Abstract:
An apparatus, method, and medium for detecting an impact sound and an apparatus, method, and medium for discriminating the impact sound using the same. The impact sound detecting apparatus includes: an onset detector separating an input signal of a frame unit into a low frequency signal and a high frequency signal, measuring powers of the separated signals, and detecting onsets by detecting changes in the measured powers; an event buffer buffering the powers measured by the onset detector and spectral data of the input signal; and an impact sound verifier determining whether each of the detected onsets is an impulse onset, and if each of the detected onsets is the impulse onset, detecting events starting from the impulse onsets by checking the powers stored in the event buffer and determining each of the detected events to be an impulse event if each of the detected onsets satisfies a predetermined condition.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS  
       [0001]     This application claims the benefit of Korean Patent Application No. 2004-8738, filed on Feb. 10, 2004, in the Korean Intellectual Property Office, the disclosure of which is incorporated herein in its entirety by reference.  
       BACKGROUND OF THE INVENTION  
       [0002]     1. Field of the Invention  
         [0003]     Embodiments of the present invention relate to an apparatus, method, and medium for detecting an impact sound and an apparatus, method, and medium for discriminating the impact sound using the same, and more particularly, to an apparatus, method, and medium for detecting an impact sound among various sounds generated from the surrounding environments and an impact sound discriminating apparatus, method, and medium for discriminating whether the detected impact sound is a target impact sound.  
         [0004]     2. Description of the Related Art  
         [0005]     An impact sound or an impulsive acoustical event generated by a mechanical interaction between objects has a short duration and relatively high intensity. This characteristic of the impact sound is called impulsiveness. According to signal processing theories, the impulsiveness can be modeled as a zero-state impulse response of a linear system.  
         [0006]     The impact sound, for example, includes a simplex sound, such as a sound generated when a pane of glass is hit by a solid stick, and a complex sound such as an explosion sound and a sound generated when a coin drops a floor.  
         [0007]     The impact sound is discriminated by detecting and discriminating the existence and characteristics of an impulsive acoustical event from a consecutive sound stream.  
       SUMMARY OF THE INVENTION  
       [0008]     Embodiments of the present invention provide an impact sound detecting apparatus, method, and medium for sensing an onset signal and detecting an impact sound.  
         [0009]     Embodiments of the present invention also provide an impact sound discriminating apparatus, method, and medium for discriminating whether a detected impact sound is a target impact sound by verifying the detected impact sound using impact sound sources.  
         [0010]     Additional aspects and/or advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.  
         [0011]     To achieve the above and/or other aspects and advantages, embodiments of the present invention set forth an impact sound detecting apparatus, including an onset detector separating an input signal of a frame unit into a low frequency signal and a high frequency signal, measuring powers of the separated low frequency and high frequency signals, and detecting an onset by detecting changes in the measured powers, an event buffer buffering the measured powers and corresponding spectral data of the input signal, and an impact sound verifier determining whether each detected onset is an impulse onset, and if each detected onset is the impulse onset then detecting events starting from the corresponding impulse onsets by checking the corresponding measured powers stored in the event buffer and identifying each of the detected events to be an impulse event if each of the detected onsets satisfies a predetermined condition.  
         [0012]     The onset detector may include an AC/DC separator separating an AC component from the input signal, as the high frequency signal, and a DC component from the input signal, as the low frequency signal, a high frequency onset detector obtaining a phase characteristic and an amount of power change of the AC component in a frequency domain, calculating amounts of power change of the AC component in a time domain, detecting onsets of the AC component using the phase characteristic and the amounts of power change of the AC component, and outputting a trigger value, a low frequency onset detector subdividing the DC component into frequency bands, obtaining amounts of power change for each frequency band, detecting onsets of the DC component by comparing the amounts of power change of each frequency band with a first threshold and combining the amounts of power change of each frequency band, and outputting an onset determining value, and an onset determiner identifying whether onsets occur in the input signal using respective amounts of power change for the AC component and each frequency band, the trigger value, and the onset determining value.  
         [0013]     The AC/DC separator may include a low pass filter passing the low frequency signal of the input signal, and a subtractor outputting the high frequency signal by subtracting the low frequency signal from the input signal.  
         [0014]     The high frequency onset detector may include a frequency domain onset detector obtaining a phase linearity in the frequency domain and a power change ratio by performing fast-Fourier transform on the AC component, a time domain onset detector obtaining powers of the AC component in the time domain and obtaining the amounts of power change of the AC component by respective spectral data of the input signal, a combiner combining an output of the frequency domain onset detector and an output of the time domain onset detector, and an onset trigger unit identifying an output of the combiner to be the onsets of the AC component according to the amounts of power change of the AC component from the time domain onset detector and outputting the corresponding trigger value.  
         [0015]     Further, the frequency domain onset detector may include a fast Fourier transformer (FFT) performing the fast-Fourier transform on the AC component, a linear phase span unit approximating phases of corresponding fast-Fourier-transformed spectral data to a linear function and obtaining a difference between a phase of the approximated first spectral data and a phase of spectral data located at a center of the frame unit, and a banked power increasing ratio calculator obtaining powers of the fast-Fourier-transformed spectral data, comparing powers of a first half of the frame unit with a second half of the frame unit, and obtaining a ratio of the compared powers greater than a second threshold.  
         [0016]     The time domain onset detector may include a power calculator obtaining a power of the AC component and scaling the obtained power logarithmically, a delta calculator calculating a difference between log-powers of current spectral data and previous spectral data output from the power calculator, and an onset filter obtaining an average of log-powers in a current frame unit and outputting a difference between the log-power average of the current frame and a log-power average of a previous frame.  
         [0017]     Further, the onset filter is a second order filter formed by combining two first order filters and has an impulse response as follows: 
 
 h ( n )=(1− e   1/τ     e   ) e   n/τ     e   )−(1− e   1/τ     i   ) e   n/τ     i     , n= 1, 2, 3, 
 
         [0018]     where τ e  and τ i  are time constants of the two first order filters.  
         [0019]     The combiner may further include a first weighting unit matched-filtering an output of the linear phase span unit, a second weighting unit shift-multiplying outputs of the banked power increasing ratio calculator and the delta calculator, and a third weighting unit performing an identity operation of an output of the onset filter, wherein the combiner adds outputs of the first, second, and third weighting units and outputs a result of the addition.  
         [0020]     In addition, the onset trigger unit may output a positive or negative value based on an output of the combiner, using an output of the onset filter as a control signal.  
         [0021]     Similarly, the low frequency onset detector may include a filter bank unit subdividing the DC component into frequency bands, a power calculator calculating a power for each frequency band and scaling the calculated powers logarithmically, a delta calculator calculating differences of log-powers output from the power calculator between neighboring frequency bands, a comparator determining whether a local onset occurs by comparing each delta log-power output from the delta calculator for each frequency band with the first threshold, and a combiner combining the detected local onsets, detected by the comparator, to output the onset determining value.  
         [0022]     The onset determiner may output a binary signal indicating whether an onset occurs by adding the trigger value and the onset determining value if the trigger value is output and a ratio of powers measured by the high frequency onset detector to a total power of the input signal is greater than the second threshold.  
         [0023]     In addition, the onset determiner may output a binary signal indicating whether an onset occurs by adding the trigger value and the onset determining value if the onset determining value is output and a ratio of powers measured by the low frequency onset detector to a total power of the input signal is greater than the second threshold.  
         [0024]     The onset detector may further include a noise level detector detecting a noise level of the input signal, where the onset detector detects onsets from a signal obtained by subtracting the detected noise level from the input signal.  
         [0025]     Further, the impact sound verifier may include an impulse onset selector determining whether each of the detected onsets is an impulse onset by checking the corresponding measured powers stored in the event buffer if the detected onsets are detected by the onset detector, an event former searching each event duration started from the impulse onsets using the measured powers stored in the event buffer, and an impulse event selector identifying each event searched by the event former to be an impulse event if corresponding events satisfy characteristics for the impulse event.  
         [0026]     The impulse onset selector, if the onsets are detected, may determine whether power peaks occur by monitoring the measured powers stored in the event buffer and determine whether the detected onsets are impulse onsets by comparing amounts of power increases from a start time of each of the detected onsets to each of power peak times with a predetermined threshold.  
         [0027]     The event former may also form each of the events by defining a start time of an event duration as an occurrence time of each of the power peaks and an ending time of the event duration as a time when power falls below a predetermined level or when the impulse onset selector outputs a succeeding impulse onset. The impulse event selector may also search a power function approximating the events formed by the event former and determine whether each of the events is an impulse event by determining whether the power function attenuates exponentially within a predetermined range from each of the power peaks.  
         [0028]     To achieve the above and/or other aspects and advantages, embodiments of the present invention set forth an impact sound detecting method including separating an input signal of a frame unit into an AC component, from the input signal, a high frequency signal and a DC component, from the input signal, as a low frequency signal, measuring powers of the separated high and low frequency signals and detecting onsets by checking changes of the measured powers, buffering the measured powers and the input signal and determining whether each of the detected onsets is an impulse onset, detecting events starting from onsets determined to be impulse onsets by checking the buffered powers for each of the detected onsets determined to be impulse onsets, and identifying each of the detected events to be an impulse event if the detected events satisfy a predetermined condition.  
         [0029]     The detecting of the onset may include obtaining a phase characteristic and an amount of power change of the AC component in a frequency domain, calculating an amount of power change of the AC component in a time domain, detecting onsets of the AC component by combining the phase characteristic and the amounts of power change for the AC component in the frequency and time domains, to output a trigger value, subdividing the DC component into frequency bands and obtaining amounts of power change for each frequency band, detecting onsets of the DC component by comparing the amounts of power change of the DC component for each frequency band with a first threshold and combining the amounts of power change for each frequency band, and detecting the onsets of the input signal based ona combining the detected onsets of the AC and DC components, the trigger value and the onset determining value.  
         [0030]     In addition, the phase characteristic may be obtained by performing fast-Fourier transform on the AC component, approximating phases of the fast-Fourier-transformed AC component spectral data to a linear function, and obtaining a difference between a phase of an approximated first spectral data and a phase of spectral data located at a center of the frame unit.  
         [0031]     Similar to above, the amount of power change of the AC component in a frequency domain can be obtained by performing fast-Fourier transform on the AC component, and obtaining a ratio of power increase greater than a second threshold by comparing powers of a first half of the frame unit of the fast-Fourier-transformed AC component spectral data with a second half of the frame unit.  
         [0032]     Further, the amounts of power change of the AC component in a time domain can be obtained by obtaining a power of the AC component and scaling the obtained power logarithmically, calculating a difference between log-powers of current spectral data and previous spectral data, and obtaining an average of the log-powers in a current frame unit and outputting a difference between log-power averages of the current frame unit and a previous frame unit.  
         [0033]     The combining of the phase characteristic and the amounts of power change may include matched-filtering the phase characteristic, shift-multiplying the amounts of power change in the frequency domain and the time domain, and performing identity operation on a difference between log-power averages of a current frame unit and a previous frame unit, wherein the matched-filtering result, the shift-multiplying result, and the identity operation result are added.  
         [0034]     In addition, the detecting of the onsets of the input signal may include outputting a binary signal, indicating whether an onset occurs, obtained by adding the trigger value and the onset determining value if the trigger value is output and a ratio of a measured power the AC component to a total power of the input signal is greater than a second threshold.  
         [0035]     The identifying of each of the detected events to be the impulse event may include determining whether power peaks occur by monitoring the buffered powers and determining whether each of the onsets is the impulse onset by comparing a power value increased from a start time of each of the onsets to a power peak time with a predetermined threshold.  
         [0036]     In addition, the detecting of events may include forming events by defining a start time of each event duration as the power peak time and an ending time of each event duration as a time when power falls below a predetermined level or when a succeeding impulse onset occurs.  
         [0037]     The identifying of the detected events to be the impulse event may also include searching a power function approximating events formed in the detecting of events and determining whether each of the detected events is the impulse event by determining whether the power function attenuates exponentially within a predetermined range from each power peak.  
         [0038]     To achieve the above and/or other aspects and advantages, embodiments of the present invention set forth an impact sound discriminating apparatus including an onset detector separating an input signal of a frame unit into a low frequency signal and a high frequency signal, measuring powers of the separated low and high frequency signals, and detecting onsets by checking changes of the measured powers, an event buffer buffering the measured powers and the input signal, an impact sound verifier determining whether each of the detected onsets is an impulse onset, and if a detected onset is the impulse onset, detecting events starting from impulse onsets by checking the measured powers stored in the event buffer and identifying each of the detected onsets to be an impulse event if each of the detected onsets satisfies a predetermined condition, and an impact sound source verifier, if each of the detected onsets is identified to be the impulse event, discriminating impulse events by comparing the impulse events with target impact sound events.  
         [0039]     The onset detector may include an AC/DC separator separating an AC component of the input signal, as the high frequency signal, and a DC component of the input signal, as the low frequency signal, a high frequency onset detector obtaining a phase characteristic and an amount of power change of the AC component in a frequency domain, calculating an amount of power change of the AC component in a time domain, detecting onsets of the AC component using the phase characteristic and the amounts of power change of the AC component, and outputting a trigger value, a low frequency onset detector subdividing the DC component into frequency bands, obtaining an amount of power change for each frequency band, detecting onsets of the DC component by comparing the amounts of power change for each frequency band with a first threshold and combining the amounts of power change for each frequency band, and outputting an onset determining value, and an onset determiner determining whether onsets occur in the input signal using respective amounts of power change for the AC component and each frequency band, the trigger value, and the onset determining value.  
         [0040]     The impact sound verifier may also include an impulse onset selector determining whether each of the detected onsets is the impulse onset by checking the measured powers stored in the event buffer, an event former, if it is determined that each of the detected onsets is the impulse onset, searching each event duration started from the impulse onsets using the measured powers stored in the event buffer, and an impulse event selector determining each event searched by the event former to be the impulse event if the events satisfy impulse event characteristics.  
         [0041]     Further, the event former may output time stamps between a start time and an ending time of the event duration, and the impact sound source verifier may include a feature vector extractor extracting feature vectors from spectral data corresponding to the time stamps among spectral data stored in the event buffer, and a classifier discriminating the input signal by calculating similarities between the extracted feature vectors and feature vectors of the target impact sound events.  
         [0042]     Here, the feature vector extractor may include a divider dividing spectral data input from the event buffer within the time stamps into segments, an accumulator accumulating the spectral data for each segment to generate vectors, and a discrete-cosine-transformer outputting feature vectors by performing discrete-cosine-transform on the vectors.  
         [0043]     The accumulator may normalize the accumulated results so that a variance of the accumulated results is compensated for. Further, the classifier may further include a template pool storing feature vectors of the target impact sounds.  
         [0044]     To achieve the above and/or other aspects and advantages, embodiments of the present invention set forth an impact sound discriminating method including separating an input signal of a frame unit into an AC component of a high frequency and a DC component of a low frequency, measuring powers of the separated high and low frequency signals and detecting onsets by checking changes of the measured powers, buffering the measured powers and the input signal and determining whether each of the detected onsets is an impulse onset, detecting each event starting from impulse onsets by checking the buffered measured powers if a detected onset is the impulse onset, determining detected events to be an impulse event if the detected events satisfy a predetermined condition, and identifying impulse events by comparing the impulse events with target impact sound events if a detected event is determined to be the impulse event.  
         [0045]     The detecting of the onset may include obtaining a phase characteristic and an amount of power change of the AC component in a frequency domain, calculating an amount of power change of the AC component in a time domain, detecting onsets of the AC component by combining the phase characteristic and the amounts of power change of the AC component to output a trigger value, subdividing the DC component into frequency bands and obtaining the amounts of power change for each frequency band, detecting onsets of the DC component by comparing the amounts of power change of the DC component for each frequency band with a first threshold and combining the amounts of power change, and detecting onsets of the input signal by combining the detected onsets of the AC and DC components, the trigger value, and the onset determining value.  
         [0046]     The determining of each of the detected events to be the impulse event may further include determining whether power peaks occur by monitoring the buffered measured powers and determining whether each of the onsets is the impulse onset by comparing a power value increased from a start time of each of the onsets to a power peak time with a predetermined threshold.  
         [0047]     In addition, the detecting of the events may include forming events by defining a start time of each of event durations as the power peak time and an ending time of each of the event durations as a time when power falls below a predetermined level or when a succeeding impulse onset occurs.  
         [0048]     Further, the identifying of the impulse events may include obtaining time stamps between a start time and an ending time of each of the event durations, extracting feature vectors from spectral data corresponding to the time stamps among buffered spectral data, and discriminating the input signal by calculating similarities between the extracted feature vectors and feature vectors of the target impact sound events.  
         [0049]     The extracting of the feature vectors may include dividing the buffered spectral data within the time stamps into segments, accumulating spectral data for each segment to generate vectors, and obtaining feature vectors by performing discrete-cosine-transform on the generated vectors. Further, the accumulating normalizes the accumulated results so that a variance of the accumulated results is compensated for.  
         [0050]     To achieve the above and/or other aspects and advantages, embodiments of the present invention set forth a medium for impact sound detecting including computer readable code implementing embodiments of the present invention, and embodiments of the present invention set forth a medium for impact sound discriminating including computer readable code implementing embodiments of the present invention. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0051]     These and/or other aspects and advantages of the invention will become apparent and more readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:  
         [0052]      FIG. 1  is a block diagram of an apparatus for detecting and discriminating an impact sound, according to an embodiment of the present invention;  
         [0053]      FIG. 2  illustrates a signal having two events;  
         [0054]      FIG. 3  is a detailed block diagram of an onset detector of  FIG. 1 , according to an embodiment of the present invention;  
         [0055]      FIG. 4A  illustrates an example of a linear component of an unwrapped phase spectrum extracted from the signal of  FIG. 2 ;  
         [0056]      FIG. 4B  illustrates a result of spanning the linear component of the phase spectrum of  FIG. 4A ;  
         [0057]      FIG. 5A  illustrates an example of a result of calculating a power increasing ratio of the signal of  FIG. 2 ;  
         [0058]      FIG. 5B  illustrates an example of a result of calculating powers of the signal of  FIG. 2 ;  
         [0059]      FIG. 5C  illustrates an example of a result of scaling the powers of  FIG. 5B  logarithmically;  
         [0060]      FIG. 5D  illustrates an example of a output signal of a delta calculator of  FIG. 3 ;  
         [0061]      FIG. 6  illustrates an example of a result of applying an onset filter to log-powers of  FIG. 5B ;  
         [0062]      FIG. 7  is a detailed block diagram of an impact sound verifier of  FIG. 1 , according to an embodiment of the present invention;  
         [0063]      FIG. 8  illustrates a typical impulse event signal;  
         [0064]      FIGS. 9A through 9D  illustrate log-power signals for input signals and approximated signals for the log-power signals; and  
         [0065]      FIG. 10  is a detailed block diagram of an impact sound source verifier of  FIG. 1 , according to an embodiment of the present invention. 
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS  
       [0066]     Reference will now be made in detail to the embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout. The embodiments are described below to explain the present invention by referring to the figures.  
         [0067]      FIG. 1  is a block diagram of an apparatus for detecting and discriminating an impact sound, according to an embodiment of the present invention. Referring to  FIG. 1 , an impact sound detecting apparatus may include an onset detector  11 , an event buffer  15 , and an impact sound verifier  12 .  
         [0068]     An impact sound discriminating apparatus may include the impact sound detecting apparatus and an impact sound source verifier  13 .  
         [0069]     The onset detector can further include a noise level detector  14  for onset detection, and the impact sound source verifier  13  can further include a template pool  16 .  
         [0070]     The onset detector  11  separates an input signal of a frame unit into a low frequency signal and a high frequency signal, measures the powers of the signals, and detects onsets by performing a Fourier analysis and other statistical processes with respect to the signals.  
         [0071]     Here, the onset, a suddenly occurring physical event signal, shows a rapid amplitude or power increase. The event, an acoustic event, has a decay pattern as general events have. The event has a duration from an onset to a time when a power falls below a predetermined level or when another impulse onset occurs.  
         [0072]      FIG. 2  illustrates a signal having two events. The illustrated signal was generated when a wood plate was hit by a wood stick, with the duration of the signal being 0.27 seconds. Reference numbers  11 - 1  and  11 - 2  indicate onsets of impulse events, with an interval between the onsets being about 23 ms.  
         [0073]     The event buffer  15  stores spectral data of the input signal and power data generated when the input signal is processed by the onset detector  11 .  
         [0074]     The noise level detector  14  detects a long-term noise level from the input signal. The onset detector  11  can detect onsets by subtracting the long-term noise level from the input signal and processing the subtracted signal.  
         [0075]     The impact sound verifier  12  verifies and outputs impulse event onsets (hereinafter, impulse onset) from the onset detected by the onset detector  11 . The impact sound verifier  12  verifies whether the onsets detected by the onset detector  11  are impulse onsets using the power data stored in the event buffer  15 . An impulse onset is verified by confirming whether an absolute value of a power level is larger than a predetermined threshold after the onset and whether there is a power decay pattern as shown in a general impact sound pattern.  
         [0076]     The impact sound source verifier  13  extracts and classifies feature vectors of the spectral data stored in the event buffer  15  and verifies whether the input signal includes a target impact sound. The template pool  16  stores a plurality of feature vectors referred to when the feature vectors from the input signal are classified.  
         [0077]      FIG. 3  is a detailed block diagram of the onset detector  11  of  FIG. 1 , according to an embodiment of the present invention. The onset detector  11  detects onsets by processing an input signal in a frame unit using a window of a size of N samples, wherein N is an even number. Referring to  FIG. 3 , the onset detector  11  includes an AC/DC separator  20 , a high frequency onset detector (HOD)  21 , a low frequency onset detector (LOD)  23 , and an onset determiner  24 .  
         [0078]     The AC/DC separator  20  includes a low pass filter (LPF)  201  and an adder  202  and separates AC/DC signals from the input signal. The DC signal is obtained by passing the input signal through the LPF  201  and extracting only a low frequency component. The AC signal is obtained by subtracting the low frequency component from the input signal. Here, the input signal is processed in a frame unit.  
         [0079]     The HOD  21  includes a fast Fourier transformer (FFT)  211 , a linear phase span unit (LPS)  212 , a first weighting unit  213 , a banked power increasing ratio calculator  214 , a second weighting unit  215 , a power calculator  216 , a delta calculator  217 , an onset filter  218 , a third weighting unit  219 , a combiner  220 , and an onset trigger unit  221  and detects onsets of a high frequency component. Here, the FFT  211 , the LPS  212 , and the banked power increasing ratio calculator  214  are signal processing blocks operated in a frequency domain; and the power calculator  216 , the delta calculator  217 , and the onset filter  218  are signal processing blocks operated in a time domain.  
         [0080]     The FFT  211  fast-Fourier-transforms the AC component of the input signal.  
         [0081]     If spectral data of the input signal is x(0), x(1), . . . , x(N−1), and each half of a frame is Y1 and Y2, Y1 and Y2 are vectors, each having N/2 elements. Y1 and Y2 are represented as shown in Equation 1 below.  
                 Y   1     =     DFT   ⁡     (     {       x   ⁡     (   0   )       ,     x   ⁡     (   1   )       ,   …   ⁢           ,     x   ⁡     (       N   2     -   1     )         }     )         ,     
     ⁢       Y   2     =     DFT   ⁡     (     {       x   ⁡     (     N   2     )       ,     x   ⁡     (       N   2     +   1     )       ,   …   ⁢           ,     x   ⁡     (   N   )         }     )                 Equation   ⁢           ⁢   1             
 
         [0082]     Here, DFT is a function of discrete Fourier transform.  
         [0083]     The LPS  212  unwraps phases of the spectral data and extracts linearity of the unwrapped phase spectrum φ(n). Here, φ(n), a linear function, can be approximated using Equation 2 below. 
 
{circumflex over (ψ)}( n )=α n +{circumflex over (ψ)}(0)   Equation 2 
 
         [0084]     Here, α is a constant number.  
         [0085]     According to Equation 2, the linearity of φ(n) can be approximated using square deviation of φ(n) as shown in Equation 3 below.  
                       Phase   ⁢           ⁢   linearity     =           ∑   n     ⁢           ⁢       (       φ   ⁡     (   n   )       -     φ   _       )     2           ∑   n     ⁢           ⁢       (       φ   ⁡     (   n   )       -       φ   ^     ⁡     (   n   )         )     2         ⁢           ⁢   where       ,                 φ   _     =       1   N     ⁢       ∑   n     ⁢           ⁢     φ   ⁡     (   n   )                         Equation   ⁢           ⁢   3             
 
         [0086]     If Equation 3 is applied to each spectral data, in order to unwrap the phases of the spectral data, the LPS  212  adds 2mπ to each phase angle so that the absolute values of differences between all adjacent phase angles are not larger than π. Here, m is a natural number. A linear component is represented as a linear function whose frequency n is between 0 and N/2 and whose value is 0 when n=0. A slope of the linear function is a value obtained by multiplying 24 by an inner product of (1, 2, . . . , N/2) and first through (N/2)th unwrapped phase angles and dividing the multiplied result by N(N+1)(N+2).  
         [0087]     A linear phase span is calculated from a difference between a first phase linearity value and an (N/2)th phase linearity value.  
         [0088]      FIG. 4A  illustrates an example of a linear component of an unwrapped phase spectrum extracted from the signal of  FIG. 2 .  FIG. 4B  illustrates an example of a result of spanning the linear component of the phase spectrum of  FIG. 4A .  
         [0089]     The first weighting unit  213  checks the latest output values following a linearly increasing pattern of the LPS  212 . It is preferable that the first weighting unit  213  is a matched filter. An output of the first weighting unit  213  is calculated from a value obtained by multiplying N/2 by an inner product of a vector including the latest N/2 output values of the LPS  212  and a desired pattern vector. Here, the desired pattern vector has an ideal linear phase span, and an ideal value corresponding to a kth linear phase span is 24(N/2−k)/(N−1_N(N+1))π.  
         [0090]     The banked power increasing ratio calculator  214  obtains powers of upper N/2 and lower N/2 spectral data from a current frame as indicated in Equation 4 below, counts the number of frequencies having a power increase that is greater than a predetermined threshold, and outputs a result of dividing the counted number by N/2.  
               Power   ⁢           ⁢   increasing   ⁢           ⁢   ratio     =       2   N     ⁢       ∑     n   =   0         N   2     -   1       ⁢     s   ⁡     (       log   ⁢              Y   2     ⁡     (   n   )            2       -     log   ⁢              Y   1     ⁡     (   n   )            2       -   th     )                   Equation   ⁢           ⁢   4             
 
         [0091]     where, th is a threshold larger than 0 and s(t) indicates a step function where t≧0.  
         [0092]     According to a calculating result of Equation 4, a high level (nearly 1) is obtained near an onset time, and the duration of the high level zone depends on a length of a window.  FIG. 5A  illustrates an example of a result of calculating a power increasing ratio of the signal of  FIG. 2 . Referring to  FIG. 5A , the high level is maintained near the onset for a predetermined time period.  
         [0093]     The power calculator  216  calculates power of an AC component of a frame and scales the power with a log operator. The delta calculator  217  obtains a difference between a current input log-power and an immediately previous input log-power. The power and delta-log-power are calculated using Equation 5 below.  
                   Power   =       1   N     ⁢       ∑     n   =   0       N   -   1       ⁢       x   ⁡     (   n   )       2                       Delta   ⁢     -     ⁢   log   ⁢     -     ⁢   power     =     log   ⁡     (       ∑     n   =     N   2         N   -   1       ⁢         x   ⁡     (   n   )       2     /       ∑     n   =   0         N   2     -   1       ⁢       x   ⁡     (   n   )       2           )                     Equation   ⁢           ⁢   5             
 
         [0094]      FIG. 5B  illustrates an example of a result of calculating powers of the signal of  FIG. 2 . Referring to  FIG. 5B , the powers dramatically increase at the onsets.  FIG. 5C  illustrates a result of scaling the powers of  FIG. 5B  logarithmically. Referring to  FIG. 5C , a reference number  216   a  indicates a noise level, and a reference number  216   b  indicates a threshold larger than the noise level by around 10.8 dB.  FIG. 5D  illustrates an example of an output signal of the delta calculator  217  of  FIG. 3 . Referring to  FIG. 5D , a location where the onset occurred can be obtained more exactly.  
         [0095]     The second weighting unit  215  shift-multiplies an output of the banked power increasing ratio calculator  214  and an output of the delta calculator  217 . The shift-multiply operation will now be described in detail. If X and Y indicate two vectors, s indicates a shift operation, and Z indicates a result of shift-multiplying X and Y, a kth element of Z is obtained from a maximum value among values obtained by multiplying respective elements of X and Y, each having k−s through k+s indexes. If s=0, the shift-multiplied result is the same as a result of a scalar multiplication of the two vectors.  
         [0096]     The onset filter  218  calculates an average in a current frame and a previous frame, respectively, of the log-powers output from the power calculator  216  and outputs a value obtained by subtracting the previous average from the current average. The two averages are calculated using a second filter formed by combining two first order linear filters, and an impulse response to the combined filter is calculated using Equation 6 below. 
 
 h ( n )=(1− e   1/τ     e   ) e   n/τ     e   )−(1− e   1/τ     i   ) e   n/τ     i     , n= 1, 2, 3,   Equation 6 
 
         [0097]     Here, τ e  and τ i  indicate time constants of two first order linear filters, and τ e ≦τ i .  
         [0098]      FIG. 6  illustrates an example of a result of applying an onset filter to log-powers of  FIG. 5B .  
         [0099]     The third weighting unit  219  may be an identity operator.  
         [0100]     The combiner  220  adds outputs of the first, second, and third weighting units  213 ,  215 , and  219 . If a result of the addition is positive, it indicates that all outputs of the first, second, and third weighting units  213 ,  215 , and  219  exceed a predetermined threshold.  
         [0101]     The onset trigger unit  221  outputs a positive or negative trigger value according to an output of the combiner  220  by using the output of the onset filter  218  as a control signal. If the control signal is smaller than an active level, the onset trigger unit  221  outputs the negative value regardless of the output of the combiner  220 , and if the control signal is equal to or larger than the active level, the onset trigger unit  221  outputs the positive value when the output of the combiner  220  is positive and the negative value when the output of the combiner  220  is negative.  
         [0102]     The LOD  23  includes a filter bank unit  231 , a power calculator  232 , a delta calculator  233 , a comparator  234 , and a combiner  235 .  
         [0103]     The filter bank unit  231  includes a plurality of band pass filters (not shown) and subdivides the low frequency audio signal output from the LPF  201  into frequency bands. The power calculator  232  accumulates powers of the low frequency audio signals corresponding to each band. The delta calculator  233  subtracts the power of an (i−1)th band from the power of an ith band and outputs a delta log-power by taking a logarithm of the result of subtraction. The comparator  234  detects a local onset in each band by determining whether the delta log-power is larger than a predetermined threshold. The combiner  235  combines onsets detected in each band and outputs an onset determining value of the entire low frequency band.  
         [0104]     The onset determiner  24  adds outputs of the HOD  21  and the LOD  23  and outputs a binary signal indicating whether or not an onset occurs. If the output signal of the LOD  23  is positive and the power of the entire low frequency band calculated by the power calculator  232  is larger than or equal to 20% of the total audio signal power, or if the output signal of the HOD  21  is positive and a power of the entire high frequency band calculated by the power calculator  216  is larger than or equal to 5% of the total audio signal power, it is determined that an onset occurred. Otherwise, it is determined that an onset did not occur.  
         [0105]      FIG. 7  is a block diagram of the impact sound verifier  12  of  FIG. 1 . Referring to  FIG. 7 , the impact sound verifier  12  includes an impulse onset selector  31 , an event former  32 , and an impulse event selector  33 .  
         [0106]     If an onset is detected by the onset detector  11 , the impulse onset selector  31  monitors log-powers buffered in the event buffer  15  and outputs a result of whether a power peak of the onset occurs. The power peak occurs when a logarithmically scaled power reaches a maximum value in an onset duration. The onset duration is a period during which the onset trigger unit  221  of  FIG. 2  is in an active state. The impulse onset selector  31  also searches a zone where power dramatically increases between an onset start time and a peak time. In the zone, there are consecutive data showing power increase greater than a first threshold during a shorter duration than a second threshold. If the search succeeds, the impulse onset selector  31  outputs a positive value. Otherwise, it outputs a negative value.  
         [0107]     The event former  32  is triggered when the impulse onset selector  31  outputs the positive value and determines an event duration while monitoring log-powers, which are output from the event buffer  15 , from when the power peak occurs. The event duration is from an event start time to an event ending time. The event start time is defined as the time when the power peak occurs, and the event ending time is when the log-power falls below a background noise level or when the event former  32  is triggered again by the impulse onset selector  31 . The event former  32  outputs time stamps at the event start time and the event ending time to the impact sound source verifier  13 .  
         [0108]     If the event ending time is indicated by one of the above two cases, the impulse event selector  33  determines whether the peak level of the event signal attenuates in an appropriate attenuating method during the event duration. That is, the impulse event selector  33  determines whether an entire event attenuated from the onset is an impulse event. Here, the appropriate attenuating method is referred to have the peak level attenuated exponentially, and the determining is achieved by selecting a power function indicating a log-power signal pattern and examining whether a parameter indicating a degree of attenuation is within an appropriate range.  
         [0109]      FIG. 8  illustrates a typical impulse event signal. The impulse signal in  FIG. 8  includes an input signal  80 , a log-power signal  81 , a noise level  82 , a level of 10.8 dB higher than the noise level  83 , and an onset  84 . Referring to  FIG. 8 , the onset  84  dramatically increases. Reference number  85  indicates an almost linearly attenuating log-power level showing a characteristic of the impulse event. The slope of the log-power shown in  FIG. 8  can be represented with an exponential function exp(●) −λ , wherein λ approximates the slope of the log-power.  
         [0110]     The impulse event selector  33  searches λ approximating to the log-power signal and determines whether λ is within a desired range.  
         [0111]      FIGS. 9A through 9D  illustrate log-power signals corresponding to input signals and approximated signals corresponding to the log-power signals. Referring to  FIGS. 9A through 9D , reference numbers  90 - 1 ,  90 - 2 ,  90 - 3 , and  90 - 4  indicate input signals, and reference numbers  91 - 1 ,  91 - 2 ,  91 - 3 , and  91 - 4  indicate log-powers of the input signals, respectively. Reference numbers  92 - 1 ,  92 - 2 ,  92 - 3 , and  92 - 4  indicate approximated log-power signals. When each log-power signal is between a noise level set for each signal and a threshold higher than the noise level, the log-power signals are approximated to 0, and when each log-power signal attenuates from each onset to a threshold, the log-power signals are approximated to signals where λ is 0.520, 0.959, 1.435, and 37.59, respectively.  FIG. 9B  shows an ideal impulse event signal, wherein λ is nearly 1.  FIGS. 9A and 9C  show impulse event signals.  FIG. 9D  also shows a dramatically increasing power level. However, since λ&gt;&gt;1, the signal cannot be admitted as an impulse event. Actually,  FIG. 9D  shows a phonetic signal not an impact sound.  
         [0112]     If the impulse event selector  33  determines the input signal to be an impulse event signal, it triggers the impact sound source verifier  13 .  
         [0113]      FIG. 10  is a detailed block diagram of the impact sound source verifier  13  of  FIG. 1 . Referring to  FIG. 10 , the impact sound source verifier  13  includes a feature vector extractor  41  and a classifier  42 .  
         [0114]     The feature vector extractor  41  includes a divider  411 , an accumulator  412 , and a discrete cosine transformer (DCT)  413  and extracts appropriate feature vectors from spectral data of an event.  
         [0115]     The divider  411  divides spectral data input from the event buffer  15  into M segments within an interval specified by the time stamps input from the event former  32 . The accumulator  412  accumulates the spectral data per each segment and generates M vectors, each having N/2 elements. Here, the accumulated result can be normalized to compensate for a variance of the accumulated result.  
         [0116]     The DCT  413  outputs feature vectors by performing a discrete-cosine-transform on the M vectors. Other features can be added to the feature vectors output from the DCT  413 . An example of the feature can be an attenuating slope obtained from an event duration or an approximated power function of an event.  
         [0117]     The classifier  42  determines whether a desired impact sound is detected by comparing the feature vectors output from the DCT  413  and templates output from the template pool  16 . Here, the template pool  16  stores statistical models of target events and a threshold for detection. The classifier  42  outputs a result of whether the input signal is a target impact sound by calculating similarities between the feature vectors and the templates and determining whether the calculated similarities are larger than the threshold for detection. A statistical classifier, such as a Gaussian mixture model, an N-nearest neighbor method, and a neural network, can be used as the classifier  42 .  
         [0118]     The present invention may be embodied in a general-purpose computer by implementing computer readable code from a medium, e.g., a computer-readable medium, including but not limited to storage media such as magnetic storage media (ROMs, RAMs, floppy disks, magnetic tapes, etc.), optically readable media (CD-ROMs, DVDs, etc.), and carrier waves (e.g., transmission over the internet). The present invention may also be embodied as a medium having a computer-readable code embodied therein for causing a number of computer systems connected via a network to effect distributed processing. And the functional programs, codes and code segments for embodying the present invention may be easily deducted by programmers in the art which the present invention belongs to.  
         [0119]     As described above, according to the present invention, a desired impact sound among impact sounds generated from the surroundings, for example, an impact sound of an object, a sound when a pane of glass is broken, a gunshot, or a footstep, can be discriminated. Therefore, the present invention can be applied to a security system and used to diagnose a defect of a structure on the basis of an acoustic diagnosis.  
         [0120]     While embodiments of the present invention have been described based on the assumption that input video data was variable length coded with reference to embodiments thereof, it will be understood by those skilled in the art that fixed length coding of the input video data may be embodied from the spirit and scope of the invention. Embodiments should be considered in descriptive sense only and not for purposes of limitation.  
         [0121]     Thus, although a few embodiments of the present invention have been shown and described, it would be appreciated by those skilled in the art that changes may be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the claims and their equivalents.