Patent Publication Number: US-9418676-B2

Title: Audio signal processor, method, and program for suppressing noise components from input audio signals

Description:
TECHNICAL FIELD 
     The present invention relates to an audio signal processor, a method, and a program applicable to, for example, communications hardware or communications software that handle audio signals such as telephone calls and teleconferences. 
     BACKGROUND ART 
     Technology known as a voice switch, technology known as a Wiener filter, and the like, are examples of noise suppression technology (see Japanese Patent Application Laid-Open (JP-A) 2006-333215 (Patent Document 1), and Japanese National-Phase Publication 2010-532879 (Patent Document 2)). 
     A voice switch is technology in which segments (target-sound segments) spoken by a speaker are detected in an input signal using a target-sound segment detection function, any target-sound segments are output unprocessed, and the amplitude is attenuated for any non-target-sound segments. For example, as illustrated in  FIG. 12 , when an input signal input is received, determination is made as to whether or not the input signal input is a target-sound segment (step S 51 ), a gain VS_GAIN is set to 1.0 if the input signal input is a target-sound segment (step S 52 ), and the gain VS_GAIN is set to a freely chosen positive value α less than 1.0 if the input signal input is a non-target-sound segment (step S 53 ). The product of the input signal input and the gain VS_GAIN is then obtained as an output signal output (step S 54 ). 
     Applying this voice switch technology to audio communications equipment such as a teleconference device or a mobile telephone enables non-target-sound segments (noise) to be suppressed and a desired target-sound to be extracted, thereby enabling an improvement in speech sound quality. 
     The non-target-sound can be divided into “interfering-sounds” that are human voices not belonging to the speaker, and “background noise” such as office noise or road noise. Although target-sound segments can be accurately determined using ordinary target-sound segment detection functions when the non-target-sound segments are background noise alone, erroneous determination occurs when interfering-sounds are superimposed on background noise, due to the target-sound segment detection function also designating the interfering-sound as target-sound. As a result, interfering-sounds cannot be suppressed by such voice switches, and sufficient speech sound quality is not attained. 
     This issue is improved by switching a feature value referenced by a target-sound segment detection section from variation in the input signal level employed hitherto, to coherence. Put simply, coherence is a feature value signifying the arrival direction of an input signal. Consider use of a mobile telephone; the speaker&#39;s voice (the target-sound) arrives from the front face, and interfering-sounds have a strong tendency to arrive from faces other than the front face, enabling target-sound to be distinguished from interfering-sounds, something that was not hitherto possible, by observing the arrival direction. 
       FIG. 13  is a block diagram illustrating a configuration of a voice switch when coherence is employed by a target-sound detection function. 
     A pair of microphones m_ 1 , and m_ 2  respectively acquire input signals s 1 ( n ) and s 2 ( n ) through an AD converter, omitted from illustration. Note that n is an index indicating the input sequence of the samples, and is expressed as a positive integer. In the present specification, the lower the value of n, the older the input sample, and the greater the value, the newer the input sample. 
     An FFT section  10  acquires input signal series s 1 ( n ) and s 2 ( n ) from the microphones m_ 1  and m_ 2 , and performs a fast Fourier transform (or a discrete Fourier transform) on the input signals s 1  and s 2 . This thereby enables the input signals s 1  and s 2  to be expressed in the frequency domain. When performing fast Fourier transform, analysis frames FRAME  1  (K) and FRAME  2  (K) are formed from a specific number N of samples from the input signals s 1 ( n ) and s 2 ( n ), and then applied. An example of configuring the analysis frames FRAME  1  (K) from the input signal s 1 ( n ) is represented by Equation (1) below, and similar applies to the analysis frames FRAME  1  (K). 
     
       
         
           
             
               
                 
                   
                       
                   
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     Note that K is an index indicating a sequence number for frames, and represents a positive integer. In the present specification, the lower the value of K, the older the analysis frame, and the greater the value, the newer the analysis frame. In the explanation of operation that follows, the index that indicates the latest analysis frame, this being the analysis target, is K unless specifically stated otherwise. 
     The FFT section  10  performs transformation into frequency domain signals X 1  (f, K), X 2  (f, K) by performing a fast Fourier transform on each analysis frame, and the obtained frequency domain signals X 1  (f, K) and X 2  (f, K) are provided to a corresponding first directionality forming section  11 , and second direction directionality forming section  12  respectively. Note that f is an index indicating the frequency. Moreover, X 1  (f, K) is not a single value, and is composed from plural spectral components of frequencies f 1  to fm as expressed by Equation (2). Similar applies to X 2  (f, K), and to B 1  (f, K) and B 2  (f, K), described later.
 
 X 1( f,K )=[( f 1, K ),( f 2, K ), . . . ,( fm,K )]  (2)
 
     In the first directionality forming section  11 , a signal B 1  (f, K) having strong directionality in a specific direction is formed from the frequency domain signals X 1  (f, K) and X 2  (f, K). In the second direction directionality forming section  12 , a signal B 2  (f, K) having strong directionality in a specific direction (different from that of the specific direction mentioned previously) is formed from the frequency domain signals X 1  (f, K) and X 2  (f, K). An existing method may be applied as the method of forming the signals B 1  (f, K), B 2  (f, K) having strong directionality in a specific direction. For example, Equation (3) may be applied to form B 1  (f, K) having strong left-direction directionality, and Equation (4) may be applied to form B 2  (f, K) having strong right-direction directionality. In Equation (3) and Equation (4), the frame index K has no effect on the computation and is therefore omitted. 
                     B   ⁢           ⁢   1   ⁢     (   f   )       =       x   ⁢           ⁢   2   ⁢     (   f   )       -     X   ⁢           ⁢   1   ⁢     (   f   )     ×     exp   ⁡     [       -       ⅈ2π   ⁢           ⁢   fS     N       ⁢   τ     ]                   (   3   )                 B   ⁢           ⁢   2   ⁢     (   f   )       =       x   ⁢           ⁢   1   ⁢     (   f   )       -     X   ⁢           ⁢   2   ⁢     (   f   )     ×     exp   ⁡     [       -       ⅈ2π   ⁢           ⁢   fS     N       ⁢   τ     ]                   (   4   )               
Wherein:
         S: sampling frequency   N: FFT analysis frame length   τ: Difference in sound wave arrival time between microphones   i: imaginary unit   f: frequency       

     The significance of these equations is explained using  FIG. 14A ,  FIG. 14B ,  FIG. 15A , and  FIG. 15B , using Equation (3) as an example. Consider a sound wave arriving from a direction θ indicated in  FIG. 14A  picked up by a pair of microphones m_ 1  and m_ 2  positioned a distance  1  apart. In such an event, a difference arises in time until the sound wave arrives at the microphones m_ 1  and m_ 2 . For a sound path difference d, this arrival time difference τ is d=1×sin θ, thus giving Equation (5), wherein c is the speed of sound.
 
τ=1×sin θ/ c   (5)
 
     A signal s 1  (t−τ), from the input signal s 1  ( n ) delayed by τ, is identical to the input signal s 2  ( t ). A signal y (t) taking the difference between these signals=s 2  ( t )−s 1  ( t −τ), is accordingly a signal in which sound arriving from the direction θ is eliminated. As a result, the microphone array m_ 1  and m_ 2  have directionality as illustrated in  FIG. 14B . 
     Although a time domain computation is described above, performing the computation in the frequency domain can be said to be equivalent. The equations in such a case are Equation (3) and Equation (4) above. Next, consider as an example changing the arrival direction θ by ±90°. Namely, the directional signal B 1  ( f ) from the first directionality forming section  11  has strong directionality in the right-direction as illustrated in  FIG. 15A , and the directional signal B 2  ( f ) from the first directionality forming section  12  has strong directionality in the left-direction as illustrated in  FIG. 15A . 
     The coherence COH is obtained for the directional signals B 1  ( f ) and B 2  ( f ), obtained as described above, by performing a calculation according to Equation (6) and Equation (7) using a coherence calculation section  13 . In Equation (6), B 2  ( f )* is the complex conjugate of B 2  ( f ). 
     
       
         
           
             
               
                 
                   
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     In a target-sound segment detection section  14 , the coherence COH is compared with a target-sound segment determination threshold value Θ, determination as a target-sound segment is made if the coherence COH is greater than the threshold value Θ, otherwise determination as a non-target-sound segment is made, and the determination results VAD_RES (K) are formed. 
     A brief description follows regarding the reasoning behind detecting target-sound segments using the magnitude of the coherence. The concept of coherence can also be referred to as the correlation between a signal arriving from the right and a signal arriving from the left (Equation (6) above computes correlations for given frequency components, and Equation (7) calculates the average correlation value for all frequency components). It is therefore possible to say that the two directional signals B 1  and B 2  have little correlation with each other when the small coherence COH is small, and, conversely, have high correlation with each other when the coherence COH is large. Input signals having little correlation are sometimes cases in which the input arrival direction is offset greatly to either of the right or left, and sometimes non-offset noise-like signals that clearly have little regularity. Thus it can be said that a segment in which the coherence COH is small is an interfering-sound segment or a background noise segment (a non-target-sound segment). It can also be said that the input signal has arrived from the front face when there is large coherence COH, due to there being no offset in the arrival direction. It is assumed that target-sound will arrive from the front face, meaning that large coherence COH can be said to signify target-sound segments. 
     A gain controller  15  sets a gain VS_GAIN for target-sound segments to 1.0, and sets a gain VS_GAIN for non-target-sound segments (interfering-sounds, background noise) to a freely selected positive value α less than 1.0. A voice switch gain multiplication section  16  obtains a post-voice switch signal y (n) by multiplying the obtained gain VS_GAIN by an input signal s 1  ( n ). 
     SUMMARY OF INVENTION 
     Technical Problem 
     Although the coherence COH is a large value overall when the arrival direction is approach from the front face, the coherence COH value gets smaller as the arrival direction is offset to the side.  FIG. 16  illustrates changes in the coherence COH when the sound arrival direction is an approach from the front face (solid line), when the sound arrival direction is from the side (dotted line), and when the arrival direction is from an intermediate point between the front face and the side (dashed line). The vertical axis indicates the coherence COH, and the horizontal axis indicates time (the analysis frame k). 
     As illustrated in  FIG. 16 , the coherence COH has a characteristic of the value range thereof changing greatly according to the arrival direction. However, hitherto there has been an issue of erroneous determination arising since the target-sound segment determination threshold value Θ is a fixed value irrespective of the arrival direction. 
     For example, if the threshold value Θ is large, when the coherence COH is not a particularly large value even though it is a target-sound segment, such as segments in which the sound rises or consonant sections, the target-sound segment is erroneously determined as a non-target-sound segment. Target-sound components are accordingly attenuated by the voice switch processing, resulting in unnatural sound qualities, such as irregular interruptions. 
     If the threshold value Θ is set to a small value, the coherence of the interfering-sound may exceed the threshold value Θ when an interfering-sound arrives from an arrival direction approaching from the front face, and non-target-sound segments may be erroneously determined as target-sound segments. Accordingly, non-target-sound components are not attenuated and sufficient elimination performance becomes unobtainable. In addition, the rate of erroneous determinations increases when the device user is in an environment where the arrival direction of interfering-sounds changes with time. 
     As described above, since the target-sound segment determination threshold value 0 is a fixed value, there is the issue that the voice switching processing is sometimes not operated on desired segments, and the voice switch processing is sometimes operated on non-desired segments, thus lowering the sound quality. 
     An audio signal processing device, method, or program that improves sound quality by appropriately operating a voice switch is therefore desired. 
     Solution to Problem 
     A first aspect of the present invention is an audio signal processing device that suppresses noise components from input audio signals. The audio signal processing device includes (1) a first directionality forming section that by performing delay-subtraction processing on an input audio signal forms a first directional signal imparted with a directionality characteristic having a null in a first specific direction, (2) a second directionality forming section that by performing delay-subtraction processing on the input audio signal forms a second directional signal imparted with a directionality characteristic having a null in a second specific direction different from the first specific direction, (3) a coherence computation section that obtains a coherence using the first and second directional signals, (4) a target-sound segment detection section that by comparing the coherence with a first determination threshold value determines whether the input audio signal is a segment of a target-sound arriving from a target direction, or a non-target-sound segment other than the target-sound segment, (5) a target-sound segment determination threshold value controller that based on the coherence detects an interfering-sound segment from among non-target-sound segments including both the interfering-sound segment and a background noise segment, that obtains an interfering-sound average coherence value representing an average coherence value in the interfering-sound segment, and that controls the first determination threshold value based on the interfering-sound average coherence value, (6) a gain controller that sets a voice switch gain according to the determination result of the target-sound segment detection section, and (7) a voice switch gain multiplication section that multiplies the input audio signal by the voice switch gain obtained by the gain controller. 
     A second aspect of the present invention is an audio signal processing method that suppresses noise components from input audio signals. The audio signal processing method includes (1) by a first directionality forming section, forming a first directional signal imparted with a directionality characteristic having a null in a first specific direction by performing delay-subtraction processing on an input audio signal, (2) by a second directionality forming section, forming a second directional signal imparted with a directionality characteristic having a null in a second specific direction different from the first specific direction by performing delay-subtraction processing on the input audio signal, (3) by a coherence computation section, calculating a coherence using the first and second directional signals, (4) by a target-sound segment detection section, comparing the coherence with a first determination threshold value determines whether the input audio signal is a segment of target-sound arriving from a target direction, or a non-target-sound segment other than the target-sound segment, (5) by a target-sound segment determination threshold value controller, detecting based on the coherence an interfering-sound segment from among non-target-sound segments including both the interfering-sound segment and a background noise segment, obtaining an interfering-sound average coherence value representing an average coherence value in the interfering-sound segment, and controlling the first determination threshold value based on the interfering-sound average coherence value, (6) by a gain controller, setting a voice switch gain according to the determination result of the target-sound segment detection section; and (7) by a voice switch gain multiplication section, multiplying the input audio signal by the voice switch gain obtained by the gain controller. 
     An audio signal processing program of a third aspect of the present invention causes a computer to function as (1) a first directionality forming section that by performing delay-subtraction processing on an input audio signal forms a first directional signal imparted with a directionality characteristic having a null in a first specific direction, (2) a second directionality forming section that by performing delay-subtraction processing on the input audio signal forms a second directional signal imparted with a directionality characteristic having a null in a second specific direction different from the first specific direction, (3) a coherence computation section that obtains a coherence using the first and second directional signals, (4) a target-sound segment detection section that by comparing the coherence with a first determination threshold value determines whether the input audio signal is a segment of a target-sound arriving from a target direction, or a non-target-sound segment other than the target-sound segment, (5) a target-sound segment determination threshold value controller that based on the coherence detects an interfering-sound segment from among non-target-sound segments including both the interfering-sound segment and a background noise segment, that obtains an interfering-sound average coherence value representing an average coherence value in the interfering-sound segment, and that controls the first determination threshold value based on the interfering-sound average coherence value, (6) a gain controller that sets a voice switch gain according to the determination result of the target-sound segment detection section; and (7) a voice switch gain multiplication section that multiplies the input audio signal by the voice switch gain obtained by the gain controller. 
     Advantageous Effects of Invention 
     The present invention controls a determination threshold value applied to determine whether there is a target-sound segment or not, thereby causing voice switching to operate appropriately, and enabling sound quality to be improved. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a block diagram illustrating a configuration of an audio signal processing device according to a first exemplary embodiment. 
         FIG. 2  is a block diagram illustrating a detailed configuration of a target-sound segment determination threshold value controller of an audio signal processing device of the first exemplary embodiment. 
         FIG. 3  is an explanatory diagram of storage content of a target-sound segment determination threshold value controller of an audio signal processing device of the first exemplary embodiment. 
         FIG. 4  is a flowchart illustrating operation of a target-sound segment determination threshold value controller of an audio signal processing device according to the first exemplary embodiment. 
         FIG. 5  is a flowchart illustrating operation of a target-sound segment determination threshold value controller of an audio signal processing device according to a second exemplary embodiment. 
         FIG. 6  is a block diagram illustrating a detailed configuration of a target-sound segment determination threshold value controller of an audio signal processing device according to a third exemplary embodiment. 
         FIG. 7  is a flowchart illustrating operation of a target-sound segment determination threshold value controller of an audio signal processing device according to the third exemplary embodiment. 
         FIG. 8  is a block diagram illustrating a configuration of a modified exemplary embodiment in which frequency attenuation subtraction is employed in combination with the first exemplary embodiment. 
         FIG. 9  is an explanatory diagram illustrating properties of a directional signal from the third directionality forming section of  FIG. 8 . 
         FIG. 10  is a block diagram illustrating a configuration of a modified exemplary embodiment in which a coherence filter is employed in combination with the first exemplary embodiment. 
         FIG. 11  is a block diagram illustrating a configuration of a modified exemplary embodiment in which a Wiener filter is employed in combination with the first exemplary embodiment. 
         FIG. 12  is a flowchart illustrating a flow of voice switch processing. 
         FIG. 13  is a block diagram illustrating a configuration of a voice switch when coherence is employed in a target-sound detection function. 
         FIG. 14A  is an explanatory diagram illustrating properties of a directional signal from the directionality forming section of  FIG. 13 . 
         FIG. 14B  is an explanatory diagram illustrating properties of a directional signal from the directionality forming section of  FIG. 13 . 
         FIG. 15A  is an explanatory diagram illustrating properties of directionality in the directionality forming section of  FIG. 13 . 
         FIG. 15B  is an explanatory diagram illustrating properties of directionality in the directionality forming section of  FIG. 13 . 
         FIG. 16  is an explanatory diagram illustrating coherence variation differing according to arrival direction of sound. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     A. First Exemplary Embodiment 
     Explanation follows regarding an audio signal processing device, method, and program of a first exemplary embodiment of the invention, with reference to the drawings. The first exemplary embodiment is able to appropriately set a determination threshold value Θ for a target-sound segment according to an arrival direction of an interfering-sound, based on the coherence COH. 
     A-1. Configuration of the First Exemplary Embodiment 
       FIG. 1  is a block diagram illustrating a configuration of an audio signal processing device according to the first exemplary embodiment. Corresponding sections similar to those in  FIG. 13  are illustrated appended with the same reference numeral. Except for the pair of microphones m_ 1  and m_ 2 , the audio signal processing device may be implemented by software executed by a CPU (an audio signal processing program); in terms of function however, the audio signal processing device can be represented by  FIG. 1 . 
     In  FIG. 1 , an audio signal processing device  1  according to a first exemplary embodiment includes a target-sound segment determination threshold value controller  20 , in addition to microphones m_ 1 , m_ 2 , an FFT section  10 , a first directionality forming section  11 , a second directionality forming section  12 , a coherence computation section  13 , a target-sound segment detection section  14 , a gain controller  15 , and a voice switch gain multiplication section  16  similar to technology hitherto. 
     Since the microphones m_ 1 , m_ 2 , the FFT section  10 , the first directionality forming section  11 , the second direction directionality forming section  12 , the coherence computation section  13 , the gain controller  15 , and the voice switch gain multiplication section  16  carry out functions similar to those of technology hitherto, explanation of such functionality is omitted. 
     Based on a calculated coherence COH (K), the coherence computation section  13  of the target-sound segment determination threshold value controller  20  sets a target-sound segment determination threshold value Θ (K) according to the arrival direction at that time, in the target-sound segment detection section  14 . 
     The target-sound segment detection section  14  of the first exemplary embodiment compares the coherence COH (K) with the target-sound segment determination threshold value Θ (K) set by variable control, makes determination as a target-sound segment if the coherence COH (K) is greater than the threshold value Θ (K), and otherwise makes determination as a non-target-sound segment, and forms determination results VAD_RES (K). 
       FIG. 2  is a block diagram illustrating detailed configuration of the target-sound segment determination threshold value controller  20 . 
     The target-sound segment determination threshold value controller  20  includes a coherence reception section  21 , a non-target-sound segment detection section  22 , a non-target-sound coherence averaging processing section  23 , a difference computation section  24 , an interfering-sound segment detection section  25 , an interfering-sound coherence averaging processing section  26 , a target-sound segment determination threshold value referencing section  27 , a storage section  28 , and a target-sound segment determination threshold value transmission section  29 . 
     The coherence reception section  21  acquires the coherence COH (K) computed by the coherence computation section  13 . 
     The non-target-sound segment detection section  22  makes an approximate determination of whether or not a segment of coherence COH (K) is a non-target-sound segment. This approximate determination is a comparison of the coherence COH (K) against a fixed threshold value Ψ. Determination as a non-target-sound segment is made when the coherence COH (K) is smaller than the fixed threshold value Ψ. The determination threshold value Ψ is a value different from the target-sound segment determination threshold value Θ controlled with time using the target-sound segment detection section  14 , and a fixed value is applied as the determination threshold value Ψ since it is sufficient to detect non-target-sound segments to a rough approximation with no need for high precision, unlike the determination threshold value Θ. 
     In the non-target-sound coherence averaging processing section  23 , if the approximate determination result is a target-sound segment, the value AVE_COH (K−1) of the immediately previous analysis frame K−1 may be applied, as is, as an average value of coherence AVE_COH (K) for the non-target-sound segment. If the approximate determination result is a non-target-sound segment, the average value AVE_COH (K) of the coherence in the non-target-sound segment may be derived by Equation (8). Note that the computation method for the average coherence value AVE_COH (K) is not limited to Equation (8), and another computation method, such as simple averaging of a specific number of sample values, may be applied. In Equation (8), δ is a value within a range of 0.0&lt;δ&lt;1.0.
 
AVE_COH( K )=δ×COH( K )+(1−δ)×AVE_COH( K− 1)  (8)
 
     A weighted sum of the coherence COH (K) for the input audio of the current frame segment (the K th  analysis frame, counting from the point in time when operation started) and the average value AVE_COH (K−1) obtained for the one previous frame segment may be calculated as the average value using Equation (8), and the contribution to the average value made by instantaneous coherence values COH (K) may be adjusted via the magnitude of the value δ. Setting δ to a small value close to 0 enables variation caused by instantaneous values to be suppressed since the contribution of instantaneous values to the average is lessened. Setting δ to a value close to 1 enables the effect of averaging processing to be weakened since the contribution of instantaneous values is increased. An appropriate value of δ may be set based on these viewpoints. 
     The difference computation section  24  calculates the absolute value DIFF (K) of the difference between the instantaneous value COH (K) and the average value AVE_COH (K) of the coherence, as expressed by Equation (9).
 
DIFF( K )=|COH( K )−AVE_COH( K )|  (9)
 
     The interfering-sound segment detection section  25  compares the value DIFF (K) with an interfering-sound segment determination threshold value Φ, and makes determination as an interfering-sound segment if the value DIFF (K) is the interfering-sound segment determination threshold value Φ or greater, and otherwise makes determination as a segment other than an interfering-sound segment (a background noise segment). The determination method utilizes a property of the difference from the average becoming large due to the value of the coherence (the instantaneous coherence) in interfering-sound segments being greater than in background noise segments. 
     If the determination result is not an interfering-sound segment, the interfering-sound coherence averaging processing section  26  applies the value DIST_COH (K−1) of the immediately previous analysis frame K−1, as is, as the average value DIST_COH (K) of the coherence in interfering-sound segments, and if the determination result is an interfering-sound segment, the interfering-sound coherence averaging processing section  26  derives the average value DIST_COH (K) of the coherence in the interfering-sound segment according to Equation (10), which is similar to Equation (8). The calculation equation for the coherence average value DIST_COH (K) is not limited to Equation (10), and another computation method, such as simple averaging of a specific number of sample values, may be applied therefor. In Equation (10), ζ is a value within a range of 0.0&lt;ζ&lt;1.0.
 
DIST_COH( K )=ζ×COH( K )+(1−ζ)×DIST_COH( K− 1)  (10)
 
     The storage section  28  stores correspondence data of the range of the average value DIST_COH of the coherence in interfering-sound segments against the target-sound segment determination threshold value Θ. The storage section  28  may, for example, be configured in a conversion table format as illustrated in  FIG. 3 . The example of  FIG. 3  shows a value of Θ  1  as the target-sound segment determination threshold value Θ corresponded against the average value DIST_COH of the coherence in interfering-sound segments when in a range A&lt;DIST_COH≦B, a value of Θ 2 as the target-sound segment determination threshold value Θ corresponded against the average value DIST_COH of the coherence in interfering-sound segments when in a range B&lt;DIST_COH≦C, and a value of Θ 3 as the target-sound segment determination threshold value Θ corresponded against the average value DIST_COH of the coherence in interfering-sound segments when in a range C&lt;DIST_COH≦D. The relationship Θ 1&lt;Θ 2&lt;Θ 3 holds here. 
     The target-sound segment determination threshold value referencing section  27  searches the storage section  28  for the average value DIST_COH range to which the average value DIST_COH (K) obtained by the interfering-sound coherence averaging processing section  26  belongs, and acquires the value of the target-sound segment determination threshold value Θ corresponding to the found range of the average value DIST_COH. 
     As the target-sound segment determination threshold value Θ (K) applied for the current analysis frame K, the target-sound segment determination threshold value transmission section  29  transmits the value of the target-sound segment determination threshold value Θ acquired by the target-sound segment determination threshold value referencing section  27  to the target-sound segment detection section  14 . 
     A-2. Operation of the First Exemplary Embodiment 
     Explanation next follows regarding operation of the audio signal processing device  1  of the first exemplary embodiment with reference to the drawings, explaining in sequence about the overall operation, and detailed operations in the target-sound segment determination threshold value controller  20 . 
     The input signals s 1 ( n ), s 2 ( n ) from the pair of microphones m_ 1  and m_ 2  are respectively transformed by the FFT section  10  from time domain into frequency domain signals X 1  (f, K), X 2  (f, K), and then directional signals B 1  (f, K), B 2  (f, K) are generated with specific directions as nulls thereof by the first and second directionality forming sections  11  and  12 , respectively. Then, the directional signals B 1  (f, K) and B 2  (f, K) are applied in the coherence computation section  13 , calculations of Equation (6) Equation (7) are executed, and the coherence COH (K) is computed. 
     In the target-sound segment determination threshold value controller  20 , a target-sound segment determination threshold value Θ (K) according to the arrival direction of a non-target-sound (in particular, an interfering-sound) at that time, is derived based on the coherence COH (K) and provided to the target-sound segment detection section  14 . Then, in the target-sound segment detection section  14 , determination as a target-sound segment or not is performed by comparing the coherence COH (K) with the target-sound segment determination threshold value Θ (K), and the gain VS_GAIN is set by the gain controller  15  that received the determination result VAD_RES (K). Then, in the voice switch gain multiplication section  16 , the input signal s 1  ( n ) is multiplied by the gain VS_GAIN set by the gain controller  15 , and the output signal y (n) is obtained. 
     Explanation next follows regarding operation of the target-sound segment determination threshold value controller  20 .  FIG. 4  is a flowchart illustrating the operation of the target-sound segment determination threshold value controller  20 . 
     The coherence COH (K) calculated by the coherence computation section  13  and input to the target-sound segment determination threshold value controller  20  is acquired by the coherence reception section  21  (step S 101 ). The acquired coherence COH (K) is compared with the fixed threshold value Ψ in the non-target-sound coherence averaging processing section  23 , and determination as a non-target-sound segment or not is performed (step S 102 ). If the determination result is a target-sound segment (if coherence COH (K)≧Ψ), the average value AVE_COH (k−1) of the immediately previous analysis frame K−1 is applied by the non-target-sound coherence averaging processing section  23 , as is, as the average value AVE_COH (K) of the coherence in the non-target-sound segment (step S 103 ). If the determination result is a non-target-sound segment (if coherence COH (K)&lt;Ψ), the average value AVE_COH (K) of the coherence in the non-target-sound segment is computed according to Equation (8) (step S 104 ). 
     Next, the absolute value DIFF (K) of the difference between the instantaneous coherence value COH (K) and the average value AVE_COH (K) is computed by the difference computation section  24  according to Equation (9) (step S 105 ). Then, in the interfering-sound segment detection section  25 , the value DIFF (K) obtained by the calculation is compared with the interfering-sound segment determination threshold value D, and determination as an interfering-sound segment is made if the value DIFF (K) is the interfering-sound segment determination threshold value 1 or greater, otherwise determination is made as a segment other than an interfering-sound segment (a background noise segment) (step S 106 ). In the interfering-sound coherence averaging processing section  26 , the value DIST_COH (K−1) in the immediately previous analysis frame K−1 is applied, as is, as the average value DIST_COH (K) of the coherence in the interfering-sound segment if the determination result is not an interfering-sound segment (step S 108 ), and the average value DIST_COH (K) of the coherence in the interfering-sound segment is computed according to Equation (10) if the determination result is an interfering-sound segment (step S 107 ). 
     Search processing is performed on the storage section  28  by the target-sound segment determination threshold value referencing section  27  using the average value DIST_COH (K) of the interfering-sound segments obtained as described above as a key. The value of the target-sound segment determination threshold value Θ corresponding to the average value range to which the key that is the average value DIST_COH (K) belongs is acquired and transmitted by the target-sound segment determination threshold value transmission section  29  to the target-sound segment detection section  14  as the target-sound segment determination threshold value Θ (K) applied to the current analysis frame K (step S 109 ). The parameter K is then incremented by 1 (step S 110 ), and processing returns to processing by the coherence reception section  21 . 
     Explanation next follows regarding obtaining an optimized target-sound segment determination threshold value Θ (K) by the above processing. 
     As illustrated in  FIG. 16 , the coherence COH has a value range that differs according to the arrival direction, enabling the average value of the coherence to be corresponded against the arrival direction. This means that the arrival direction can be estimated by obtaining the average value of the coherence. Since the voice switch processing allows target-sound to pass through unprocessed, and performs processing to attenuate interfering-sounds, detection of the arrival direction of interfering-sounds is desired. Interfering-sound segments are therefore detected by the interfering-sound segment detection section  25 , and average value DIST_COH (K) of the coherence in non-target-sound segments is computed by the interfering-sound coherence averaging processing section  26 . 
     A-3. Advantageous Effects of the First Exemplary Embodiment 
     According to the first exemplary embodiment, the target-sound segment determination threshold value Θ is controlled according to the arrival direction of a non-target-sound (in particular, an interfering-sound), enabling determination precision to be increased for target-sound segments and non-target-sound segments, and can help to prevent sound quality from deteriorating by mistaken operation of voice switch processing other than on segments where desired. 
     An improvement in speech sound quality can therefore be anticipated when applying the audio signal processing device, method, or program of the first exemplary embodiment to a communications device, such as a teleconference device or mobile telephone. 
     B. Second Exemplary Embodiment 
     Explanation next follows regarding an audio signal processing device, a method, and a program of a second exemplary embodiment according to the present invention, with reference to the drawings. 
     In rare cases, the interfering-sound segment detection method of the first exemplary embodiment sometimes makes an interfering-sound segment detection despite the segment not being an interfering-sound segment, and the second exemplary embodiment is configured to help prevent such erroneous detection. In the first exemplary embodiment, the detection method for the interfering-sound segment, for example a background noise segment immediately following transition from a target-sound segment to a non-target-sound segment, sometimes makes an interfering-sound segment detection despite the segment not being an interfering-sound segment. Errors also arise in the setting of the target-sound segment determination threshold value Θ (K) if the average value DIST_COH of the coherence is updated by such erroneous detections. 
     An audio signal processing device  1 A according to the second exemplary embodiment, and an overall configuration thereof, may be illustrated by  FIG. 1  used to explain the first exemplary embodiment. A target-sound segment determination threshold value controller  20 A according to the second exemplary embodiment, and an internal configuration thereof, may be illustrated by  FIG. 2  used to explain the first exemplary embodiment. 
     In the case of the second exemplary embodiment, the condition for the interfering-sound segment detection section  25  to make determination as an interfering-sound segment is different from that of the first exemplary embodiment. 
     The determination condition in the first exemplary embodiment was “the value DIFF (K) is the interfering-sound segment determination threshold value Φ or greater”; however, the determination condition in the second exemplary embodiment is “the value DIFF (K) is the interfering-sound segment determination threshold value Φ or greater, and the coherence COH (K) is greater than the average coherence value AVE_COH (K) in a non-target-sound segment”. 
     Explanation follows regarding the reasoning behind this modification to the determination condition. Although, in background noise segments, the coherence has a small value and small variation, the value is large in interfering-sound segments, albeit not as large as for target-sound segments, and the variation is large. Accordingly, there is often a big difference between the instantaneous coherence value COH (K) in an interfering-sound segment and the average value AVE_COH (K). This characteristic is taken into account by the condition of the value DIFF (K) being the interfering-sound segment determination threshold value Θ or greater. However, with just this condition, erroneous determinations arise as described above. The cause is that, although the average value AVE_COH (K) of the coherence of non-target-sound segments is a large value in background noise segments immediately following target-sound segments due to residual effects of the coherence in the immediately previous interfering-sound segment, the difference between the instantaneous value and the average value increases due to the instantaneous coherence value COH (K) being a small value in the background noise segments, and the value DIFF (K) that is the absolute value thereof is therefore also made large. Thus, in the second exemplary embodiment, erroneous determination is prevented by adding the condition “COH (K)&gt;AVE_COH (K)” of the instantaneous coherence value of an interfering-sound segment being greater than the average value. 
       FIG. 5  is a flowchart illustrating operation of the target-sound segment determination threshold value controller  20 A of the second exemplary embodiment, and corresponding steps to those in  FIG. 4  of the first exemplary embodiment are appended with the same reference numerals. 
     As described above, in the second exemplary embodiment, a step S 106 A that is the determination step for interfering-sound segments is modified from “DIFF (K)≧Φ” of step S 106  of the first exemplary embodiment to “value DIFF (K)≧Φ, and COH (K)&gt;AVE_COH (K)”, and other processing is similar to that of the first exemplary embodiment. 
     As described above, according to the second exemplary embodiment, erroneous updates to the average coherence value of the interfering-sound segments can be prevented even in the case of, for example, a background noise segment immediately following the end of a target-sound segment, enabling the level of determination precision of target-sound segments to be further improved since the target-sound segment determination threshold value can be set to an appropriate value. 
     An improvement in speech sound quality can therefore be anticipated when the audio signal processing device, method, or program of the second exemplary embodiment is applied to a communications device, such as a teleconference device or mobile telephone. 
     C. Third Exemplary Embodiment 
     Explanation next follows regarding an audio signal processing device, a method, and a program of a third exemplary embodiment according to the present invention, with reference to the drawings. 
     The coherence COH in non-target-sound segments suddenly increases immediately after switching from a background noise segment to an interfering-sound segment. However, since the average coherence value DIST_COH (K) of the interfering-sound segment is an average value, variation does not immediately appear in the average coherence value DIST_COH (K) even when the coherence COH suddenly increases. Namely, the coherence average value DIST_COH (K) tracks sudden increases in the coherence COH poorly. As a result, the average coherence value DIST_COH (K) of the interfering-sound segments is not accurate immediately after switching from a background noise segment to an interfering-sound segment. The third exemplary embodiment takes such points into consideration, and is configured to give an appropriate average coherence value DIST_COH (K) of the interfering-sound segments, employed in setting the target-sound segment determination threshold value, even immediately after switching from a background noise segment to an interfering-sound segment. Specifically, the third exemplary embodiment is configured to control the time constant ζ in Equation (10) immediately after switching from a background noise segment to an interfering-sound segment. 
     C-1. Configuration of the Third Exemplary Embodiment 
     An audio signal processing device  1 B according to the third exemplary embodiment, and an overall configuration thereof, may be illustrated by  FIG. 1  employed to explain the first exemplary embodiment. 
       FIG. 6  is a block diagram illustrating a detailed configuration of a target-sound segment determination threshold value control section  20 B of the third exemplary embodiment, and parts corresponding to similar parts in  FIG. 2  of the second exemplary embodiment are appended with the same reference numerals. 
     The target-sound segment determination threshold value control section  20 B of the third exemplary embodiment includes an average parameter controller  30  and an interfering-sound segment determination result continuation section  31 , in addition to the coherence reception section  21 , the non-target-sound segment detection section  22 , the non-target-sound coherence averaging processing section  23 , the difference computation section  24 , the interfering-sound segment detection section  25 , the interfering-sound coherence averaging processing section  26 , the target-sound segment determination threshold value referencing section  27 , the storage section  28 , and the target-sound segment determination threshold value transmission section  29  of the second exemplary embodiment. The average parameter controller  30  is interposed between the interfering-sound segment detection section  25  and the interfering-sound coherence averaging processing section  26 , and the interfering-sound segment determination result continuation section  31  is interposed between the target-sound segment determination threshold value referencing section  27  and the target-sound segment determination threshold value transmission section  29 . 
     The average parameter controller  30  receives the determination result of the interfering-sound segment detection section  25 , and stores 0 in determination result storing variable var_new if the determination result is not an interfering-sound segment, and stores 1 in the determination result storing variable var_new if the determination result is an interfering-sound segment. This is then compared with the determination result storing variable var_old of the immediately previous frame. If the determination result storing variable var_new of the current frame exceeds the determination result storing variable var_old of the immediately previous frame, the average parameter controller  30  treats this as a transition from a background noise segment to an interfering-sound segment, and sets a large fixed value near to 1.0 (larger than an initial value, described later) as the average parameter ζ employed in the computation of the average coherence value for the interfering-sound segment. If the determination result storing variable var_new of the current frame does not exceed the determination result storing variable var_old of the immediately previous frame, the average parameter controller  30  sets the initial value as the average parameter ζ employed in the calculation of the average coherence value of the interfering-sound segment. 
     The interfering-sound coherence averaging processing section  26  of the third exemplary embodiment applies the average parameter ζ set by the average parameter controller  30 , and performs the computation of Equation (10) above. 
     The interfering-sound segment determination result continuation section  31  overwrites the determination result storing variable var_old of the immediately previous frame with the determination result storing variable var_new of the current frame when the setting processing of the average parameter ζ for the current frame has ended, and then continues the processing on the next frame. 
     C-2. Operation of the Third Exemplary Embodiment 
     Explanation next follows regarding detailed operation of the target-sound segment determination threshold value control section  20 B of the audio signal processing device  1 B of the third exemplary embodiment, with reference to the drawings. The overall operation of the audio signal processing device  1 B of the third exemplary embodiment is similar to the overall operation of the audio signal processing device  1  of the first exemplary embodiment, and explanation thereof is omitted. 
       FIG. 7  is a flowchart illustrating operation of the target-sound segment determination threshold value control section  20 B of the third exemplary embodiment, and corresponding steps to those in  FIG. 5  of the second exemplary embodiment are appended with the same reference numerals. 
     The coherence COH (K) that was calculated by the coherence computation section  13  and input to the target-sound segment determination threshold value control section  20 B, is acquired by the coherence reception section  21  (step S 101 ), and is compared with the fixed threshold value Ψ in the non-target-sound coherence averaging processing section  23 , and determination is performed as to whether it is a non-target-sound segment (step S 102 ). If the determination result is a target-sound segment (if COH (K)≧Ψ), the average value AVE_COH (K−1) of the immediately previous analysis frame K−1 is applied by the non-target-sound coherence averaging processing section  23 , as is, as the average value AVE_COH (K) of coherence in the non-target-sound segment (step S 103 ). If the determination result is a non-target-sound segment (if COH (K)&lt;Ψ), the average value AVE_COH (K) of coherence is computed for the non-target-sound segment according to Equation (8) (step S 104 ). 
     Next, the absolute value DIFF (K) of the difference between the instantaneous coherence value COH (K) and the average value AVE_COH (K) is computed by the difference computation section  24  according to Equation (9) (step S 105 ). Then, in the interfering-sound segment detection section  25 , determination is made as to whether or not the interfering-sound segment condition “the value DIFF (K) being the interfering-sound segment determination threshold value Φ or greater, and the coherence COH (K) being greater than the average value AVE_COH (K) of the coherence of the non-target-sound segment”, is satisfied (step S 106 A). 
     In the average parameter controller  30 , 0 is stored in the determination result storing variable var_new of the current frame when this condition is not satisfied (when not an interfering-sound segment) (step S 150 ). Then, in the interfering-sound coherence averaging processing section  26 , the value DIST_COH (K−1) of the immediately previous analysis frame K−1 is applied, as is, as the average value DIST_COH (K) of the coherence of the interfering-sound segments (step S 108 ). 
     In the average parameter controller  30 , 1 is stored in the determination result storing variable var_new of the current frame when the interfering-sound segment condition is satisfied (when being an interfering-sound segment) (step S 151 ), and then the determination result storing variable var_new of the current frame is compared with the determination result storing variable var_old of the immediately previous frame (step S 152 ). When the determination result storing variable var_new of the current frame exceeds the determination result storing variable var_old of the immediately previous frame, a large fixed value close to 1.0 is set by the average parameter controller  30  as the average parameter ζ employed in the computation of the average coherence value of the interfering-sound segments (step S 154 ). When the determination result storing variable var_new of the current frame does not exceed the determination result storing variable var_old of the immediately previous frame, the initial value is set by the average parameter controller  30  as the average parameter ζ employed in the computation of the average coherence value of the interfering-sound segments (step S 153 ). After this setting is made, the average coherence value DIST_COH (K) of the interfering-sound segments is computed by the interfering-sound coherence averaging processing section  26  according to Equation (10) (step S 107 ). 
     Search processing in the storage section  28  is executed by the target-sound segment determination threshold value referencing section  27  using the average value DIST_COH (K) of interfering-sound segments obtained as described above as a key. The value of the target-sound segment determination threshold value Θ corresponding to the average value range to which the key that is the average value DIST_COH (K) belongs is acquired and transmitted by the target-sound segment determination threshold value transmission section  29  to the target-sound segment detection section  14  as the target-sound segment determination threshold value Θ (K) applied to the current analysis frame K (step S 109 ). 
     The interfering-sound segment determination result continuation section  31  then overwrites the determination result storing variable var_old of the immediately previous frame with the determination result storing variable var_new of the current frame (step S 155 ). The parameter K is then incremented by 1 (step S 110 ), and processing returns to processing by the coherence reception section  21 . 
     The value stored in the determination result storing variable var_new of the current frame and the determination result storing variable var_old of the immediately previous frame are not limited to 1 and 0. When different values are stored, the determination condition of step S 152  may be modified according to those values 
     Although explanation has been given of cases in which the average parameter ζ is set to a large value close to 1.0 for just 1 frame immediately after a switch from a background noise segment to an interfering-sound segment, the average parameter ζ may be set to a large value close to 1.0 continuously for an exact specific number of frames by counting a number of frames from a frame immediately after the switch. For example, control may be performed such that the average parameter ζ is set to a large value close to 1.0 continuously for 5 frames immediately after the switch, and is restored to the initial value for frames thereafter. 
     C-3. Advantageous Effects of the Third Exemplary Embodiment 
     According to the third exemplary embodiment, a switch from a background noise segment to an interfering-sound segment is detected, and a parameter in the computation method of the average coherence of the interfering-sound segment is controlled when the switch is made. This thereby enables delay in tracking of the average coherence to be suppressed to a minimum limit, such that the target-sound segment determination threshold value can be set more appropriately. 
     An improvement in speech sound quality can therefore be anticipated when the audio signal processing device, method, or program of the third exemplary embodiment is applied to a communications device, such as a teleconference device or mobile telephone. 
     D. Other Exemplary Embodiments 
     Although various modified exemplary embodiments have been mentioned in the explanations of each of the exemplary embodiments above, more examples of modified exemplary embodiments can be given, such as the examples below. 
     Although the average coherence value DIST_COH (K) in the interfering-sound segments is updated in Equation (10) based on the coherence COH (K) of the current frame, depending on the characteristics of noise, sometimes a detection method that somewhat relaxes the effect of instantaneous coherence COH (K) caused by random noise characteristics is more accurate. In such cases, the average coherence value DIST_COH (K) of the interfering-sound segments may be updated based on the average coherence value AVE_COH (K) of the non-target-sound segments. Equation (11) below is a calculation equation for such a modified exemplary embodiment.
 
DIST_COH( K )=ζ×AVE_COH( K )+(1−ζ)×DIST_COH( K− 1)  (11)
 
     Although examples have been given for each of the above exemplary embodiments in which the target-sound segment detection section establishes the threshold value to be employed based on the average coherence value of the interfering-sound segments, the parameters employed in deciding the threshold value are not limited to the average coherence value. It is sufficient that the parameters are able to reflect trends in the coherence of the immediately previous time period to some extent. For example, the threshold value may be set based on a peak coherence obtained by applying a known peak holding technique. Moreover, the threshold value may be set based on a statistical quantity such as a coherence distribution or standard deviation. 
     Although an examples have been given for each of the above exemplary embodiments, in which the non-target-sound coherence averaging processing section  23  uses a single fixed threshold value Ψ to choose which of two update methods to apply for the average coherence value, three or more methods may be prepared as the update methods for the average coherence value, and a number of threshold values matching the number of update methods may be set. For example, plural update methods may be prepared with mutually different δ values for Equation (8). 
     One out of a known spectral subtraction, coherence filter, or Weiner filter may be employed in combination with each of the above exemplary embodiments, or two or all thereof may be employed in combination. Combined employment enables greater noise suppression performance to be realized. A simple description follows of the configuration and operation when spectral subtraction, a coherence filter, or a Weiner filter is employed in combination with the first exemplary embodiment. 
       FIG. 8  is a block diagram illustrating a configuration of a modified exemplary embodiment in which spectral subtraction is employed in combination with the first exemplary embodiment, with corresponding steps to those in  FIG. 1  of the first exemplary embodiment appended with the same reference numerals. 
     In  FIG. 8 , in addition to the configuration of the first exemplary embodiment, an audio signal processing device  1 C according to this modified exemplary embodiment includes a spectral subtraction section  40 . The spectral subtraction section  40  includes a third directionality forming section  41 , a subtraction section  42 , and an IFFT section  43 . 
     “Spectral subtraction” here refers to a means of performing noise suppression by subtracting non-target-sound signal components from the input signal. 
     The third directionality forming section  41  is provided with the two input signals X 1  (f, K) and X 2  (f, K) from the FFT section  10  that have been transformed to the frequency domain. By executing Equation (12), the third directionality forming section  41  forms a third directional signal B 3  (f, K) conforming to a directionality characteristic having a null at a front face, as illustrated in  FIG. 9 , and the third directional signal B 3  (f, K) acting as a noise signal is provided to the subtraction section  42  as input for subtraction. One of the signals transformed to the frequency domain, the input signal X 1  (f, K), is provided to the subtraction section  42  as input for subtraction from, and, as expressed by Equation (13), the subtraction section  42  obtains a frequency subtracted processed signal D (f, K) by subtracting the third directional signal B 3  (f, K) from the input signal X 1  (f, K). The IFFT section  43  transforms the frequency subtracted processed signal D (f, K) to a time domain signal q (n), and provides the time domain signal q (n) to the voice switch gain multiplication section  16 .
 
 B 3( f,K )= X 1( f,K )− X 2( f,K )  (12)
 
 D ( f,K )= X 1( f,K )− B 3( f,K )  (13)
 
       FIG. 10  is a block diagram illustrating a configuration of a modified exemplary embodiment, of a coherence filter employed in combination with the first exemplary embodiment, and corresponding steps to those in  FIG. 1  of the first exemplary embodiment are appended with the same reference numeral. 
     In  FIG. 10 , an audio signal processing device  1 D according to this modified exemplary embodiment includes a coherence filter calculation section  50  in addition to the configuration of the first exemplary embodiment. The coherence filter calculation section  50  includes a coherence filter coefficient multiplication section  51  and an IFFT section  52 . 
     A “coherence filter” is a noise elimination technique, in which signal components having an offset arrival direction are suppressed by multiplying each frequency of the input signal by a coef (f, K) obtained using Equation (6) above. 
     As expressed by Equation (14), the coherence filter coefficient multiplication section  51  multiplies the input signal X (f, K) by a coefficient coef (f, K) obtained by a computation process of the coherence computation section  13 , obtaining a post-noise-suppression signal D (f, K). The IFFT section  52  transforms the post-noise-suppression signal D (f, K) into a time domain signal q (n), and provides the time domain signal q (n) to the voice switch gain multiplication section  16 .
 
 D ( f,K )= X 1( f,K )×coef( f,K )  (14)
 
       FIG. 11  is a block diagram illustrating a configuration of a modified exemplary embodiment, in which a Wiener filter is employed in combination with the first exemplary embodiment, and corresponding portions to those in  FIG. 1  of the first exemplary embodiment are appended with the same reference numerals. 
     In  FIG. 11 , in addition to the configuration of the first exemplary embodiment, an audio signal processing device  1 E according to this modified exemplary embodiment includes a Wiener filter computation section  60 . The Wiener filter computation section  60  includes a Wiener filter coefficient calculation section  61 , a Wiener filter coefficient multiplication section  62 , and an IFFT section  63 . 
     As described in Patent Document 2, a “Wiener filter” here is technology that estimates noise characteristics per frequency from a signal of a noise segment, and eliminates the noise by multiplying by obtained coefficients. 
     The Wiener filter coefficient calculation section  61  references the detection result of the target-sound segment detection section  14 , and estimates a Wiener filter coefficient wf_coef (f, K) if the detection result is a non-target-sound segment (see the computation equation “Equation (3)” of Patent Document 2). However, a Wiener filter coefficient is not estimated if the detection result is a target-sound segment. The Wiener filter coefficient multiplication section  62  obtains a post-noise-suppression signal D (f, K) by multiplying the input signal X 1  (f, K) by the Wiener filter coefficient wf_coef (f, K), as expressed by Equation (15). The IFFT section  63  transforms the post-noise-suppression signal D (f, K) into a time domain signal q (n), and provides the time domain signal q (n) to the voice switch gain multiplication section  16 .
 
 D ( f,K )= X 1( f,K )× wf _coef( f,K )  (15)
 
     In the spectral subtraction processing above, an example is given in which voice switching processing is performed after performing coherence filtering processing or Wiener filter processing; however, these processing sequences may be reversed. 
     In each of the exemplary embodiments above, where possible processing in which a frequency domain signal was processed may be configured as processing on a time domain signal, and conversely, where possible processing in which a time domain signal was processed, may be configured as processing on a frequency domain signal. 
     Although examples are given in each of the exemplary embodiments above of cases in which immediate processing is performed on a signal picked up by a pair of microphones, the audio signal that is the target of processing of the present invention is not limited thereto. For example, the present invention can also be applied in cases in which processing is performed on a pair of audio signals read from a recording medium, and the present invention can also be applied in cases in which processing is performed on a pair of audio signals transmitted from counterpart devices. 
     The entire contents of the disclosure of Japanese Patent Application No. 2012-221537 is incorporated by reference in the present specification. 
     All cited documents, patent applications and technical standards mentioned in the present specification are incorporated by reference in the present specification to the same extent as if the individual cited document, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.