configured to run on cellular phone, e.g. a smartphone, or on another portable device allowing communication with said hearing device or said hearing system.

Definitions:

In the present context, a ‘hearing device’ refers to a device, such as a hearing aid, e.g. a hearing instrument, or an active ear-protection device, or other audio processing device, which is adapted to improve, augment and/or protect the hearing capability of a user by receiving acoustic signals from the user's surroundings, generating corresponding audio signals, possibly modifying the audio signals and providing the possibly modified audio signals as audible signals to at least one of the user's ears. A ‘hearing device’ further refers to a device such as an earphone or a headset adapted to receive audio signals electronically, possibly modifying the audio signals and providing the possibly modified audio signals as audible signals to at least one of the user's ears. Such audible signals may e.g. be provided in the form of acoustic signals radiated into the user's outer ears, acoustic signals transferred as mechanical vibrations to the user's inner ears through the bone structure of the user's head and/or through parts of the middle ear as well as electric signals transferred directly or indirectly to the cochlear nerve of the user.

The hearing device may be configured to be worn in any known way, e.g. as a unit arranged behind the ear with a tube leading radiated acoustic signals into the ear canal or with an output transducer, e.g. a loudspeaker, arranged close to or in the ear canal, as a unit entirely or partly arranged in the pinna and/or in the ear canal, as a unit, e.g. a vibrator, attached to a fixture implanted into the skull bone, as an attachable, or entirely or partly implanted, unit, etc. The hearing device may comprise a single unit or several units communicating electronically with each other. The loudspeaker may be arranged in a housing together with other components of the hearing device, or may be an external unit in itself (possibly in combination with a flexible guiding element, e.g. a dome-like element).

More generally, a hearing device comprises an input transducer for receiving an acoustic signal from a user's surroundings and providing a corresponding input audio signal and/or a receiver for electronically (i.e. wired or wirelessly) receiving an input audio signal, a (typically configurable) signal processing circuit (e.g. a signal processor, e.g. comprising a configurable (programmable) processor, e.g. a digital signal processor) for processing the input audio signal and an output unit for providing an audible signal to the user in dependence on the processed audio signal. The signal processor may be adapted to process the input signal in the time domain or in a number of frequency bands. In some hearing devices, an amplifier and/or compressor may constitute the signal processing circuit. The signal processing circuit typically comprises one or more (integrated or separate) memory elements for executing programs and/or for storing parameters used (or potentially used) in the processing and/or for storing information relevant for the function of the hearing device and/or for storing information (e.g. processed information, e.g. provided by the signal processing circuit), e.g. for use in connection with an interface to a user and/or an interface to a programming device. In some hearing devices, the output unit may comprise an output transducer, such as e.g. a loudspeaker for providing an air-borne acoustic signal or a vibrator for providing a structure-borne or liquid-borne acoustic signal. In some hearing devices, the output unit may comprise one or more output electrodes for providing electric signals (e.g. a multi-electrode array for electrically stimulating the cochlear nerve). In an embodiment, the hearing device comprises a speakerphone (comprising a number of input transducers and a number of output transducers, e.g. for use in an audio conference situation).

In some hearing devices, the vibrator may be adapted to provide a structure-borne acoustic signal transcutaneously or percutaneously to the skull bone. In some hearing devices, the vibrator may be implanted in the middle ear and/or in the inner ear. In some hearing devices, the vibrator may be adapted to provide a structure-borne acoustic signal to a middle-ear bone and/or to the cochlea. In some hearing devices, the vibrator may be adapted to provide a liquid-borne acoustic signal to the cochlear liquid, e.g. through the oval window. In some hearing devices, the output electrodes may be implanted in the cochlea or on the inside of the skull bone and may be adapted to provide the electric signals to the hair cells of the cochlea, to one or more hearing nerves, to the auditory brainstem, to the auditory midbrain, to the auditory cortex and/or to other parts of the cerebral cortex.

A hearing device, e.g. a hearing aid, may be adapted to a particular user's needs, e.g. a hearing impairment. A configurable signal processing circuit of the hearing device may be adapted to apply a frequency and level dependent compressive amplification of an input signal. A customized frequency and level dependent gain (amplification or compression) may be determined in a fitting process by a fitting system based on a user's hearing data, e.g. an audiogram, using a fitting rationale (e.g. adapted to speech). The frequency and level dependent gain may e.g. be embodied in processing parameters, e.g. uploaded to the hearing device via an interface to a programming device (fitting system), and used by a processing algorithm executed by the configurable signal processing circuit of the hearing device.

A ‘hearing system’ refers to a system comprising one or two hearing devices, and a ‘binaural hearing system’ refers to a system comprising two hearing devices and being adapted to cooperatively provide audible signals to both of the user's ears. Hearing systems or binaural hearing systems may further comprise one or more ‘auxiliary devices’, which communicate with the hearing device(s) and affect and/or benefit from the function of the hearing device(s). Auxiliary devices may be e.g. remote controls, audio gateway devices, mobile phones (e.g. smartphones), or music players. Hearing devices, hearing systems or binaural hearing systems may e.g. be used for compensating for a hearing-impaired person's loss of hearing capability, augmenting or protecting a normal-hearing person's hearing capability and/or conveying electronic audio signals to a person. Hearing devices or hearing systems may e.g. form part of or interact with public-address systems, active ear protection systems, handsfree telephone systems, car audio systems, entertainment (e.g. karaoke) systems, teleconferencing systems, classroom amplification systems, etc.

Embodiments of the disclosure may e.g. be useful in applications such as audio devices, such as hearing aids, headsets, mobile telephones, etc., typically operating in an acoustic environment comprising noisy signals, where a target signal should be improved to enhance a user's perception of the target signal.

