Classifications

• • 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

Definitions

• 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.
• Peak-clipping in the time-domain such as time-domain MPO is effective and fast, but it usually causes serious distortion of sound quality.
• high pass filters are often used; since the transient noise has most of the energy at high frequencies (sudden signal changes mean rich high frequency components) .
• Low-pass filters are also often used to attenuate the transient noise without affecting simultaneously speech content of the signal.
• 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 . Long signal-delay may thus be required and the duration of the delay is usually set substantially equal to the length of time required for control system to respond to PLI (Peak level increase) requiring correction.
• PLI Peak level increase
• this technology is more focused on broadcasting or audio recording and therefore no acoustic environment factors are considered.
• the signal processing required for the system particularly peak estimator (prefer to up-sample the input signal) , is higher than it is available in low-power digital systems such as digital hearing devices, thus this system is not suitable for miniaturized, low-power digital devices.
• 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 8OdB is required in order to not affect any first spoken syllable before the mean level has returned to 6OdB.
• This method can effectively detect stronger transient signal over average acoustic environment such as 6OdB. If the minimum threshold level is dropped below 8OdB, it can affect speech signal. On the other hand, the transient signal below 8OdB in the quiet acoustic environment, such as 4OdB, can result in big perceived shock since the gain at this soft input level is usually very high.
• 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.
• 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 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.
• Fig. 1 schematically, a block diagram of an anti-shock system according to the present invention
• FIG. 2 again schematically, a more detailed block diagram of an embodiment of the digital subsystem of Figure 1 according to the present invention
• Fig. 3 a plot of a curve showing the signal of a typical aperiodic shock signal as a function of time
• Fig. 4 schematically, a block diagram of the detection and treatment of a signal both in the time-domain according to the present invention
• Fig. 5 a double plot of curves showing above the signal of a typical aperiodic shock signal as a function of time and below the implemented gain reduction as a function of time;
• Fig. 6 schematically, a block diagram of the detection of a shock event in the time-domain and the treatment or management respectively in the frequency domain according an embodiment of the present invention
• Fig. 7 a double plot of curves showing above the signal of a shock signal as a function of time, the delayed shock signal with the system group-delay
• Fig. 8 a double plot of curves according to Figure 7 with a second stronger shock following a first weaker shock
• Fig. 9 a double plot of curves according to Figure 7 with two equal shocks following each other in a short period of time;
• Fig. 10 a double plot of curves according to Figure 7 with a second weaker shock following a first stronger shock.
• FIG. 1 a purely schematic overview of the present anti-shock method and system is shown.
• 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 coefficients 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. In a real world environment, the 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.
• Time tO 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.
• the shock contrast level dL is:
• Signal Floor Sn can be obtained through a fast smooth processing that can catch up the non-transient signal change over time.
• Signal Floor Sn here is using the fast average
• the fast averaging of input signal s(t) is processed over a short duration of such as lms 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 lower the signal floor Sn the higher the shock contrast, which will result in a stronger shock impact perception.
• 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.
• the absolute shock impact level (SIL) is:
• the relative shock impact level can be expressed as the Shock Index:
• SI O 1 ⁇ t ⁇ t 0
• ⁇ is the coefficient for Shock Index
• 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.
• the relative shock energy E may be measured as follows:
• 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) .
• 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 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 antishock management will be both performed in the time-domain, as depicted schematically in the block diagram of Figure 4.
• the whole shock part cannot be handled with the anti-shock process in the time-domain without adding additional delay, which will cause distortion of shock event .
• additional time delay is required to be added by these few samples in addition to the existing system time delay. Adding additional time delay at this juncture could cause artificial effects on the input signals.
• 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.
• anti-shock gain reduction g(t) is defined as:
• - A is the anti-shock strength
• - P is a time constant for anti-shock control.
• time constants P 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 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 ryN
• T time-delay
• 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.
• ⁇ Q is an initial gain reduction
• Ct is the time constant for anti-shock attack speed
• the factors ⁇ o / , P 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. In general, the higher the shock contrast level
• 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: A second stronger shock follows a first weaker shock, as depicted in Figure 8. In this case, the stronger shock will mask the previous one and the new anti-shock for the stronger shock will take over the control once the stronger shock is detected.
• 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. Therefore, a stronger shock happening right after a weaker shock will overtake the weaker shock management, while a stronger shock management will not be affected by a following weaker shock.
• 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 .

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• 2006
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  • 2006-06-13 EP EP06763663A patent/EP2027750B1/fr active Active
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