EP2027750B1 - Procede et systeme de detection de chocs acoustiques et application dudit procede a des protheses auditives - Google Patents

Procede et systeme de detection de chocs acoustiques et application dudit procede a des protheses auditives Download PDF

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EP2027750B1
EP2027750B1 EP06763663A EP06763663A EP2027750B1 EP 2027750 B1 EP2027750 B1 EP 2027750B1 EP 06763663 A EP06763663 A EP 06763663A EP 06763663 A EP06763663 A EP 06763663A EP 2027750 B1 EP2027750 B1 EP 2027750B1
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shock
signal
input signal
detecting
time
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EP2027750A2 (fr
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Henry Luo
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Sonova Holding AG
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Phonak AG
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; DEAF-AID SETS; PUBLIC ADDRESS SYSTEMS
    • H04R25/00—Deaf-aid sets, i.e. electro-acoustic or electro-mechanical hearing aids; Electric tinnitus maskers providing an auditory perception
    • H04R25/50—Customised settings for obtaining desired overall acoustical characteristics
    • H04R25/505—Customised settings for obtaining desired overall acoustical characteristics using digital signal processing

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  • the invention relates generally to a method and system for detecting acoustic shock signals in audio signals and to applications of that method in hearing devices.
  • the invention relates to further reduce or minimize detected shock effects in audio signals.
  • Detection of acoustic shock is a well-known problem in signal processing.
  • Acoustic shock signals are referred to as impulse signals or transient signals.
  • the nature of an impulse signal is such that its amplitude suddenly changes within a very short duration.
  • transient signals There are two typical types of transient signals: aperiodic and periodic signals.
  • An aperiodic impulse is for example generated by an explosion, gunfire or a firecracker.
  • Aperiodic shocks last for very short timeframes such as 250 ⁇ s or less.
  • a periodic impulse is usually generated from an impact between two mechanically and acoustically un-dampened objects such as two glass bottles hitting each other.
  • Periodic shocks usually have much longer durations in the order of 5 to 200ms, and also usually have a lower peak level.
  • Periodic shocks consist of multiple peaks, which come closely one after the other and have attenuated peak levels during their duration.
  • a sub-band-based acoustic shock algorithm has been presented by Todd Schneider et al. in EP 1'471'767 .
  • a pattern analysis-based approach is taken to an input signal to perform feature extraction.
  • a parameter space is identified, which is corresponding to the signal space of the input signal.
  • a rule-based decision approach is taken to the parameter space to detect an acoustic shock event and, then, the shock is removed from the input signal to generate a processed output signal.
  • the sudden sound increase is detected with a block frame of a number of samples in time-domain and similar detection also happens within each sub-band.
  • An additional sample delay of a further number of samples is used to allow the time-domain measurement enough time to notify the shock detection module in the frequency domain about the presence of a high level input before the shock reaches the filter bank, thus providing extra time for the shock-detection module to react.
  • the shock detection module in the frequency domain detects if a shock has occurred in a particular sub-band, and determines the sub-band energy measurement to be used for the gain calculation.
  • a state machine is used for sub-band shock determination by examining the sub-band energy with the shock flag. The acoustic shock phenomenon is eliminated by applying the appropriate gain reduction to the signal in each sub-band.
  • the shock detection in the sub-band is very expensive cycle budget-wise and also difficult to synchronize with the time-domain parameter extraction.
  • the sub-band strategy will not be able to detect very fast shocks reliably and accurately since the filter bank can smear the actual sound level change. It is also not desired to eliminate the shock in individual sub-bands, because this may cause the user to lose environmental awareness and, hence, not perceive correctly the nature of the shock, which might be very important information for the user. It is also expensive to implement this approach and to optimize this algorithm with existing hearing device technology. More complex hearing device systems may also suffer from excessive input-output latency or require very expensive computing power to process this strategy.
  • US 5,579,404 describes a digital audio limiter.
  • This signal processing system comprising components such as split-band perceptual coders that receive a peak amplitude limited input audio signal and can process the signal in such a manner that the processed signal preserves the apparent loudness of the input signal but is no longer peak-amplitude limited.
  • up-sampling is used in estimating the resultant peak amplitude and gain factors established in response to the estimated peak amplitude are applied to one or more frequency sub-bands of the processed signal.
  • This method and system for defining a threshold value are described to limit the output signal of a processing unit which is fed with an input signal.
  • an input-signal level is determined and the threshold value is set as a function of that input-signal level to prevent the maximum output level in the device from exceeding a predefined threshold value, which protects the user of the device from excessive noise exposure.
  • the threshold value is set as a function of the input-signal level, i.e. in adaptive fashion, it is also possible to limit transient noise whose level is well below the maximum value of the threshold value.
  • a time-based mean value across the magnitude of the input signal is calculated with the averaging performed over a relative long time interval which may be a time span of for instance 5 seconds.
  • This method uses a known fact that human speech occupies a dynamic range of about -15 to +18 dB (decibels) around the respective mean level; in quiet surroundings with little ambient noise, this mean level is about 60 to 65 dB.
  • a minimum threshold level such as 80dB is required in order to not affect any first spoken syllable before the mean level has returned to 60dB.
  • This method can effectively detect stronger transient signal over average acoustic environment such as 60dB. If the minimum threshold level is dropped below 80dB, it can affect speech signal. On the other hand, the transient signal below 80dB in the quiet acoustic environment, such as 40dB, can result in big perceived shock since the gain at this soft input level is usually very high.
  • shock reduction algorithms are implemented in the form of shock reduction algorithms. Many of these are based on peak-clipping in order to minimize delay, but, which, as previously stated, usually introduce artifacts or distortion into the signal. Some more advanced peak-clipping technologies use an adaptive clipping threshold to handle different levels of shock. However, the problems of distortion or uncomfortable artificial effects still cannot be avoided with adaptive peak clipping. Some other more sophisticated shock reduction algorithms detect transient noises in both the time-domain and individual frequency bands, then apply shock reduction in specific frequency bands while keeping the normal signal in other frequency bands untouched, as presented in the above mentioned EP 1'471'767. Although many of these algorithms are quite successful for telecommunication applications, typically experienced by a user through headphones or a headset, they usually need to add more delay and require intensive computational power. Since hearing devices possess limited computational power, this restricts the application of such techniques.
  • Acoustic shock is a type of acoustic event, which belongs to the acoustic environment. It is important that any acoustic event is not taken away from the user for his safety. In extreme examples such as a gun shot or car crash, common sense dictates that the user should be able to sense such an event so that he or she can react accordingly, but this is also true in more moderate cases of acoustic shock such as dishes breaking or a door slam.
  • the international application WO 03/003790 A1 discloses a method for detecting the presence of one or more shrieks within an audible frequency range of an audio signal. Detection is achieved by calculating the frequency spectrum of the sound present during short, successive intervals of time. From this frequency spectrum the peak power level and the average surrounding power spectral level are determined. The ratio of the peak power level to the average surrounding power spectral level is then calculated. This ratio is compared to a predetermined threshold. Furthermore, the peak power level is compared to a predetermined threshold. If the ratio of the peak power to the average surrounding power spectral level exceeds a predetermined threshold and the absolute peak power level also exceeds a predetermined threshold then a peak is deemed to be present in the current analysis block.
  • the present invention provides a method for detecting acoustic shock in a audio input signal (s(t)), comprising the steps of
  • the present method provides a quick and reliable shock detector that operates in the time-domain.
  • the shock detection takes place with zero time delay, or even predicts the shock before.it fully goes through the signal processing.
  • the signal floor (Sn) is obtained through a signal processing method catching up the non-transient signal change over time.
  • the signal processing method is provided by a lowpass filter or a fast smooth signal processing.
  • the signal processing method is catching up the non-transient signal change over time.
  • the method further comprises the step of applying anti-shock gain reduction (g(t)) when a shock event has been indicated.
  • g(t) anti-shock gain reduction
  • the present invention further provides a system for performing the claimed method.
  • This system is adapted to be used in small devices with only limited electrical power, such as in hearing devices.
  • a hearing device with adaptive shock management qualities to achieve a natural anti-shock treatment without impacting audio signals such as speech or music, thus keeping the acoustic shock event natural and comfortable for the user of the hearing device.
  • the sound input 1 a mixture of signal and noise, is first acquired by a transducer 2, i.e. a microphone, and then converted to a digital input signal 4 by an A/D converter 3.
  • This digital input signal 4 is then fed to a digital subsystem 5 comprising the below described anti-shock system.
  • a digital output signal 6, which has been treated by the anti-shock system by applying the present anti-shock method as well as by other digital components such as filters and amplifiers within the digital subsystem 5, will then be converted by a D/A converter 7 into an analog output signal 8 that will be applied to a receiver for outputting a corresponding sound 9.
  • the digital input signal 4 is on one path framed and windowed with a low-pass filter 10.
  • the windowed data is then converted from the time domain to the frequency domain via a time-to-frequency transformation such as 2N-point FFT.
  • the coefficient of the 2N-point FFT represent N frequency bands of a band-pass filter-bank.
  • the signal strength of a band is calculated from its FFT coefficients.
  • the signal strength of the band in the frequency-domain varies with time.
  • the input signal changes its frequency components over time.
  • the signal at each frequency band is processed accordingly.
  • a frequency-to-time transformation such as reverse FFT 11 is then applied to convert the coefficients from the frequency-domain to the time-domain, providing a digital output signal 6 that may be converted to an analog output signal with a D/A converter 7, as shown in Figure 1 .
  • transformation of the digital signal between the time-domain and frequency-domain also can be performed with other methods such as band-pass filters or wavelet transforms.
  • the digital input signal will be introduced into a shock detection module 12 for an immediate detection of a shock.
  • This shock detection module 12 thus continuously monitors and detects the digital input signal 4 in real time in the time-domain.
  • Figure 3 depicts the plot of the curve of the Signal s(t) of a typical aperiodic shock event as a function of the time t.
  • a periodic shock can be viewed as if it consists of a train of attenuating aperiodic shocks. Therefore, the detection of a periodic shock can be treated as a set of individual detections of aperiodic shocks, which follow one after the other.
  • shock event could start off with soft shocks and then be followed by stronger shocks. Therefore, the detection of shock needs to be designed to handle each individual shock independently. Then, an adaptive shock reduction can be applied accordingly to handle different kinds of shock within a set of successive shocks. With this approach, shock detection is simplified and different shock reduction strategies can be applied to different kinds of individual shocks.
  • Time t0 is defined as the starting point of the shock and time t2 is defined as the half-way point between peak level L and the signal floor Sn.
  • signal Floor Sn can be obtained through a fast smooth processing that can catch up the non-transient signal change over time.
  • the fast averaging of input signal s(t) is processed over a short duration of such as 1ms so that it can reflect the normal speech signal or the music signal change over time.
  • Other smoothing functions of s(t) can be applied to derive Signal Floor Sn to achive the same characteristic as the above fast averaging example.
  • the higher the shock peak level L the stronger the shock will be perceived.
  • the perceived shock strength depends on the actual shock contrast level dL and the duration T.
  • the longer the duration T of the shock the stronger the shock will be perceived. Therefore, it is critical to detect the shock level T and shock contrast in order to determine the shock impact and the necessary solution in managing the shock with an appropriate anti-shock strategy.
  • SIL L t 1 - t 0
  • SES shock energy strength
  • the shock index normalization constant ⁇ can be defined according to the individual's preference.
  • the shock index S_Index will drop.
  • the constant may be defined by using other typical shock events or shock sounds respectively as a reference for the normalization.
  • MCL minimum shock contrast level
  • MSI minimum shock Index
  • the shock detection runs in real-time with the use of the thresholds of minimum shock contrast level (MCL) and minimum Shock Index (MSI).
  • MCL minimum shock contrast level
  • MSI minimum Shock Index
  • the present shock detection includes the shock detection as such and the shock strength detection. According to the shock contrast level dL and Shock Index SI, it can determine whether a shock happens and how strong the shock is. Since the shock detection runs continuously, the shock can be detected anytime as long as it meets with the shock detection criteria; it is not necessary that shock detection happens solely at the shock peak time. This implies that a shock can be detected during its build-up process before it reaches its peak level.
  • an anti-shock management module After detection of a shock, an anti-shock management module has to react for reducing or minimizing the shock effect, by keeping the shock sound as natural as possible to allow awareness by the user of the shock event. Furthermore it should keep the relative loudness of shock so that the user can perceive the shock level and keep the shock within a comfort range of the user.
  • the shock detection and the anti-shock management will be both performed in the time-domain, as depicted schematically in the block diagram of Figure 4 .
  • the threshold delay beyond which this negative impact would happen is determined by the overall system delay, the type of shock and the actual shock detection. If the shock detection takes longer time, more samples, and thus more delay, is needed to reduce the artifacts. On the other hand the more delay is implemented due to this fact, the overall system delay could become longer than desired. Therefore, these two mechanisms are balanced to reduce artifacts and keep the overall system delay below the desired threshold.
  • anti-shock manager will apply anti-shock gain reduction g(t) to the input signal s(t) to get a new signal x(t) with anti-shock processing already completed after a shock is detected.
  • time constants ⁇ and ⁇ can be different to achieve different release speeds at different durations for different purposes; or be the same to simplify the anti-shock release process.
  • the shock detection takes place in the time-domain whereas the treatment or management respectively of the signal takes place in the frequency-domain, as depicted schematically in Figure 6 .
  • the shock detection will be carried out by the shock detection module 12 in the time domain as already described above with no additional time delay required.
  • the signal s(t) in the time-domain is then transformed into frequency-domain by a TTF module 14 for any frequency-domain signal processing in module 15 and the anti-shock management by the anti-shock management module 13.
  • the frequency-domain signal gain(f) is transformed back to time-domain by the FTT module 16 resulting in a new signal y(t).
  • the signal transformation from time-domain to frequency-domain and then back to time-domain is frame-based by applying a certain window such as Hanning or Hamming.
  • the fast shock detection in time-domain provides early prediction for anti-shock processing in frequency-domain.
  • An adaptive anti-shock management plan can thus be specified to suppress shock without artificial break of anti-shock.
  • the anti-shock gain reduction g(t) may be divided into three anti-shock phases, such as anti-shock attack phase, anti-shock holding phase and anti-shock release phase.
  • the factors A 0 , ⁇ , ⁇ or ⁇ can be pre-defined as constants or they can be adaptively updated according to the shock contrast level dL, shock index SI or Shock Duration T.
  • the higher the shock contrast level dL and/or the higher Shock Index SI the higher A 0 and/or ⁇ will be.
  • each frequency band can have a different weighting factor adjusted according to preferences. This can result in an effective anti-shock system for the preferable hearing compensation or comfort.
  • different activation functions can be selected according to the shock type and the user preference.
  • the method according the present invention is not only suitable for single shock events, but will also handle multiple shock events.
  • Figures 8 to 10 displays three different types of multiple shock events:
  • An equal shock follows a first shock, as depicted in Figure 9 .
  • the actual anti-shock relation depends on time difference between the two shocks. If they are very close, they will be detected as only one shock. If the time difference is big enough, they will be detected as two separate shocks and a similar anti-shock processing will be applied to both independently.
  • A.weaker second shock follows a stronger first shock, as depicted in Figure 10 .
  • the weaker shock after the strong shock can be masked by the stronger shock, if the time difference between them is short. If the weaker shock happens a certain time after the stronger one, it can be detected as a new shock and new anti-shock processing is applied.
  • a zero-delay or predictive shock detection and adaptive shock management has thus been achieved. Shock detection takes place with zero time delay, or even predicts the shock before it fully goes through the signal processing.
  • the present method thus is highly efficient and very fast and may be used for shock detection and shock reduction. While reducing acoustic shock adaptively, it keeps the natural sound quality of shock events for environmental awareness by the user maintained and does not hamper the user's safety.
  • This method is capable of detecting and canceling acoustic shocks adaptively under different environments and reducing the shock in an optimized way to keep the natural sound quality of shock events. It can detect various acoustic shocks reliably and adaptively to the environment.
  • the acoustic shock detection results in a shock index, which reflects the actual shock strength and allows more adaptive shock reduction accordingly. This is also very different from most other transient or impulse detection technologies which simply detect whether a transient or impulse is present or not. Based on the continuous shock detection resulting shock index SI, an adaptive shock management is carried out to adaptively reduce the acoustic shock.
  • hearing device must be understood as hearing aid, be it introduced in the ear canal or implanted into a patient, to correct a hearing impairment as well as to any communication device used to facilitate or improve communication.

Claims (17)

  1. Un procédé pour détecter des chocs acoustiques dans un signal audio d'entrée (s(t)), comprenant les pas de:
    - effectuer un monitorage du signal audio d'entrée (s(t)) dans la plage de temporisation, par quoi
    - détecter un signal de fond (Sn),
    - détecter un point culminant (L) du signal d'entrée (s(t)),
    - détecter un temps d'attaque (t1-t0) du signal d' entrée (s(t)),
    - détecter une durée de choc (T) du signal d'entrée (s(t)),
    - déterminer un niveau de choc contraste (dL) comme différence entre le point culminant (L) et le signal de fond (Sn),
    - déterminer un index de choc (SI) en appliquant la formule suivante: SI = σ ⁢ L - Sn t 1 - t 0
    Figure imgb0019
    σ étant un index normalisation constant,
    - comparer le niveau de choc contraste (dL) et l'index de choc (SI) aux valeurs de seuil respectives (MCL;MSI) et
    - indiquer un choc acoustique si les deux valeurs de seuil sont excédées.
  2. Un procédé selon la revendication 1, caractérisé en ce que le signal de fond (Sn) est obtenu par un procédé de traitement de signal rattrapant le changement du signal non-transient sur temps.
  3. Procédé selon la revendication 2, caractérisé en ce que le procédé de traitement de signal es prévu par un filtre passe-bas ou un traitement de signal lisse rapide.
  4. Procédé selon la revendication 1, caractérisé en ce le signal de fond (Sn) est dérivé de la formule: Sn = 10 ⁢ log ⁢ 1 T 0 ∫ t - T 0 t s t ⁢ dt
    Figure imgb0020
  5. Procédé selon la revendication 4, caractérisé en ce que la moyenne du s(t) est effectué pour une durée brève T0 d'environ 4ms ou moins.
  6. Un procédé selon la revendication 1, caractérisé en ce que le coefficient pour la normalisation index choc
    (σ) est prédéfini pour des évènements de choc typiques ou est déterminé par un processus autodidacte.
  7. Le procédé selon une des revendications 1 à 6, caractérisé en ce qu'il de plus comprend le pas
    - d'appliquer un gain de réduction anti-choc (g(t)) quand un événement de choc a été indiqué.
  8. Un procédé selon la revendication 7, caractérisé en ce que un gain de réduction anti-choc (g(t)) est appliqué dans la plage de temporisation au signal d'entrée (s(t)) résultant en un signal nouveau (x(t)) avec un traitement anti-choc complété.
  9. Un procédé selon la revendication 8, caractérisé en ce que un gain de réduction anti-choc (g(t)) est appliqué au signal d'entrée (s(t)) après additionner le signal de délai.
  10. Un procédé selon la revendication 7, caractérisé en ce que le gain de réduction anti-choc (g(t)) est appliqué au signal d'entrée (s(t)) dans la plage de temporisation.
  11. Un procédé selon la revendication 7, caractérisé en ce que le gain de réduction anti-choc (g(t)) est appliqué en des bandes de fréquence différentes de manière indépendante.
  12. Le procédé selon la revendication 7, caractérisé en ce qu'en outre des fonctions d'activation différentes sont sélectées selon du type de choc ou une préférence d'un utilisateur.
  13. Application du procédé selon une des revendications 1 à 12 pour opérer un dispositif auditif.
  14. Un système de traitement de signal audio pour détecter un choc acoustique dans signal audio d'entrée (s(t)) comprenant au moins un module de détection choc (12) avec un moyen qui permet de
    - effectuer un monitorage du signal audio d'entrée (s(t)) dans la plage de temporisation, par quoi
    - détecter un signal de fond (Sn),
    - détecter un point culminant (L) du signal d'entrée (s(t)),
    - détecter un temps d'attaque (t1-t0) du signal d'entrée (s(t)),
    - détecter une durée de choc (T) du signal d'entrée (s(t)),
    - déterminer un niveau de choc contraste (dL) comme différence entre le point culminant (L) et le signal de fond (Sn),
    - déterminer un index de choc (SI) en appliquant la formule suivante: SI = σ ⁢ L - Sn t 1 - t 0
    Figure imgb0021
    σ étant un index normalisation constant,
    - comparer le niveau de choc contraste (dL) et l'index de choc (SI) aux valeurs de seuil respectives (MCL;MSI) et
    - indiquer un choc acoustique si les deux valeurs de seuil sont excédées.
  15. Un système selon la revendication 14, caractérisé en ce qu'il de plus comprend au moins un module de gestion (13) avec un moyen qui permet d'appliquer un gain de réduction anti-choc (g(t)) quand un évènement de choc a été indiqué.
  16. Un système selon la revendication 15, caractérisé en ce que le module de gestion (13) marche dans la plage de temporisation.
  17. Un système selon la revendication 15, caractérisé en ce que le module de gestion (13) marche dans la gamme de fréquence.
EP06763663A 2006-06-13 2006-06-13 Procede et systeme de detection de chocs acoustiques et application dudit procede a des protheses auditives Active EP2027750B1 (fr)

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WO2011048101A1 (fr) * 2009-10-20 2011-04-28 St-Ericsson (France) Sas Traitement de chocs acoustiques
US9167359B2 (en) 2010-07-23 2015-10-20 Sonova Ag Hearing system and method for operating a hearing system
DE102016200637B3 (de) * 2016-01-19 2017-04-27 Sivantos Pte. Ltd. Verfahren zur Reduktion der Latenzzeit einer Filterbank zur Filterung eines Audiosignals sowie Verfahren zum latenzarmen Betrieb eines Hörsystems
EP3337186A1 (fr) * 2016-12-16 2018-06-20 GN Hearing A/S Système de dispositif auditif binauriculaire ayant un classificateur d'environnement impulsionnel binauriculaire
CN111341347B (zh) * 2020-03-11 2023-07-18 腾讯音乐娱乐科技（深圳）有限公司 一种噪声检测方法及相关设备
CN113132880B (zh) * 2021-04-16 2022-10-04 深圳木芯科技有限公司 基于双麦克风架构的冲击噪声抑制方法和系统

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AUPR604201A0 (en) 2001-06-29 2001-07-26 Hearworks Pty Ltd Telephony interface apparatus
CA2424093A1 (fr) * 2003-03-31 2004-09-30 Dspfactory Ltd. Methode et dispositif de protection contre les chocs acoustiques
DE102004041199B4 (de) * 2004-08-25 2006-06-29 Dietmar Ruwisch Verfahren und Vorrichtung zum Dämpfen von Schallsignalen

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