Device for reducing noise during the reproduction of an audio signal using a headphone or hearing aid, and corresponding method

Abstract

The invention relates to a device for reducing noise during the reproduction of an audio signal using a headphone (10) or hearing aid. At least one sensor (20, 22, 23) is provided for detecting a sensor signal based on ambient sound and / or structure-borne sound. The sensor signal or sensor signals are first supplied to a pre-processing unit (32) in order to be pre-processed, said pre-processing unit carrying out a filtering and / or summation process for an active suppression of interference noise, an active suppression of the occlusion effect, and / or an ambient mode. A subsequent filter bank is use to separate the sensor signal or the output signal of the pre-processing unit into frequency bands by means of multiple filters (30). One or more calculation units (31) are provided for calculating weighting factors for the individual frequency bands, said calculation units calculating the weighting factors on the basis of a measurement of the sensor signal in the respective frequency band and a measurement of the noise signal of the sensor or the output signal of the pre-processing unit (32) in silence in said frequency band. The individual frequency bands are multiplied by the corresponding calculated weighting factors using multipliers, and the weighted output signals of the filter bank are summed in order to form a total output signal by means of an adder. A compensation signal based on the total output signal is output by means of an output unit (21).

Description

[0001] Description

[0002] Device for reducing noise during the reproduction of an audio signal with headphones or a hearing aid and corresponding method

[0003] The present invention relates to a device for reducing noise during the reproduction of an audio signal with a near-head audio output device, in particular a headset or hearing aid. The present invention further relates to a corresponding method.

[0004] The range of functions of modern headphones often extends far beyond listening to music or making phone calls. Active noise cancellation (ANC), which reduces the perceptibility of ambient noise by playing an acoustic compensation signal through a built-in speaker, is now standard equipment on such headphones. The same applies to a transparency mode provided on headphones and hearing aids, in which ambient noise is filtered and played through the built-in speaker in such a way that there is hardly any difference to the auditory perception with open ears, i.e. without wearing the headphones. Some headphones, and in particular hearing aids, also have an ambient mode in which ambient sound is processed and / or amplified, for example to improve speech intelligibility or compensate for hearing loss.These applications are not limited to headphones and hearing aids, but can be implemented in all types of head-mounted audio output devices, such as smart glasses, VR / AR headsets, collar speakers, or bone conduction headphones. To support active noise cancellation, a transparency, or ambient mode, headphones are equipped with at least one external microphone, one internal microphone, and optionally an acceleration sensor, hereinafter referred to collectively as sensors, in addition to the speaker. The processing of the microphone signals and acceleration data recorded by the external microphone, internal microphone, and possibly the acceleration sensor, hereinafter referred to collectively as sensor data, is typically performed on a digital signal processor (DSP), as this is the only way to implement sufficiently powerful algorithms.

[0005] When these sensors convert acoustic sound into analog electrical signals, noise is imprinted on the sensor's useful signal. Furthermore, the analog-to-digital conversion of the analog electrical signals into digital signals introduces quantization noise, the performance of which depends on the bit accuracy of the converter. Due to the processing and filtering of the noisy sensor data on a DSP, the noise can also be amplified, making it clearly audible after playback through the loudspeaker. This can be unpleasant for users, especially in quiet environments.

[0006] The state of the art lists a whole range of methods for improving or suppressing interference in speech and useful signals. The most widespread are analysis-synthesis systems, which analyze a section of the input signal in the frequency domain after a time-to-frequency domain transformation, weight individual frequencies, and then synthesize a time-domain signal using an inverse transformation. These systems are particularly advantageous due to their computational efficiency, since convolution in the frequency domain and the time-to-frequency domain transformation can be implemented particularly cost-effectively using a fast Fourier transform. However, these systems exhibit a high delay due to frame-by-frame processing. To ensure high-performance ANC even for non-deterministic signals, the delay in the signal path of the ANC filter must be as low as possible.In a transparency mode, the interference of passive sound and delayed active sound can lead to comb filter effects and the double perception of plosives. Therefore, an analysis-synthesis system in the signal path is unsuitable for such applications.

[0007] EP 1 538 749 A2 presents an alternative system, the so-called filter bank equalizer, which uses a time-domain filter with a finite impulse response (FIR) to suppress interference from an input signal. The time-domain filter is derived from the product of the impulse response of a prototype low-pass filter with an effective window function. The effective window function, in turn, is derived from the Fourier transform of weighting factors for individual frequency bands. By using a time-domain filter, the delay of the filter bank equalizer is significantly lower than that of an analysis-synthesis system. However, a time / frequency domain transformation is still necessary for the calculation of the filter. Thus, while there is no delay in the filtering itself, there is still a delay in the filter adaptation, which can make the approach ineffective, particularly for plosives.A linear-phase prototype low-pass filter imposes a further delay depending on the filter length. Furthermore, this approach only allows for the implementation of FIR filters, which are often not supported by specialized processors with low delay. Furthermore, a filter bank with a nonlinear frequency resolution is only possible with this method using many all-pass filters, which increases the computational complexity.

[0008] It is an object of the invention to provide a device and a corresponding method in which the audibility of the noise during the reproduction of an audio signal with a near-head audio output device, in particular a headphone or hearing aid, is reduced without noticeably changing the useful signal.

[0009] This object is achieved by a device having the features of claim 1 and a corresponding method according to claim 12. Preferred embodiments of the invention are the subject of the dependent claims.

[0010] A device according to the invention for reducing noise during the reproduction of an audio signal with a near-head audio output device, in particular headphones or a hearing aid, comprises at least one sensor for detecting a sensor signal based on ambient sound and / or structure-borne sound; a preprocessing unit for preprocessing the sensor signal or signals, wherein the preprocessing unit performs filtering and / or summation for active noise suppression, active suppression of the occlusion effect, and / or an ambient mode; a filter bank for dividing the sensor signal or the output signal of the preprocessing unit into frequency bands using a plurality of filters;one or more calculation units for calculating weighting factors for the individual frequency bands, wherein the weighting factors are calculated based on a measure of the signal of the sensor or the output signal of the pre-processing unit in the respective frequency band and a measure of the noise signal of the sensor or the output signal of the pre-processing unit in silence in this frequency band;

[0011] Multipliers, by means of which the individual frequency bands are multiplied by the associated calculated weighting factors; an adder, by means of which the weighted output signals of the filter bank are summed to form an overall output signal; and an output unit for outputting a compensation signal based on the overall output signal. According to a preferred embodiment of the invention, the weighting factors are calculated based on the estimated power or standard deviation of the sensor signal or the output signal of the preprocessing unit in the respective frequency band and the estimated power or standard deviation of the noise signal of the sensor or the output signal of the preprocessing unit in silence in this frequency band.

[0012] According to yet another preferred embodiment, the preprocessing unit, the filters of the filter bank, the multipliers and the adder are implemented at a first sampling rate and the calculation units are implemented at a lower second sampling rate.

[0013] Advantageously, the preprocessing unit, the filters of the filter bank, the multipliers and the adder are implemented by a first processor.

[0014] Advantageously, the calculation units are implemented by a separate second processor.

[0015] In this case, the output signals of the respective filters of the filter bank are advantageously transmitted from the first processor to the second processor via an interface between the processors, and the calculated weighting factors for the individual bands of the filter bank are transmitted from the second processor back to the first processor.

[0016] According to one embodiment of the invention, the rate of the output signals of the filters of the filter bank is adapted to the sampling rate on the second processor by sampling rate converters.

[0017] According to a further embodiment of the invention, the input signal of the filter bank is transmitted from the first processor to the second processor via an interface between the processors, wherein the rate of the input signal to be transmitted is converted by a sampling rate converter and a second filter bank is simulated on the second processor for calculating the weighting factors, which implements the filters at a correspondingly lower sampling rate and wherein the calculated weighting factors for the individual bands of the filter bank are transmitted from the second processor back to the first processor.Preferably, in the device according to the invention, the at least one sensor comprises one or more internal microphones arranged in an earpiece for detecting a sound signal in the ear canal of a user and / or external microphones for detecting a sound signal outside the ear canal and / or acceleration sensors for detecting structure-borne sound which is transmitted to the earpiece via the ear canal, and the output unit comprises at least one loudspeaker.

[0018] Furthermore, in one embodiment it can advantageously be provided that the filters of the filter bank are realized by cascaded biquadratic filters as low-pass, high-pass and / or band-pass filters.

[0019] The device according to the invention can be integrated into a head-mounted audio output device, in particular a headphone or hearing aid.

[0020] Accordingly, in a method according to the invention for reducing noise during the reproduction of an audio signal with a near-head audio output device, in particular a headphone or hearing aid, the following steps are carried out:

[0021] Detecting a sensor signal based on ambient sound and / or structure-borne sound with at least one sensor arranged in the headphones or hearing aid;

[0022] - Pre-processing the sensor signal or signals, wherein the pre-processing unit performs filtering and / or summation for active noise suppression, active suppression of the occlusion effect and / or an ambient mode;

[0023] - applying noise suppression to the sensor signal or the output signal of the pre-processing unit, wherein the signal is divided into several frequency bands by means of a filter bank, the individual frequency bands are multiplied by weighting factors for the individual frequency bands, wherein the weighting factors are calculated based on a measure of the signal of the sensor or the output signal of the pre-processing unit in the respective frequency band and a measure of the noise signal of the sensor or the output signal of the pre-processing unit in silence in this frequency band, and the weighted output signals of the filter bank are then summed to form an overall output signal; and

[0024] - Output of a compensation signal based on the total output signal.

[0025] The invention also relates to a computer program with instructions that cause a computer to carry out the steps of the method according to the invention.

[0026] Further features of the present invention will become apparent from the following description and claims in conjunction with the figures.

[0027] Fig. 1 shows schematically an in-ear headphone in the ear canal of a user with essential electronic components;

[0028] Fig. 2 shows a block diagram for a noise suppression with a filter bank in the time domain with one adaptation per band;

[0029] Fig. 3 shows a block diagram of a filtering with noise suppression according to the invention;

[0030] Fig. 4 shows schematically the magnitude response for a filter bank with bandpass filters;

[0031] Fig. 5 shows a calculation unit for calculating a weighting factor per

[0032] Band;

[0033] Fig. 6 shows a calculation unit for the numerically robust calculation of a weighting factor per band;

[0034] Fig. 7 shows a calculation unit for calculating a weighting factor, wherein the noise power is estimated from the input signal;

[0035] Fig. 8 shows a block diagram of a hybrid multi-channel ANC system with noise cancellation;

[0036] Fig. 9 shows a block diagram of a hybrid multi-channel ANC system with noise cancellation and feedback loop compensation;

[0037] Fig. 10 shows a flowchart of a method according to the invention. To better understand the principles of the present invention, embodiments of the invention are explained in more detail below with reference to the figures. It is understood that the invention is not limited to these embodiments and that the described features can also be combined or modified without departing from the scope of the invention as defined in the claims.

[0038] Fig. 1 shows an example of an in-ear headset 10 for use with the device according to the invention. However, the device can equally be used in other types of near-head audio output devices, such as headphones, hearing aids, smart glasses, VR / AR headsets, collar speakers, or bone conduction headphones. The in-ear headset 10 sits in the ear canal 12, held by an earpiece 11, and acoustically seals it completely or partially. As a result, users can no longer clearly perceive their surroundings. To still enable users to have a clear auditory impression of their surroundings while wearing headphones, the headset is equipped with microphones 22 and at least one processor 24, which record and process the ambient sound and reproduce it via the headset's internal speaker 21.

[0039] Sealing off the ear canal 12 with headphones 10 also means that structure-borne noise, such as footsteps or speech, which is radiated into the ear canal 12 by vibrating ear canal walls, can hardly escape from the ear canal 12. This manifests itself in an amplification of low frequencies of the structure-borne noise compared to an open ear canal, which, in combination with the weakened perception of ambient noise, is referred to as the occlusion effect. To compensate for the occlusion effect (Active Occlusion Cancellation, AOC), additional sensors in the form of the inward-facing microphone 20 and the acceleration sensor 23 on the side of the headphones facing into the ear canal can be used to record information about the structure-borne noise in the ear canal 12.

[0040] In addition to generating acoustic transparency or compensating for the occlusion effect when wearing headphones, the sensors 20, 22, 23 and processors 24 can also be used to actively attenuate loud ambient noise. With active noise cancellation, an acoustic compensation signal based on the sensor data is played via the headphones' internal loudspeaker 21, which destructively interferes with the ambient sound at the eardrum 13 and thus reduces the perceived volume of the ambient sound. Furthermore, the sensors can be used for an ambient mode, in which ambient sound is processed and / or amplified, for example, to improve speech intelligibility or compensate for hearing loss.

[0041] As already mentioned, one problem solved by the method according to the invention is that the sensors not only record a wanted signal x(n) with the discrete time index n, but also induce noise v(n). In the context of this invention, the wanted signal includes not only speech but also ambient noise, some of which is considered undesirable in conventional methods for noise suppression, but here is assigned to the wanted signal and not to the noise. The output signal of a sensor results from the sum of the wanted signal and the sensor noise, x(n) = x(n) + v(n).

[0042] By processing and filtering the sensor signal, the noise can be significantly amplified, which can be perceived as unpleasant when played back through the speaker for an AOC or ANC.

[0043] Fig. 2 shows a structure for noise suppression. The disturbed signal x(n) is first passed through a filter bank with K filters 30 with respective impulse responses b k (n) with k = 1, 2, ..., K into different frequency ranges. Each of the parallel process chains resulting from the filtering is referred to as a (frequency) band. The output signals of the filters 30 are each k ( ) = b k ( ) *x(n).

[0044] For each band k, a time-variant weighting factor g k (ri) is calculated, which is then compared with the band signal ü k (n). At the output of the noise suppressor 63, an estimate x(n) of the desired signal is obtained, based on the weighted sum of the band signals:

[0045] Fig. 3 shows a device according to the invention, wherein a useful signal x(ri), such as ambient or structure-borne sound, is recorded by an external microphone 22 of a headset 10, as shown by way of example in Fig. 1, and is thereby additionally disturbed by a noise v(ri). The microphone signal is then processed on a processor 34 for fast filtering, first by a preprocessing unit 32 and subsequently by a filter bank with filters 30 with the impulse responses b k (n). The individual bands are then weighted by weighting factors g k(n) weighted, with the weighting factors being calculated on one or more additional processors 35. The output signals of the respective filters of the filter bank are transmitted via an interface from the fast filtering processor to the additional processor. The weighting factors for the individual bands of the filter bank are also transmitted via this interface from the additional processor back to the fast filtering processor.

[0046] The preprocessing unit can, for example, filter the microphone signal using a filter with an impulse response w(n), which is designed for a transparency or ambient mode, an ANC, or an AOC. Furthermore, the preprocessing unit can, for example, filter multiple sensor signals with different filters and then sum them to an output signal.

[0047] The output signal is obtained with a filter w(n) as follows:

[0048] To achieve the lowest possible input-to-output latency on the processor for fast filtering 34, a high sampling rate is preferably used. The input-to-output latency should advantageously be less than 1 millisecond. Since the characteristics of the wanted signal generally change only slowly, the weighting factors can be calculated at a lower sampling rate. Advantageously, the weighting factors can be calculated on one or more separate processors 35. To avoid aliasing effects when transferring the band signals to a lower sampling rate for calculating the weighting factors, a sampling rate conversion by sampling rate converter 33 is optionally provided. The weighting factors, however, do not require sampling rate conversion since they are low-frequency signals.Instead of converting the rate of the K output signals of the filters 30, the rate of the input signal of the filter bank can alternatively be converted, and a second filter bank can be simulated on the processor or processors for calculating the weighting factors 35, which the filters 30 implement at a correspondingly lower sampling rate. The factors calculated in this way are then transferred to the processor for fast filtering 34 and applied there, as previously described. Since a filter bank on the processor for fast filtering 34 is still necessary, this does not reduce the complexity of the processors 34, 35, but does reduce the number of sampling rate converters 33 and communication channels between the processors 34, 35.

[0049] Fig. 4 shows an example of the magnitude response 40 of the filter bank, where the filters 30 are implemented as bandpass filters. Each bandpass filter with the impulse response b k(n) should be designed in such a way that it ideally covers the frequencies of an input signal below a lower cut-off frequency f g k and above an upper limit frequency f g , k+1 blocks, as well as frequencies between f g k and f g , k+1 This results in the following objective function for the magnitude response of a bandpass filter depending on the frequency f: 0, if f < f g fc if f g fc < f < f g fc+1 0, otherwise

[0050] Furthermore, the sum of the bandpass filters should be 30 advantageously be optimized for the following objective function This prevents unwanted cancellations or amplifications, especially in the transition areas when the bandpass filters are connected in parallel. The lower cutoff frequency of the first bandpass filter f g lcan be equal to 0 Hz, commonly known as low-pass filter, and the upper cutoff frequency of the last band-pass filter f 0iK+1 can be set equal to the Nyquist frequency, commonly known as a high-pass filter. To perform processing that mimics the human ear, it is advantageous to set the cutoff frequencies f g k linearly distributed on a psychoacoustic frequency scale, e.g., the Bark scale. Furthermore, the filters 30 can advantageously be optimized such that the group delay of the transfer function B(z) is minimized, taking into account a target curve and a maximum deviation for the magnitude response.

[0051] Advantageously, the filters 30 can be implemented as a cascade of biquadratic filters.

[0052] Thus, the filter bank contributes only minimally to signal path delay, allowing for high-performance ANC and a transparency mode without comb filter effects and without the double perception of plosives, and can be calculated efficiently. Advantageously, the magnitude and phase response of B(z) is taken into account for the design of filters for ANC or AOC, for example, in a preprocessing unit 32.

[0053] However, an implementation similar to a quadrature filter bank is also possible. While this results in a filter bank with a linear frequency resolution and possibly an additional delay due to a sampling rate conversion in the signal path, it also reduces computational complexity.

[0054] The weighting factors can be calculated based on a spectral subtraction rule using estimates of the short-term power of the disturbed useful signal oj(n) and the noise <? 2 (n). The subtraction rule can be calculated from the cost function

[0055] C = E{[x(n) — g(ri) ■ x(n)] 2} and results, assuming that the noise and the wanted signal are uncorrelated, in Based on this rule, the weighting factor can become negative, leading to unwanted phase distortions. Therefore, it is usually assumed that 0 < g(n) < 1. A hard limitation of g(n) to this range of values ​​can lead to undesirable temporal artifacts due to discontinuous changes. Depending on the estimated short-term power of the undisturbed wanted signal ^(n), the mathematically optimal weighting factor is defined using the cost function C as 2(zn \)' which ensures that the desired range of values ​​of gn is maintained. Unfortunately, x(n) and thus also 9x(n) are unknown.

[0056] Since the power of sensor noise is usually small compared to the power of a useful signal, it can be assumed that ( n) if a useful signal is present, which results in the calculation rule of block 53 in the calculation unit 31 according to Fig. 5 for a band k. The power of the sensor and quantization noise is usually constant, therefore d^ k (n) = d^ k for each band, e.g., by measuring in silence, listening tests, considering component specifications, estimating in a quiet environment during runtime, or using mathematical methods. The sensor and quantization noise is also commonly known as system noise or noise floor. For a measurement in silence, for example, the digitized signals of the sensors 20, 22, 23 or the output signal of the preprocessing unit 32 can be recorded, with the headphones 10 activated and located in a room acoustically protected from ambient noise. Advantageously, the values ​​8 kbe selected so that a specific wanted signal, with a selected sound pressure level at one of the sensors 20, 22, 23 or a separate reference sensor, results in a specific maximum attenuation. This differs from the goal of typical hearing aid processing, which reduces ambient noise to extract voice signals. The estimated short-term power d~ k (n) of the input signal u fc (n) can be calculated, for example, by a block 50 using an exponential smoother with a smoothing factor 0 « A < 1 using be calculated. For cost and battery efficiency reasons, integrated systems such as headphones often use processors that only have fixed-point arithmetic. In particular, the division operation is numerically poorly conditioned, which is why it is desirable to reduce the dynamic range of the input values ​​of the division operation when calculating the weighting factor. This can be achieved by the calculation unit 31 shown in Fig. 6 by using u instead of the corresponding short-term power. 2(n) the standard deviation, or the square root of the variance of the signal, u(n) is used and then the quotient is squared using block 53. Neglecting the cross term of the binomial formula, this calculation rule of block 53 is equivalent to the previous calculation rule of block 53 from Fig. 5. An estimate of the standard deviation can again be made by a block 51 using an exponential smoother using be calculated.

[0057] As shown in Fig. 7, the short-term power cr 2 k (n) of the noise signal based on the output signals of the filters 30 ü k(n) can be estimated. For this purpose, established algorithms such as the so-called baseline tracer can be used in block 52. These algorithms are based on the assumption that the noise power is quasi-time-invariant and can be estimated during pauses in the useful signal. These methods can be applied to estimate the system noise in a running system when a quiet environment is detected. In contrast to hearing aid applications, the goal here is not to detect ambient noise, but to detect the system noise.

[0058] Furthermore, it is possible to use the weighting factors g k (n) such that the power of the respective weighted bandpass signals does not exceed a specified threshold. This can be used to protect the hearing of users in noisy environments.

[0059] Fig. 8 shows a further embodiment of the device according to the invention, which comprises M external microphones 22, a microphone 20 directed into the ear canal, and a loudspeaker 21. In addition to or instead of the external microphones 22 or the internal microphone 20, one or more acceleration sensors 23 can also be used. The signal from the microphone 20 directed into the ear canal is fed to a filter 62 k(ri), which can be designed, for example, to attenuate ambient or structure-borne sound d(n) in certain frequency ranges. For the design of a feedback filter 62, the secondary path 61 with the impulse response g(n), which characterizes the transfer function between the loudspeaker 21 and the internal microphone 20, must be taken into account in particular. The signals from the external microphones 22 are fed to the preprocessing unit 32, which filters the microphone signals, for example, each with a filter w m(n) with m = 1, 2, ..., M and then summed. The filters can be designed for a transparency or ambient mode, an ANC or AOC. By filtering and subsequently summing multiple microphones, the preprocessing unit can, for example, implicitly implement a filter-and-sum beamformer, which processes the signals of a microphone array, for example, such that the output signal primarily comprises sound from specific directions. The output signal of the preprocessing unit is then fed to the noise suppression 63 according to Fig. 3.The preprocessing unit 32 and the feedback filter 62 are still implemented at a high sampling rate, for example, on a processor for fast filtering, whereas the calculation units for calculating the weighting factors for noise suppression 63 are implemented at a lower sampling rate, for example, on one or more separate processors. The output signal of the feedback filter 62 can be fed via switch 64 either to the sum of the loudspeaker signal (switch position 1) or to the sum of the input signal for noise suppression 63 (switch position 2). Furthermore, the reproduction of a multimedia signal a(n), such as music or speech from a telephone call, is provided, which is equalized by an equalizer 60 with the impulse response q(n).The output signal of the equalizer is passed directly to the loudspeaker 21 together with the output signal of the feedback filter 62 and the noise suppressor 63.

[0060] Fig. 9 shows a further embodiment of the device according to the invention, which, like the embodiment of Fig. 8, has a plurality of external microphones 22 and filters 32 for filtering, a microphone 20 directed into the ear canal and a feedback filter 62, a loudspeaker 21, a multimedia signal a(n), and an equalizer 60. In contrast to the embodiment of Fig. 8, this embodiment contains an estimate of the secondary path 65 with the impulse response g(n), to which the sum of the equalized multimedia signal and the denoised signal is fed. The output signal of the secondary path estimate 65 is added to the signal of the inner microphone 20, so that the closed control loop formed by the feedback filter 62 and the secondary path 61 has only a reduced effect on the signals fed to the secondary path estimate 65.Otherwise, the transmission behavior to the inner microphone 20 as well as to the eardrum 13 would audibly change depending on the feedback filter 62.

[0061] The device according to the invention can in particular be integrated into headphones, whereby such headphones can be designed in various ways. For example, they can be earphones, hearables, or so-called in-ear monitors, which are used, for example, during live performances by musicians or television presenters to check one's own voice, or a combination of headphones and a mouth microphone for capturing speech in the form of a headset. Likewise, the device can also be part of a hearing aid. Furthermore, the device can be integrated into smart glasses, VR / AR headsets, collar speakers, or bone conduction headphones. Finally, parts of the device can also be part of an external device, such as a smartphone.

[0062] Figure 10 schematically shows the basic concept of a method for reducing noise during the reproduction of an audio signal, as can be carried out, for example, using a device from Figure 3. In the following, reference is made to the application of the method to headphones as an example; however, the method is not limited to this and can also be applied to other head-mounted audio output devices, in particular to a hearing aid.

[0063] In the method, in a first step 70, ambient sound and / or structure-borne sound, which may originate, for example, from the voice output of the user wearing the headphones or from footsteps of this user, is detected using at least one sensor arranged in the headphones. The corresponding sensor signals are processed in a subsequent step 71 by a preprocessing unit, which performs filtering and / or summation for active noise suppression, active suppression of the occlusion effect, and / or an ambient mode.

[0064] In the subsequent step 72, the sensor signal or the output signal of the preprocessing unit is then subjected to noise suppression. The method according to the invention utilizes a filter bank that is integrated into the signal path between the sensors and the speaker of the headphones. The filter bank divides the filtered sensor signal into several frequency bands. An algorithm sets weighting factors, which are multiplied by the respective output signals of the filter bank, such that frequency bands in which hardly any useful signal is present are noticeably attenuated. In particular, the weighting factors can be calculated based on a measure of the sensor signal or the output signal of the preprocessing unit (32) in the respective frequency band and a measure of the noise signal of the sensor or the output signal of the preprocessing unit (32) in silence in this frequency band.The weighted output signals of the filter bank are then summed to form an overall output signal.

[0065] In the subsequent step 73, a compensation signal based on the total output signal is then fed to a loudspeaker of the headphones and output by the latter.

[0066] In the case of headphones that include sound transducers for both ears of the user, the described procedure can be carried out separately for each ear or jointly for the sound transducers of both ears.

[0067] List of reference symbols

[0068] In-ear headphones

[0069] Ear insert

[0070] ear canal

[0071] eardrum

[0072] Internal microphone

[0073] Speaker

[0074] External microphone

[0075] Accelerometer

[0076] Signal processor

[0077] filter

[0078] Calculation unit for weighting factor

[0079] Preprocessing unit

[0080] Sample rate converter

[0081] Processor for fast filtering

[0082] Processor for calculating the weighting factors

[0083] Magnitude response of a filter

[0084] Power estimator of the useful signal

[0085] Estimator of the standard deviation of the useful signal

[0086] Power estimator of the noise signal

[0087] Block with calculation rule

[0088] Equalizer

[0089] Secondary path

[0090] filter

[0091] Noise reduction

[0092] Switch for filter output signal

[0093] Estimation of the secondary path

[0094] Process step for collecting the sensor data

[0095] Process step for filtering the sensor data

[0096] Process step for applying noise reduction

[0097] Process step for outputting a compensation signal

Claims

Patent claims 1. Device for reducing noise during the playback of an audio signal with a head-mounted audio output device, in particular a headphone (10) or hearing aid, comprising at least one sensor (20, 22, 23) for detecting a sensor signal based on ambient sound and / or structure-borne sound; a preprocessing unit (32) for preprocessing the sensor signal or sensor signals, wherein the preprocessing unit (32) performs filtering and / or summation for active noise suppression, active suppression of the occlusion effect and / or an ambient mode; a filter bank for dividing the sensor signal or the output signal of the preprocessing unit (32) into frequency bands by means of several filters (30);one or more computation units (31) for calculating weighting factors for the individual frequency bands, wherein the weighting factors are calculated based on a measure of the sensor signal or the preprocessing unit output signal (32) in the respective frequency band and a measure of the sensor noise signal or the preprocessing unit output signal (32) in silence in that frequency band; multipliers by which the individual frequency bands are multiplied by the associated calculated weighting factors; an adder by which the weighted output signals of the filter bank are summed to a total output signal; and an output unit (21) for outputting a compensation signal based on the total output signal.

2. Device according to claim 1, wherein the weighting factors are calculated based on the estimated power or standard deviation of the sensor signal or the output signal of the preprocessing unit (32) in the respective frequency band and the estimated power or standard deviation of the noise signal of the sensor or the output signal of the preprocessing unit (32) in silence in that frequency band.

3. Device according to one of the preceding claims, wherein the preprocessing unit (32), the filters (30) of the filter bank, the multipliers and the adder are implemented at a first sampling rate and the computation units (31) are implemented at a lower second sampling rate.

4. Device according to claim 3, wherein the preprocessing unit (32), the filters (30) of the filter bank, the multipliers and the adder are implemented by a first processor (34).

5. Device according to claim 4, wherein the computing units (31) are implemented by a separate second processor.

6. Device according to claim 5, wherein the output signals of the respective filters (30) of the filter bank are transmitted from the first processor (34) to the second processor (35) via an interface between the processors, and the calculated weighting factors for the individual bands of the filter bank are transmitted from the second processor (35) back to the first processor (34).

7. Device according to claim 6, wherein the rate of the output signals of the filters (30) of the filter bank is adapted to the sampling rate on the second processor (35) by sampling rate converters (33).

8. Device according to claim 5, wherein the input signal of the filter bank is transmitted from the first processor (34) to the second processor (35) via an interface between the processors, wherein the rate of the input signal to be transmitted is converted by a sampling rate converter and a second filter bank is simulated on the second processor (35) for calculating the weighting factors, which implements the filters at a correspondingly lower sampling rate and wherein the calculated weighting factors for the individual bands of the filter bank are transmitted from the second processor (35) back to the first processor (34).

9. Device according to one of the preceding claims, wherein the at least one sensor comprises one or more internal microphones (20) arranged in an earpiece (11) for detecting a sound signal in the ear canal (12) of a user and / or external microphones (22) for detecting a sound signal outside the ear canal and / or acceleration sensors (23) for detecting structure-borne sound transmitted to the earpiece (11) via the ear canal, and the output unit comprises at least one loudspeaker (21).

10. Device according to one of the preceding claims, wherein the filters (30) of the filter bank are implemented by cascaded biquadratic filters as low-pass, high-pass and / or band-pass filters.

11. Device according to one of the preceding claims, wherein it is integrated into a head-near audio output device, in particular a headphone or hearing aid.

12. Method for reducing noise during the playback of an audio signal using a head-mounted audio output device, in particular a headphone (10) or hearing aid, comprising the steps: Capturing (70) a sensor signal based on ambient sound and / or structure-borne sound using at least one sensor arranged in the headphones or hearing aid; - Preprocessing (71) the sensor signal or signals, wherein filtering and / or summation is performed for active noise suppression, active occlusion effect suppression and / or an ambient mode; - Applying (72) noise reduction to the sensor signal or the output signal of the preprocessing unit, wherein the signal is divided into several frequency bands by means of a filter bank, the individual frequency bands are multiplied by weighting factors for the individual frequency bands, the weighting factors being calculated based on a measure of the sensor signal or the preprocessing unit output signal (32) in the respective frequency band and a measure of the noise signal of the sensor or the preprocessing unit output signal (32) at silence in that frequency band, and the weighted output signals of the filter bank are subsequently summed to form an overall output signal; and - Output (73) of a compensation signal based on the total output signal.

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