Active noise reduction with impulse detection and suppression

Abstract

The apparatus includes noise-reducing headphones having one or more microphones and an acoustic transducer, the one or more microphones configured to generate an input signal; and a controller including one or more processing devices, the controller is configured to process the input signal through one or more noise-reducing filters to generate a noise-reducing signal, compare the input signal with an estimate of the ambient noise to determine whether the energy of the input signal is greater than the estimate of the ambient noise, and if the energy of the input signal is greater than the estimate of the ambient noise by a predetermined amount, suppress changes in the noise-reducing signal, and generate an output signal that at least partially includes the noise-reducing signal, the acoustic transducer is configured to generate an acoustic output in accordance with the output signal.

Description

Technical Field

[0001] The present disclosure generally relates to acoustic devices such as headphones that may include an active noise reduction (ANR) function that blocks at least a portion of ambient noise from reaching a user's ear, and more particularly to acoustic devices having an ANR function that detects and suppresses an ANR response to impulse sound.

Summary of the Invention

Means for Solving the Problems

[0002] Two or more of the features described in the present disclosure, including the features described in this summary section, can be combined to form implementations not specifically described herein.

[0003] According to one aspect, the apparatus is a noise reduction headset comprising one or more microphones and an acoustic transducer, the one or more microphones being configured to generate an input signal based on the captured ambient sound, a noise reduction headset, and a controller including one or more processing devices, the controller being configured to process the input signal through one or more noise reduction filters to generate a noise reduction signal configured to reduce the effect of the input signal, compare the input signal with an estimated value of the ambient noise to determine whether the energy of the input signal is greater than the estimated value of the ambient noise, and if the energy of the input signal is greater than the estimated value of the ambient noise by a predetermined amount, suppress a change in the noise reduction signal and generate an output signal at least partially including the noise reduction signal, the acoustic transducer being configured to generate an acoustic output according to the output signal.

[0004] In one example, the output signal is a weighted combination of the noise reduction signal and the pass-through signal.

[0005] In one example, comparing an input signal to an estimated ambient noise level involves comparing the energy of the input signal to an ambient noise signal generated by a first low-pass filter, which is configured such that the ambient noise signal is an estimate of the ambient noise present in the captured ambient sound.

[0006] In one example, the ambient noise signal is delayed in time relative to the input signal.

[0007] In one example, the energy of the input signal is determined by the output of a second low-pass filter, which provides stronger smoothing to the input signal than the first low-pass filter.

[0008] In one example, comparing the energy of the input signals further includes determining whether the difference between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

[0009] In one example, comparing the energy of the input signals further includes determining whether the ratio between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

[0010] For example, suppressing a noise reduction signal includes temporarily stopping the increase in the magnitude of the noise reduction signal.

[0011] In one example, temporarily stopping the increase in the magnitude of the noise reduction signal involves temporarily stopping the adjustment of a variable gain filter in the pass-through processing chain that generates a pass-through signal, and the output signal is a weighted combination of the noise reduction signal and the pass-through signal.

[0012] For example, suppressing a noise reduction signal involves adjusting the rate at which the noise reduction signal is adjusted in response to an input signal.

[0013] In another embodiment, one or more non-temporary machine-readable storage devices having computer-readable instructions encoded thereon for causing one or more processing devices to perform a method, the method comprising: receiving an input signal based on captured ambient sound from one or more microphones; processing the input signal through one or more noise reduction filters to generate a noise reduction signal configured to reduce the influence of the input signal; comparing the input signal with an estimate of ambient noise to determine whether the energy of the input signal is greater than an estimate of ambient noise, wherein if the energy of the input signal is greater than an estimate of ambient noise by a predetermined amount, the change in the noise reduction signal is suppressed; and generating an output signal to an acoustic transducer, the output signal comprising at least a portion of the noise reduction signal, so that the acoustic transducer generates an acoustic output according to the output signal.

[0014] In one example, the output signal is a weighted combination of a noise reduction signal and a pass-through signal.

[0015] In one example, comparing an input signal to an estimated ambient noise level involves comparing the energy of the input signal to an ambient noise signal generated by a first low-pass filter, which is configured such that the ambient noise signal is an estimate of the ambient noise present in the captured ambient sound.

[0016] In one example, the ambient noise signal is delayed in time relative to the input signal.

[0017] In one example, the energy of the input signal is determined by the output of a second low-pass filter, which provides stronger smoothing to the input signal than the first low-pass filter.

[0018] In one example, comparing the energy of the input signals further includes determining whether the difference between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

[0019] In one example, comparing the energy of the input signals further includes determining whether the ratio between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

[0020] For example, suppressing a noise reduction signal includes temporarily stopping the increase in the magnitude of the noise reduction signal.

[0021] One or more non-temporary machine-readable storage devices according to claim 18, wherein temporarily stopping the increase of the noise reduction signal includes temporarily stopping the adjustment of a variable gain filter in a pass-through processing chain that generates a pass-through signal, and the output signal is a weighted combination of the noise reduction signal and the pass-through signal.

[0022] One or more non-temporary machine-readable storage devices according to claim 11, wherein suppressing the noise reduction signal includes adjusting the rate at which the noise reduction signal is adjusted in response to an input signal.

[0023] In another embodiment, a method includes: receiving an input signal representing speech captured by a microphone of active noise reduction (ANR) headphones; processing a portion of the input signal with one or more processing devices to determine the noise level in the input signal; determining that the noise level satisfies a first threshold condition; comparing the input signal with an estimated ambient noise to determine whether the energy of the input signal is greater than the energy of an estimated ambient noise by a predetermined amount; generating an output signal in response to the determination that the noise level satisfies the first threshold condition and the energy of the input signal is not greater than the energy of an estimated ambient noise by a predetermined amount, wherein ANR processing on the input signal is automatically controlled to limit the loudness level of the output signal; generating an output signal in response to the determination that the energy of the input signal is greater than the estimated ambient noise by a predetermined amount, wherein ANR processing on the input signal is not automatically controlled to limit the loudness level of the output signal; and driving an acoustic transducer of ANR headphones using the output signal.

[0024] In one example, the step of generating an output signal, in which ANR processing on an input signal is automatically controlled to limit the loudness level of the output signal, includes generating an output signal, in which ANR processing on an input signal is automatically controlled to limit the loudness level of the output signal to a level lower than or substantially equal to a predefined target loudness level of the output signal.

[0025] For example, a predefined target loudness level is the sound pressure level in the ear of the ANR headphone user.

[0026] Details of one or more implementations are described in the attached drawings and the following description. Other features, purposes, and advantages will become apparent from this description and drawings, as well as from the "Claims."

Brief Description of the Drawings

[0027] [Figure 1] It is a diagram showing an example of in-ear type active noise reduction (ANR) headphones. [Figure 2] It is a block diagram of an exemplary configuration of an ANR device. [Figure 3A] It is a block diagram of an exemplary implementation form of an ANR device in which a variable pass-through path is arranged in parallel with the ANR path in the feed-forward signal transmission path. [Figure 3B] It is a block diagram of an exemplary implementation form of a binaural ANR system in which the variable gain of the pass-through path arranged in parallel with the ANR path for each ear is controlled by a coprocessor based on the estimated values of the noise levels in both ears. [Figure 3C] It is a block diagram of an exemplary implementation form of an ANR device in which a plurality of variable pass-through paths are arranged in parallel with the ANR path in the feed-forward signal transmission path. [Figure 4A] It is a block diagram of an exemplary implementation form of an impulse detector. [Figure 4B] It is a block diagram of an exemplary implementation form of an impulse detector. [Figure 5A] It is a plot of the acoustic signal of a cough and the resulting impulse detection flag. [Figure 5B] It is a plot of the detection signal generated from the acoustic signal of a cough and the ambient noise signal. [Figure 5C] It is a plot of the signal-to-noise ratio between the detection signal generated from the acoustic signal of a cough and the ambient noise signal and the impulse detection threshold. [Figure 6A] It is a plot of the acoustic signal of case closure and the resulting impulse detection flag. [Figure 6B] It is a plot of the detection signal generated from the case closure signal of a cough and the ambient noise signal. [Figure 6C] It is a plot of the signal-to-noise ratio between the detection signal generated from the acoustic signal of case closure and the ambient noise signal and the impulse detection threshold. [Figure 7A] This is a plot of the pink noise acoustic signal and the resulting impulse detection flag. [Figure 7B] This is a plot of the detection signal and the ambient noise signal generated from the pink noise acoustic signal. [Figure 7C] This plot shows the signal-to-noise ratio and impulse detection threshold between the detected signal and the ambient noise signal generated from the pink noise acoustic signal. [Figure 8] This is a flowchart illustrating an exemplary process for suppressing noise reduction signals output from one or more noise reduction filters in response to an impulse acoustic input to a microphone, such as a feedforward microphone. [Modes for carrying out the invention]

[0028] This disclosure relates to the use of active noise reduction (ANR) in acoustic devices, which simultaneously allows the user to perceive ambient noise up to a threshold level and suppresses the ANR response to rapid transients (also referred to herein as impulses).

[0029] The techniques described herein, in some examples, enable the implementation of a variable hear-through or pass-through signal transmission path in parallel with an ANR signal transmission path, where the gain of the pass-through signal path is controllable or adjustable based on threshold conditions or ambient noise. For example, a device implementing this technique may be configured to allow ambient noise up to a threshold level to pass through (possibly using several ANR processes in parallel), but to enable or gradually increase ANR processing when the ambient noise level exceeds the threshold. In some cases, this can improve the overall user experience, for example, by helping the user avoid excessive acoustic separation in low-noise environments while still providing ANR functionality when noise exceeds a threshold.

[0030] In addition, the techniques described herein can suppress ANR responses to rapid transients. Noises such as clapping, the clinking of silverware, the clicking of case lids, coughing, and closing doors can all be characterized as impulses of these types. Any ANR response to an impulse is almost necessarily slower than the impulse that triggered it, meaning that the user hears both the impulse and a subsequent delayed, short noise reduction, which can be noticeable and distracting. To avoid this type of behavior, ANR responses to impulses can be suppressed by comparing the input signal (e.g., from a feedforward microphone) to an estimate of ambient noise to determine whether a rapid increase in signal energy has occurred. If such an increase has occurred, it can be determined that ANR processing can be suppressed (e.g., temporarily frozen) to prevent an undesirable ANR response to the impulse.

[0031] As background, ANR devices, such as active noise reduction (ANR) headphones, are used to provide a potentially immersive listening experience by reducing the effects of ambient noise and sound. However, by blocking the effects of ambient noise, ANR devices can create acoustic isolation from the environment, which may be undesirable under certain conditions. For example, a user waiting at an airport may want to be able to hear flight announcements while using ANR headphones. In another embodiment, a user may want to use ANR headphones to cancel out cabin noise during flight, while still being able to converse with a flight attendant without having to remove the headphones.

[0032] Furthermore, some headphones offer a feature commonly called "talk-through" or "monitor," in which an external microphone is used to detect external sounds that the user wants to hear. For example, if the external microphone detects sound in the speech band or some other frequency band of interest, it can allow the signal of the corresponding frequency band to be sent through the headphones. Some other headphones allow for multi-mode operation, and in "hear-through" mode, the ANR function may be switched off or at least reduced over at least a frequency range, allowing a relatively wide bandwidth of ambient sound to reach the user. However, in some cases, the user may want to be aware of ambient sound up to a threshold, and want ANR processing to start only when the ambient sound exceeds that threshold. In addition, the user may want some control over the amount of ambient sound that passes through the ANR device.

[0033] Active noise reduction (ANR) devices may include configurable digital signal processors (DSPs) that can be used to implement various signal transmission topologies and filter configurations. Examples of such DSPs are described in U.S. Patents 8,073,150 and 8,073,151, which are incorporated herein by reference in their entirety. U.S. Patent 9,082,388, which is also incorporated herein by reference in its entirety, describes an acoustic implementation of an in-ear active noise reduction (ANR) headphone, as shown in Figure 1. The headphone 100 includes a feedforward microphone 102, a feedback microphone 104, an output transducer 106 (sometimes also called an electroacoustic transducer or acoustic transducer), and a noise reduction circuit (not shown) coupled to both microphones and the output transducer to provide the output transducer with a noise reduction signal based on signals detected by both microphones. Additional inputs to the circuit (not shown in Figure 1) provide additional audio signals, such as music or communication signals, to be played back via the output transducer 106 independently of the noise reduction signal. These additional inputs may be wired or wireless (e.g., Bluetooth) connections to an audio source.

[0034] The term "headphones" is used herein interchangeably with the term "headset" and includes various types of personal acoustic devices such as in-ear, over-ear, or over-ear headsets, earphones, and hearing aids. A headset or headphones may include an earbud or earcup for each ear. The earbuds or earcups may be physically connected to each other, for example, by a cord, an overhead bridge or headband, or a retaining structure at the back of the head. In some implementations, the earbuds or earcups of headphones may be connected to each other via a wireless link.

[0035] To enable functions such as voice equalization, feedback noise cancellation, and feedforward noise cancellation, various signal transmission topologies can be implemented in the ANR device. For example, as seen in the illustrative block diagram of the ANR device 200 in Figure 2, the signal transmission topology may include a feedforward signal transmission path 110 that drives the output transducer 106 to generate a noise cancellation signal (e.g., using a feedforward compensator 112) to reduce the effect of noise signals picked up by the feedforward microphone 102. In another embodiment, the signal transmission topology may include a feedback signal transmission path 114 that drives the output transducer 106 to generate a noise cancellation signal (e.g., using a feedback compensator 116) to reduce the effect of noise signals picked up by the feedback microphone 104. The signal transmission topology may also include an audio path 118 that includes circuitry (e.g., an equalizer 120) for processing an input audio signal 108, such as music or a communication signal, for playback via the output transducer 106. In some implementations, the feedforward compensator 112 may include an ANR signal transmission path arranged in parallel with the pass-through path. An example of such a configuration is described in U.S. Patent No. 10,096,313, the entire contents of which are incorporated herein by reference.

[0036] In some implementations, the output of the output transducer 106 can be adjusted according to a desired final volume or loudness in the ear, such that the amount of overall attenuation provided by the ANR device (e.g., obtained by controlling one or both of the ANR signal path and the pass-through signal path) increases and decreases, respectively, as the ambient noise level increases and decreases. For example, when the ambient noise level does not meet a threshold condition (e.g., below the threshold level), the ambient noise may be allowed to pass to the ear with little or no attenuation. On the other hand, when the ambient noise level meets a threshold condition (e.g., above the threshold level), the ambient noise may be progressively attenuated in some cases (i.e., with more attenuation as the environment becomes noisier).

[0037] Figure 3A is a block diagram of an exemplary implementation of the ANR device 300, in which a variable pass-through path is arranged in parallel with the ANR path in the feedforward signal transfer path to provide the variable attenuation described above. Specifically, the device 300 includes an ANR filter 305 (also indicated as KANR) arranged in parallel with a combination of a pass-through filter 310 (also indicated as KAW) and a detector filter 315 (also indicated and referred to as a side-chain filter Kd). The detector filter 315 may be used to monitor the signal captured using the FF microphone 102 and to control the input to the pass-through filter (e.g., using a variable gain amplifier (VGA) or compressor 320). In some implementations, the input to the detector filter 315 may be pre-processed, for example, to make the detector filter 315 more sensitive to certain types of signals. For example, the side-chain filter may be configured to make the detector filter more sensitive to perceptually weighted speech band noise level changes. The output of the detector filter 315 can be used to adjust the VGA320, which applies gain to the input signal provided to the pass-through filter 310.

[0038] In some implementations, the detector filter 315 may include a frequency-weighted filter (e.g., an A-weighted filter and / or a filter representing a head-related transfer function (HRTF)). The detector filter 315 may also include a level generator that converts the output of the frequency-weighted filter into a signal level, which is then compared to a threshold level (e.g., a user-defined or predetermined level). The detector filter 315 may also include a signal generator configured to generate a control signal that controls the gain of the VGA320. In some implementations, the signal generator may be configured to generate a control signal according to target attack and decay rate dynamics. "Attack rate" is defined as the rate at which decay increases. In some implementations, the target attack rate is less than 100 dB per second (in overall insertion gain), such as about 10 dB / second. "Decay rate" or "release rate" is defined as the rate at which decay decreases. In some implementations, the decay rate is more than twice as fast as the attack rate. In some implementations, a combination of a low threshold (e.g., insertion gain less than 80 dBA) and a low attack speed (e.g., less than 100 dB / sec) can be used for a comfortable user experience in various everyday scenarios.

[0039] In some implementations, the detector filter 315 may be configured to control the VGA or compressor 320 according to a threshold condition. The threshold condition can be preset or set according to user input. In some implementations, if the detector filter 315 determines that the ambient noise level is below a certain threshold, the output of the detector filter 315 controls the compressor or VGA 320 so that the gain of the pass-through signal transmission path is substantially equal to 1. This allows the user to hear ambient sounds with substantially little or no attenuation. In some implementations, if the detector filter determines that the ambient noise level is above a certain threshold, the output of the filter 315 may be configured to control the compressor or VGA 320 so that the overall gain of the pass-through signal path is less than 1, and the output of the ANR filter 305 causes noise attenuation in the ear. This allows the user to recognize ambient noise and sounds when the noise is below the threshold, but to use the headset's ANR function when the noise exceeds the threshold to prevent loud noises from, for example, vehicles, sirens, or machinery from becoming uncomfortably loud.

[0040] The example in Figure 3A shows a VGA placed only in the pass-through signal path, but other variations are possible. For example, the VGA may be placed in the ANR path in addition to, or instead of, the VGA320 placed in the pass-through signal path. In some implementations, a VGA placed in a signal path (e.g., the ANR path or the pass-through path) may be controlled to adjust the weights associated with the corresponding path. For example, the VGA gain may be set to substantially equal to 0, making the weight associated with the corresponding path substantially equal to 0. In some implementations, one or more additional parameters associated with the VGA (or generally the corresponding path) may be adjusted to control one or more characteristics of the corresponding path. For example, the response speed of the VGA (also known as the compressor attack time and release time, corresponding to whether the compression is increasing or decreasing, respectively) may be adjusted to provide either a rapid response or a relatively slow response to changing noise levels. In some implementations, this allows instructing how quickly the ANR device adjusts its gain when the noise level meets a threshold condition, and / or how quickly it reduces or restores its gain to a predetermined level (e.g., 1) when the noise level no longer meets the threshold condition. In some implementations, the response speed can be adjusted based on the target attack speed so that the ANR processing responds smoothly to increases in noise level. In some implementations, the target attack speed may be less than 100 dB / second.

[0041] In some implementations, the outputs of the ANR path and the pass-through path are combined (e.g., in a weighted combination) to generate a feedforward signal 325 that drives the acoustic transducer 106 at least partially. In some implementations, the feedforward signal 325 may be combined with a feedback signal 330 and / or one or more other signals 335. Signals 335 may include, for example, a media signal originating from the audio input 108, or signals from one or more other microphones or audio sources.

[0042] In some implementations, the gain control of the VGA or compressor 320 in each of the two separate earbuds or earcups is harmonized to avoid, for example, having substantially unequal noise reduction in the two earbuds / earcups of the headphones. Figure 3B is a block diagram of an exemplary implementation of a bi-ear ANR system 350 in which the variable gain of a pass-through path, arranged in parallel with the ANR path for each ear, is controlled based on estimates of noise levels in both ears. Specifically, the implementation shown in Figure 3B includes a coprocessor 360 which receives input from noise estimator modules 355 located in each of the two earbuds or earcups 352a and 352b (352 as a whole) and harmonizes the gain control of the corresponding VGA or compressor 320 in the two earbuds or earcups 352. In some implementations, the coprocessor 360 is located in one of the earbuds or earcups 352. In some implementations, the coprocessor 360 may be located in a device outside the headphones, such as within the device that is the source of the audio media being played through the headphones. The coprocessor may include one or more processing devices configured to analyze the input received from the noise estimator 355 and generate a gain control signal for the VGA320.

[0043] In some implementations, the noise estimator 355 comprises one or more digital filters configured to generate a signal that gives an estimate of the noise at the location of the corresponding earbud or earcup 352. For example, the noise estimator 355 may include a front-end weighting filter that emphasizes the part of the spectrum that best indicates how loud the sound is perceived to be. In some implementations, the response of the front-end weighting filter approximates an A weight divided by the head-related transfer function (HRTF) (or another function representing the effect of the presence / orientation of the user's head) to relate the noise signal measured at the headphone's ear microphone to the diffuse field. Other front-end weighting filters, such as B or C weighting, are possible, or more sophisticated loudness models may be used. In some implementations, the front-end weighting filter may be used to compensate for hardware effects (e.g., microphone sensitivity). In some implementations, the front-end weighting filter may include multiple cascaded filters, each considering / compensating for a distinct effect (e.g., the effect of the presence / orientation of the head, hardware effects, and / or A weighting). The output of the weighted filter may be an AC signal representing the relative loudness perceived by the corresponding ear. Such an output may then be post-processed (e.g., by rectification and then low-pass filtering) before being provided to the coprocessor 360 as an estimate of the noise level in the corresponding ear.

[0044] In some implementations, the systems depicted in Figures 3A and 3B may be implemented as part of a multiband system with two or more parallel paths, each accompanied by its own VGA320 and pass-through filter KAW310, all arranged in parallel with KANR305. An example of such a device is shown in Figure 3C, which shows a multiband version of the device in Figure 3A. Specifically, Figure 3C is a block diagram of an exemplary implementation of an ANR device 375 in which multiple variable pass-through paths are arranged in parallel with the ANR path in a feedforward signal transfer path. Each path includes a corresponding pass-through filter (one of 310a, ..., and 310n (310 as a whole)), a corresponding detector filter (one of 315a, ..., and 315n (315 as a whole)), and a corresponding VGA (one of 320a, ..., and 320n (320 as a whole)). Each pass-through filter 310 passes a different portion of the desired pass-through spectrum (filtered using one of the corresponding bandpass filters 380a, ..., and 380n) so that the overall desired “recognition” response is achieved when all VGA320s have unit gain. In some implementations, various parameters of different parallel paths may be configured separately. For example, a particular parallel path may be configured to have its own attack and release rates, compression ratio, and / or threshold, suitable for the corresponding frequency band. In some implementations, one or more parameters, e.g., threshold and compression ratio, may be common across multiple parallel paths, but the corresponding attack and release rates may differ. This can allow for frequency-specific fine-tuning of the ANR device’s response. For example, the device may be configured to have a fast response to high-frequency noise spikes but a relatively slow response to low-frequency noise. In some implementations, the parameters of different paths may be user-adjustable.

[0045] In some implementations, the components of the feedforward signal path 110 can be tuned in various ways to generate the feedforward signal 325. Such ways of tuning them, and plots showing some exemplary variations of ANR processing in the feedforward signal path 110 based on different threshold conditions, are shown in U.S. Patent No. 11,087,776, which is incorporated in its entirety herein by reference.

[0046] In certain cases, the ANR path response may be briefly suppressed to avoid responding to detected impulses (i.e., rapid transient signals typically within 1-2 ms, characterized by a sudden increase and corresponding sharp decrease in noise). To suppress the ANR response to impulses, it is first necessary to distinguish between impulses and ambient noise (i.e., noise that should ideally be filtered out, such as the low-frequency hum of aircraft noise or the sound of passing motorcycles). To achieve this, the detector filter 315 may be further configured to compare the energy in each sample (i.e., the sample under test) with the estimated energy of the ambient noise. Ambient noise can be estimated by characterizing the energy in adjacent samples. If the energy of the sample under test is greater than the energy of adjacent samples by a certain amount, it can be concluded that a large energy spike indicating an impulse has occurred. Of course, it is also possible that impulses not greater than the ambient noise may occur, but in these cases, the impulses are likely to be imperceptible beyond the ambient noise and should not interfere with the ANR gain. (Although explained in relation to detector filter 315, it should be understood that impulse detection can be performed at any appropriate location within the topology.)

[0047] The energy in adjacent samples can be estimated in various ways. One example is to store a buffer of samples and average their values. The sample buffer may include samples prior to the sample under test, samples after the sample under test, or both. In any case, it is typically useful, though not necessary, to exclude the sample under test itself from the mean, as this tends to distort the mean with respect to the sample under test being measured. Alternatively, instead of using a sample buffer, an exponential moving average can be used to average the current sample using a weighted average of the previous example.

[0048] Alternatively, instead of manipulating in the time domain, the input signal may be transformed into the frequency domain (e.g., via a DFT or other suitable frequency transformation). Ambient noise estimates may be determined by examining the average power at the resulting frequencies, or the average power in a subset of frequency bins of interest. This average power may be updated (e.g., by an exponential moving average) for each consecutive frame of the frequency bins (i.e., for each new sample), or calculated independently for each frame. Any given bin or set of bins exceeding the calculated ambient noise may be flagged as impulses. However, these methods are relatively memory-intensive and computationally expensive.

[0049] In the alternative example shown in Figure 4A, two low-pass filters can be used in parallel paths. The low-pass filters in the two paths can operate to smooth the input signal at different rates. For example, low-pass filter 402 can apply stronger smoothing to the input signal than low-pass filter 404, resulting in a signal representing an estimate of ambient noise. (Thus, in this example, the output of this low-pass filter 402 is called the ambient noise signal 406.) More specifically, the output of low-pass filter 404 may, in some examples, be optimized as an exponential moving average to provide an approximate mean of the samples within a sliding window. Furthermore, in various examples, the output of low-pass filter 402 may be scaled and / or otherwise processed to optimize it to better represent ambient noise. In these examples, ambient noise signal 406 is not simply the output of low-pass filter 402, but the cumulative output of the processing performed to estimate ambient noise. In contrast, the output of low-pass filter 404 can be subjected to relatively fast smoothing and acts as an envelope detector to characterize the peak values ​​of the input signal. This filter functions to expand the impulse to make it easier to capture peak estimates and compare them with ambient noise estimates. The output of this filter 404 is called the detection signal 408. Similarly, the detection signal 408 may be the result of additional processing to characterize the energy of the sample under test to help detect the impulse. Furthermore, in some examples, the low-pass filter 404 can be omitted, and the input signal can be used directly for comparison with the ambient noise signal 406. For the purposes of this disclosure, in examples where the low-pass filter 404 is omitted, the input signal is the detection signal 408.

[0050] In general, any suitable low-pass filter can be used for low-pass filters 402 and 404. Furthermore, different cutoff frequencies can be selected for each to achieve different smoothing characteristics for low-pass filters 402 and 404. For example, the cutoff frequency of low-pass filter 402 can be set to 5 Hz and the cutoff frequency of low-pass filter 404 can be set to 100 Hz, but other suitable cutoff frequencies can also be used. In various examples, the input signal may be filtered using an FIR Hilbert transform or whitening filter instead, which helps to remove any spectral shape of ambient noise, resulting in more robust impulse detection (however, these examples may require more processing power than is typically available).

[0051] Since the ambient noise signal 406 represents an estimate of ambient noise, the presence of an impulse can be detected by comparing the detection signal 408 with the ambient noise signal 406. The comparison between the detection signal 408 and the ambient noise signal 406 can be achieved by one of several methods. In one example, the difference between the detection signal 408 and the ambient noise signal 406 may be found by a difference module 410, whose output is input to a comparator 412 for comparing the difference between the signals to a threshold. If the difference between the signals is greater than the threshold, the input signal may be flagged as likely to contain an impulse, or at least the start of a new sustained noise. In an alternative example, instead of finding the difference between the detection signal 408 and the ambient noise signal 406, the ratio of the two signals may be found and compared to a threshold to determine whether the ratio of the two signals indicates an impulse. (This method is analogous to comparing the signal-to-noise ratio of two signals to a threshold.) Other suitable methods for comparing the detection signal 408 with the ambient noise signal 406 that give some indication of how much larger the detection signal 408 is than the ambient noise signal 406 are contemplated herein.

[0052] In the example shown in Figure 4B, to better represent ambient noise, the output of the low-pass filter 402 is delayed by a predetermined amount (e.g., 2 ms) using a delay 414, preventing the sample under test from affecting the ambient noise signal 406 it is being compared to. In other words, by applying a delay, the ambient noise signal represents the ambient noise that existed before the current sample, and therefore better represents the ambient noise to which the signal should be compared. Typically, such a delay is useful for capturing everything except very fast energy impulses that could be captured without such a delay.

[0053] Furthermore, as shown in Figures 4A and 4B, the input signal applied to low-pass filters 402 and 404 may be the absolute value (e.g., the rectified version) of the output of the feedforward microphone 102. This is to prevent naturally oscillating voice signals from compromising the average value of ambient noise and to ensure that the detected signal 408 and the ambient noise signal 406 have the same sign when compared. Additionally, it should be understood that additional processing (e.g., high-pass filtering) may be performed on the input signal before it is received by low-pass filters 402 and 404, in order to ensure that impulses are detected more reliably, or for any other appropriate reason.

[0054] In response to the output of comparator 412 indicating the possible presence of an impulse, the ANR response that would have resulted from the feedforward microphone output sample containing the detected impulse can be suppressed. However, if the output of comparator 412 does not indicate the possible presence of an impulse, the ANR output is not suppressed, and instead, as described above, the system parameters are followed to apply the ANR according to a threshold condition or some other metric. If the flagged sample is not an impulse but the beginning of a new sustained noise (e.g., an approaching motorcycle), the initial sample containing the new sustained noise will be higher than the ambient noise and therefore initially flagged as an impulse. However, as the ambient noise continues, the ambient noise signal rapidly increases to the level of the detected signal, meaning that the comparison of the two signals only temporarily exceeds the threshold condition. The time constant of the ANR filter is typically such that the delay is imperceptible to the user.

[0055] To further improve the performance of impulse detection, each sample exceeding a threshold can be zeroed out or otherwise processed so that the detected impulse does not affect the ambient noise signal 406. In other words, during the delay performed by the delay unit 414, the detected energy of the impulse can be removed so that the detected impulse does not affect the background noise measurement for future samples.

[0056] To demonstrate the operation of impulse detection, Figures 5–7 depict various recorded audio signals, the output detection signal 408 and the ambient noise signal 406, as well as the calculated signal-to-noise ratio between the two. Figure 5A shows the input audio signal of a person coughing at fairly regular intervals (approximately 1-second intervals). Figure 5B shows the detection signal 408 and the ambient noise signal 406 delayed by 2ms. As shown, the ambient noise signal 406 uses a larger amount of smoothing so that sharp peaks in the input signal are not captured. Furthermore, as long as peaks in the input signal are captured, they are delayed by 2ms, and as a result, the discrepancy between the captured peaks in the detection signal 408 is compared to the ambient noise that was present before the start of the cough. Consequently, as shown in Figure 5C, the peak at the start of the cough is sufficient to produce a large difference between the detection signal 408 and the ambient noise signal 406, and therefore the detection flag (shown in Figure 5A) is triggered and the ANR response is suppressed. In this example, note that the detection flag is held high for a predetermined time period after the SNR exceeds the 15dB threshold to ensure that the entire duration of the ANR responds to the impulse.

[0057] Similarly, Figures 6A–6C show the output of the feedforward microphone 102 in response to the periodic closure of the case. Figure 6B shows the detection signal 408 and the ambient noise signal 406 resulting from this signal, which, like the cough signal in Figure 5A, gives rise to an initial peak in the detection signal sufficient to generate the SNR in Figure 6C, exceeding a predetermined threshold and setting a flag to suppress the ANR response.

[0058] In contrast, Figure 7A shows the voice signal from a telephone that is shaken back and forth near the feedforward microphone 102, with pink noise beginning to play at approximately 0.75 seconds. As shown, at the initial start of the pink noise voice signal, the spike in the detection signal 408 against the ambient noise signal 406 (Figure 7B) records an SNR in Figure 7C that triggers suppression of the ANR response. However, the subsequent changes in the voice signal resulting from shaking the telephone back and forth do not produce a sufficiently large difference between the detection signal 408 and the ambient noise signal 406 to exceed the SNR threshold. This demonstrates that the initial start of new, sustained ambient noise triggers and briefly delays the ANR response, but the ambient noise signal 406 adapts rapidly, allowing the ANR response to reduce ambient noise as desired.

[0059] ANR suppression can be performed in any number of appropriate ways and depends in part on the implementation of the ANR / passthrough system. For example, an interrupt signal can be generated that temporarily freezes the adjusting VGA320, so that the ANR response is kept constant until the period for adjustment resulting from the impulse has elapsed. Alternatively, the response time of the VGA320 related to the signal path can be adjusted, for example, as illustrated with reference to Figure 3A. The response speed of the VGA320 can be modified so that the ANR adjusts relatively slowly in response to the sample under test, making the changes in the ANR less noticeable or undetectable to the user. For the purposes of this disclosure, it should be understood that suppressing the ANR response means reducing the ANR response in relation to how the ANR response occurs during normal operation (i.e., without intervention from impulse detection) in response to an impulse. Therefore, keeping the ANR response constant when an impulse is detected, or slowing down the response to an impulse, can both be considered "suppressing" the ANR response.

[0060] Depending on the topology of the ANR system, suppressing the ANR response may involve adjusting or keeping constant the VGA at the input or output of the ANR filter. Furthermore, adjustments can be made to the ANR filter itself, such as adjusting its adaptation speed so that it does not adapt to incoming impulses or adapts very slowly. Other appropriate methods for suppressing the ANR response, such as filtering input samples from the ANR filter input, are possible and within the scope of this disclosure.

[0061] Furthermore, in an alternative example, instead of suppressing the entire ANR response, the ANR response can be tuned to mitigate the effects of overloading transducer 106 in response to a large input signal. A large input signal clips the microphone, causing noise transients in the voltage signal applied to the transducer. A large input also tends to result in a large ANR response that overloads transducer 106. Overloading transducer 106 can be mitigated by reducing the ANR filter gain in a specific portion of the frequency range (e.g., very high or very low frequencies). Other means of mitigating transducer overload are also conceivable and depend in part on the topology of the ANR / passthrough system, as in the example of suppressing the ANR output.

[0062] The impulse detection described herein may be further employed to control the operation of a device such as a headset 100. For example, a digital signal processor may be further programmed to monitor an impulse detection flag for a set of impulses corresponding to a preset user input. As an example, a digital signal processor may be programmed to consider two separate impulses separated by about 1 / 2 second as a user command, such as pausing a track or skipping to the next track. This is merely presented as an example of the types of impulses that may be considered user commands. In general, it would be beneficial to select impulses that can be easily generated by a user, for example, by clicking their tongue, and that are unlikely to occur except as intentional commands.

[0063] Figure 8 is a flowchart of an exemplary process 800 for suppressing noise reduction signals output from one or more noise reduction filters in response to an impulse acoustic input to a microphone, such as a feedforward microphone.

[0064] At least a portion of process 800 can be implemented using one or more processing devices, such as DSPs, as described in U.S. Patents 8,073,150 and 8,073,151, which are incorporated herein by reference in their entirety. In some implementations, process 800 can be implemented in a device that includes signal paths substantially similar to those shown in Figures 3 and 4.

[0065] In step 802, an input signal is received from one or more microphones based on the captured ambient sound. The microphones may be feedforward microphones, such as feedforward microphone 102. In step 804, the input signal is processed through one or more noise reduction filters (e.g., ANR filters) to generate a noise reduction signal, which is configured to reduce the impact of the input signal.

[0066] In step 806, the input signal is compared with an estimated ambient noise level to determine whether the energy of the input signal is greater than the estimated ambient noise level. The estimated ambient noise level can be estimated in various ways. For example, a buffer of samples can be stored, and the current sample can be averaged using each averaged value or an exponential moving average, or using a weighted average as in the previous example. Alternatively, the input signal can be converted to the frequency domain, and the power of the bins or a subset of the bins can be averaged to determine the estimated ambient noise level. In yet another example, a low-pass filter, as shown in Figures 4A and 4B, can be used to smooth the input signal and form and estimate the ambient noise level.

[0067] The energy of the input signal (which itself may be output from a low-pass filter as shown in Figures 4A and 4B) can be compared with an estimated ambient energy by, for example, finding the difference or ratio between the energy of the input signal and the estimated ambient energy.

[0068] In step 808, if it is determined that the energy of the input signal is greater than the estimated ambient noise by a predetermined amount, the noise reduction signal is suppressed. The result of the comparison in step 806 can be compared with a threshold to determine whether it indicates an impulse (or at least the start of sustained noise). If the comparison exceeds the threshold, measures can be taken to suppress the noise reduction signal.

[0069] ANR suppression can be performed in any number of appropriate ways and depends in part on the implementation of the ANR / passthrough system. In the example in Figures 3 and 4, an interrupt signal can be generated that temporarily freezes the adjustment of the variable gain amplifier, so that the ANR response remains constant until the period during which the adjustment caused by the impulse has elapsed. Alternatively, the response time of the VGA320 related to the signal path can be adjusted, for example, as described with reference to Figure 3A. The response rate of the VGA320 can be modified so that the ANR adjusts relatively slowly in response to the sample under test, making the changes in ANR less noticeable or undetectable to the user.

[0070] Furthermore, depending on the topology of the ANR system, suppressing the ANR response may also involve adjusting or keeping constant the VGA at the input or output of the ANR filter. Additionally, adjustments can be made to the ANR filter itself, such as adjusting its adaptation speed so that it does not adapt to incoming impulses. Other suitable methods for suppressing the ANR response, such as filtering input samples from the ANR filter input, are conceivable and within the scope of this disclosure.

[0071] In step 810, an output signal is generated for the acoustic transducer, and the output signal includes at least a partial noise reduction signal, so the acoustic transducer generates an acoustic output according to the output signal.

[0072] The functions or parts thereof described herein, and various modifications thereof (hereinafter, “Functions”) may be implemented, at least in part, through computer program products, for example, computer programs tangibly embodied in one or more non-temporary machine-readable media or information-holding media such as storage devices for execution by or control of the operation of one or more data processing devices, for example, programmable processors, computers, multiple computers, and / or programmable logical components.

[0073] Computer programs can be written in any form of programming language, including compiled or interpreted languages, and can be deployed as standalone programs or in any form, including modules, components, subroutines, or other units suitable for use in a computing environment. Computer programs can be deployed to run on one computer or on multiple computers at one location, or they can be distributed across multiple locations and interconnected by a network.

[0074] The operations associated with implementing all or part of the functionality may be carried out by one or more programmable processors that execute one or more computer programs to realize the functionality of the calibration process. All or part of the functionality may be implemented as special-purpose logic circuits, such as FPGAs and / or ASICs (Application-Specific Integrated Circuits).

[0075] Examples of processors suitable for executing computer programs include both general-purpose microprocessors and special-purpose microprocessors, as well as any one or more processors in any type of digital computer. Generally, a processor receives instructions and data from read-only memory, random-access memory, or both. The components of a computer include a processor for executing instructions and one or more memory devices for storing instructions and data.

[0076] Elements of different implementations described herein may be combined to form other embodiments not specifically described above. Elements may be removed from the structures described herein without adversely affecting the operation of the structures described herein. Furthermore, various distinct elements may be combined into one or more individual elements to achieve the functions described herein. [Explanation of Symbols]

[0077] 100 headphones 102 Feedforward Microphone 104 Feedback Microphone 106 Output Transducer 108 Input audio signals 110 Feedforward signal path 112 Feedforward Compensator 114 Feedback signal transmission path 116 Feedback Compensator 118 Voice Path 120 Equalizer 200 ANR devices 300 ANR devices 305 ANR filter 310 Pass-through filter 315 Detector filter 320 VGA 325 Feedforward signal 330 Feedback signal 335 Signal 350 Binaural ANR System 352 Earcups 355 Noise Estimator 360 Coprocessor 375 ANR devices 380 Bandpass Filter 402 Low-pass filter 404 filter 406 Ambient Noise Signal 408 Detection signal 410 Differential Modules 412 Comparator 414 delay 416 absolute value

Claims

1. It is a device, A noise-canceling headphone comprising one or more microphones and acoustic transducers, wherein the one or more microphones are configured to generate an input signal based on captured ambient sound, A controller comprising one or more processing devices, wherein the controller To generate a noise reduction signal configured to reduce the influence of the input signal, the input signal is processed through one or more noise reduction filters, To determine whether the energy of the input signal is greater than the estimated ambient noise, the input signal is compared with the estimated ambient noise, and if the energy of the input signal is greater than the estimated ambient noise by a predetermined amount, the change in the noise reduction signal is suppressed, and comparing the input signal with the estimated ambient noise includes comparing the energy of the input signal with an ambient noise signal generated by a first low-pass filter, the first low-pass filter is configured such that the ambient noise signal is an estimated value of the ambient noise present in the captured ambient sound, and the ambient noise signal is delayed in time with respect to the input signal. An apparatus comprising an output signal that includes at least partially the noise reduction signal, wherein the acoustic transducer is configured to generate an output signal that generates an acoustic output according to the output signal.

2. The apparatus according to claim 1, wherein the output signal is a weighted combination of the noise reduction signal and the pass-through signal.

3. The apparatus according to claim 1, wherein the energy of the input signal is determined by the output of a second low-pass filter, and the second low-pass filter provides stronger smoothing to the input signal than the first low-pass filter.

4. The apparatus according to claim 3, further comprising comparing the energy of the input signals to determine whether the difference between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

5. The apparatus according to claim 3, further comprising comparing the energy of the input signal to determine whether the ratio between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

6. The apparatus according to claim 1, wherein suppressing the noise reduction signal includes temporarily stopping the increase in the magnitude of the noise reduction signal.

7. The apparatus according to claim 6, wherein temporarily stopping the increase in the magnitude of the noise reduction signal includes temporarily stopping the adjustment of a variable gain filter in a pass-through processing chain that generates a pass-through signal, the output signal being a weighted combination of the noise reduction signal and the pass-through signal.

8. The apparatus according to claim 1, wherein suppressing the noise reduction signal includes adjusting the speed at which the noise reduction signal is adjusted in response to the input signal.

9. One or more non-temporary machine-readable storage devices having encoded computer-readable instructions for causing one or more processing devices to perform a method, wherein the method is The steps include receiving input signals based on captured ambient sound from one or more microphones, The steps include: processing the input signal through one or more noise reduction filters in order to generate a noise reduction signal configured to reduce the influence of the input signal; A step to determine whether the energy of the input signal is greater than the estimated ambient noise is to compare the input signal with the estimated ambient noise, wherein if the energy of the input signal is greater than the estimated ambient noise by a predetermined amount, the change in the noise reduction signal is suppressed, and comparing the input signal with the estimated ambient noise includes comparing the energy of the input signal with an ambient noise signal generated by a first low-pass filter, wherein the first low-pass filter is configured such that the ambient noise signal is an estimated value of the ambient noise present in the captured ambient sound, and the ambient noise signal is delayed in time with respect to the input signal. One or more non-temporary machine-readable storage devices, comprising the step of generating an output signal, the output signal comprising at least partially the noise reduction signal, such that the acoustic transducer generates an acoustic output according to the output signal.

10. The output signal is a weighted combination of the noise reduction signal and the pass-through signal, one or more non-temporary machine-readable storage devices according to claim 9.

11. The energy of the input signal is determined by the output of a second low-pass filter, the second low-pass filter provides a stronger smoothing to the input signal than the first low-pass filter, one or more non-temporary machine-readable storage devices according to claim 9.

12. One or more non-temporary machine-readable storage devices according to claim 11, further comprising comparing the energy of the input signals to determine whether the difference between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

13. One or more non-temporary machine-readable storage devices according to claim 11, further comprising comparing the energy of the input signals to determine whether the ratio between the output of the second low-pass filter and the ambient noise signal satisfies a threshold condition.

14. One or more non-temporary machine-readable storage devices according to claim 11, wherein suppressing the noise reduction signal includes temporarily stopping the increase in the magnitude of the noise reduction signal.

15. One or more non-temporary machine-readable storage devices according to claim 14, wherein temporarily stopping the increase of the noise reduction signal includes temporarily stopping the adjustment of a variable gain filter in a pass-through processing chain that generates a pass-through signal, the output signal being a weighted combination of the noise reduction signal and the pass-through signal.

16. The one or more non-temporary machine-readable storage devices according to claim 9, wherein suppressing the noise reduction signal includes adjusting the speed at which the noise reduction signal is adjusted in response to the input signal.

17. It is a method, Receiving an input signal representing audio captured by the microphone of active noise reduction (ANR) headphones, To determine the noise level in the input signal, a portion of the input signal is processed by one or more processing devices, Determining that the noise level satisfies the first threshold condition, In order to determine whether the energy of the input signal is greater by a predetermined amount than the energy of the estimated ambient noise, the input signal is compared with the estimated ambient noise, In response to the determination that the noise level satisfies the first threshold condition and that the energy of the input signal is not greater than the estimated energy of the ambient noise by a predetermined amount, an output signal is generated, wherein the ANR processing on the input signal is automatically controlled to limit the loudness level of the output signal. In response to determining that the energy of the input signal is greater by a predetermined amount than the estimated value of the ambient noise, an output signal is generated in which the ANR processing on the input signal is not automatically controlled in order to limit the loudness level of the output signal. A method comprising driving the acoustic transducer of the ANR headphones using the output signal.

18. The step of generating an output signal, wherein ANR processing on the input signal is automatically controlled to limit the loudness level of the output signal, The method according to claim 17, comprising generating an output signal, wherein the loudness level of the output signal is automatically controlled to limit the output signal to a level lower than or substantially equal to a predefined target loudness level of the output signal, or to a level substantially equal to the target loudness level.

19. The method according to claim 18, wherein the predefined target loudness level is the sound pressure level in the user's ear of the ANR headphones.

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