Estimation device, estimation method, and storage medium

Abstract

The invention relates to an estimation device, an estimation method, and a storage medium, which can robustly estimate the arrival direction of a sound source at a lower calculation cost. An estimation device according to an embodiment includes a conversion unit, a spatial correlation calculation unit, a spatial correlation filter unit, and a direction estimation unit. The conversion unit acquires a frequency spectrum by performing time-frequency conversion on acoustic signals of a plurality of channels. The spatial correlation calculation unit calculates a spatial correlation matrix on the basis of the frequency spectrum. The spatial correlation filter unit calculates a spatial correlation filter on the basis of the spatial correlation matrix. The direction estimation unit estimates general direction information on the basis of the partial elements included in the spatial correlation filter.

Description

Technical Field

[0001] Embodiments of the present invention relate to an estimation device, an estimation method, and a storage medium. Background Art

[0002] Conventionally, there is a known method of frequency-converting an acoustic signal input from a plurality of microphones and performing beamforming based on a time-frequency conversion signal after the frequency conversion using a spatial correlation filter based on target sound source direction information indicating the direction of the target sound source included in the sound signal.

[0003] However, in the prior art, it is difficult to robustly estimate the arrival direction of the sound source at a lower computational cost. Summary of the invention

[0004] The estimation device of the embodiment includes a conversion unit, a spatial correlation calculation unit, a spatial correlation filter unit, and a direction estimation unit. The conversion unit obtains a frequency spectrum by performing time-frequency conversion on the sound signals of multiple channels. The spatial correlation calculation unit calculates a spatial correlation matrix based on the frequency spectrum. The spatial correlation filter unit calculates a spatial correlation filter based on the spatial correlation matrix. The direction estimation unit estimates generalized direction information based on some elements included in the spatial correlation filter.

[0005] According to the above-mentioned estimation device, the arrival direction of the sound source can be estimated robustly at a lower calculation cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1 It is a diagram showing an example of arrangement of a plurality of microphones according to the first embodiment.

[0007] Figure 2 It is a diagram showing an example of the functional configuration of the estimation device according to the first embodiment.

[0008] Figure 3A It is a diagram for explaining the phase spectrum.

[0009] Figure 3B It is a diagram for explaining the phase spectrum.

[0010] Figure 4 It is a diagram showing an example of the spatial correlation filter according to the first embodiment and an application example thereof.

[0011] Figure 5 It is a diagram showing an example of the functional configuration of the direction estimating unit according to the first embodiment.

[0012] Fig. 6A This is a diagram showing a general example 1 of estimating direction information according to the first embodiment.

[0013] Figure 6BThis is a diagram showing a general example 2 of estimating direction information according to the first embodiment.

[0014] Figure 7 This is a flowchart showing an example of the estimation method according to the first embodiment.

[0015] Figure 8 It is a diagram showing an example of the functional configuration of the direction estimating unit according to the second embodiment.

[0016] Fig. 9 This is a flowchart showing an example of the estimation method according to the second embodiment.

[0017] Fig.10 It is a diagram showing an example of the hardware configuration of the estimation device according to the first and second embodiments.

[0018] Explanation of symbols

[0019] L, R: microphones; 1: conversion unit; 2: delay unit; 3: spatial correlation calculation unit; 4: spatial correlation calculation unit; 5: spatial correlation filter unit; 6: direction estimation unit; 7: control unit; 10: estimation device; 61: extraction unit; 62: estimation unit; 63: smoothing processing unit; 201: processor; 202: main storage device; 203: auxiliary storage device; 204: display device; 205: input device; 206: communication device; 210: bus. DETAILED DESCRIPTION

[0020] Hereinafter, embodiments of the estimation device, the estimation method, and the program will be described in detail with reference to the drawings.

[0021] (First embodiment)

[0022] If the notification result of the sound recognition mode is controlled, beamforming is not necessary. For example, sometimes it is sufficient to obtain general direction information such as left and right estimation. In addition, strict direction estimation may not be suitable for the purpose when the target sound source is not completely fixed but moves slightly or the distance between microphones changes. On the other hand, direction determination sometimes requires robustness to surrounding noise.

[0023] Hereinafter, an estimation device according to a first embodiment which can reduce calculation cost and enhance noise tolerance will be described.

[0024] First, an example of arrangement of a plurality of microphones according to the first embodiment will be described.

[0025] [Example of multiple microphone configuration]

[0026] Figure 1 It is a diagram showing an example of arrangement of a plurality of microphones L and R according to the first embodiment. Figure 1The example of the in-vehicle use case is shown. The estimation device of the first embodiment estimates the general direction of arrival of the sound source (in Figure 1 The general direction of arrival of the sound source is used, for example, for device control based on a keyword detected by sound recognition.

[0027] Specifically, for example, in in-car entertainment operations such as music, television, and radio (for example, operations based on user voice input such as "music play"), it is possible to consider device control that responds to anyone's voice. Figure 1 In the example of , in the device control based on the in-car entertainment operation, both the sound coming from the right side (i.e., the voice of the user sitting in the front passenger seat) and the sound coming from the left side (i.e., the voice of the driver sitting in the driver's seat) are reflected.

[0028] In addition, for example, in driving assistance control based on a keyword of driving operation (for example, "rear monitor", etc.), it is conceivable to reflect only the voice of the driver in the driver's seat. Figure 1 In the example of driving assistance control, the sound coming from the left side (that is, the voice of the driver sitting in the driver's seat) is reflected, and the sound coming from the right side (that is, the voice of the user sitting in the front passenger seat) is not reflected.

[0029] Furthermore, the estimation device of the first embodiment can estimate not only the general arrival direction of left and right, but also the general arrival direction of up and down, front and back, etc., based on the arrangement of the plurality of microphones. The number of the plurality of microphones (the plurality of channels) is not limited to two, but may be three or more.

[0030] [Example of functional configuration]

[0031] Figure 2 1 is a diagram showing an example of the functional configuration of the estimation device 10 according to the first embodiment. The estimation device 10 according to the first embodiment includes a conversion unit 1, a delay unit 2, a spatial correlation calculation unit 3, a spatial correlation calculation unit 4, a spatial correlation filter unit 5, a direction estimation unit 6, and a control unit 7.

[0032] The conversion unit 1 converts the sound signal input from the microphone L into a frequency spectrum X[0][size] by performing a time-frequency conversion. Here, [0] indicates the number of channels that reflect the input from the microphone L. [size] indicates the number of frequency bins. The time-frequency conversion is calculated by, for example, fast Fourier transform and discrete Fourier transform.

[0033] Similarly, the conversion unit 1 converts the sound signal input from the microphone R into a frequency spectrum X[1][size] by performing time-frequency conversion. Here, [1] indicates the number of channels representing the input from the microphone R.

[0034] In the following, when the frequency spectra X[0][size] and X[1][size] are not distinguished, they are expressed as frequency spectra X[ch][size].

[0035] The components of the frequency spectrum X[ch][size], that is, the components of the acoustic signal after the time-frequency conversion, are expressed by a complex spectrum as shown in the following equation (1).

[0036]

Formula 1

[0037] X[ch][size]=X[ch][size].re+X[ch][size].im···(1)

[0038] Here, re represents the real part, and im represents the imaginary part. This complex spectrum is used, for example, in calculation of a power spectrum (amplitude component for each frequency) based on the following equation (2) and a phase spectrum (phase component for each frequency) based on the following equation (3).

[0039]

Formula 2

[0040]

[0041]

Formula 3

[0042]

[0043] Figure 3A 3B is a diagram for explaining the phase spectrum. The phase spectrum is an indicator showing how much the sound signal is advanced (or delayed) from the reference time. Figure 3A As shown in FIG. 1 , if there is a direction difference in the direction of arrival of the sound from the sound source, the arrival distance to each microphone L and R changes by Δd. Figure 3B As shown, a phase delay Δd occurs in the sound signal reaching the microphone R.

[0044] Return to Figure 2The delay unit 2 is configured to delay the frequency spectrum X[ch][size] for a predetermined time when the frequency spectrum X[ch][size] is received from the conversion unit 1. The delay time can be set so that the duration of the sound to be emphasized, i.e., the command word, is approximately less than the delay time. In the case where the command word is a shorter sentence such as "switch on", it can be assumed that the duration of the command word is less than 1 second. In this case, the delay time is set to 1 second, for example. A delay time of 1 second is equal to 125 (=16000×1 / 128) delay frames. That is, the delay unit 2 buffers 125 frames of the frequency spectrum X[ch][size] and outputs X[ch][size] delayed by 125 frames.

[0045] The spatial correlation calculation unit 3 calculates the spatial correlation matrix of the sound and the noise based on the frequency spectrum X[ch][size]. The spatial correlation matrix is ​​information indicating the spatial correlation between channels and represents the energy distribution in space. Specifically, first, the spatial correlation calculation unit 3 calculates the mixing matrix signal Conv[size][f] based on the sound signal (frequency spectrum X[ch][size]) after time-frequency conversion. As shown in the following formula (4), the mixing matrix Conv[size][f] is calculated in a manner that mixes information of multiple channels.

[0046]

Formula 4

[0047]

[0048] Here, f represents an element number. In addition, there are elements in the mixed matrix signal that contain all information of multiple channels. In the above equation (4), the mixed matrix with element numbers f3 and f4 contains information on phase differences of multiple channels (channels 0 and 1 in the first embodiment).

[0049] Next, the spatial correlation calculation unit 3 calculates the spatial correlation matrices Φs[size][f] and Φn[size][f] from the mixing matrix Conv[size][f] by the following equation (5): Here, s represents a signal, and n represents noise.

[0050]

Formula 5

[0051]

[0052] Similarly, the spatial correlation calculation unit 4 calculates the spatial correlation matrix of the sound and the noise based on the frequency spectrum X[ch][size] received from the delay unit 2. A plurality of spatial correlation matrix signals may be calculated as in the spatial correlation calculation units 3 and 4 of the first embodiment. For example, the spatial correlation matrix at the current moment calculated by the spatial correlation calculation unit 3 may be used as a spatial correlation matrix signal component, and the spatial correlation matrix a certain time ago (predetermined number of frames ago) calculated by the spatial correlation calculation unit 4 may be used as a spatial correlation noise component (for details, refer to Patent Document 3).

[0053] Furthermore, when the calculation of the spatial correlation matrix a certain time ago (predetermined number of frames ago) is not performed, the estimation device 10 may not include the delay unit 2 and the spatial correlation calculation unit 4 .

[0054] The spatial correlation filter unit 5 calculates one or more spatial correlation filters (two spatial correlation filters in the first embodiment) based on the spatial correlation matrices Φs[size][f] and Φn[size][f]. Specifically, first, the spatial correlation filter unit 5 calculates the eigenvalue vector signal based on the spatial correlation matrices Φs[size][f] and Φn[size][f]. When calculating the eigenvalue vector signal, in order to suppress the processing load, the eigenvalue vector may be a two-dimensional eigenvalue vector such as the two-dimensional eigenvalue vector M[size] of the following formula (6).

[0055]

Formula 6

[0056]

[0057] For each element, the eigenvalue vector has an element including all information of a plurality of channels. In the example of the above equation (6), the eigenvalues ​​M of the mixing matrices using the element numbers f3 and f4 both include phase difference information.

[0058] Next, the spatial correlation filter unit 5 calculates spatial correlation filter coefficients based on the eigenvalue vector signal. For example, in the case of a two-dimensional eigenvalue, four element components are generated.

[0059] Figure 4 : is a diagram showing an example of the spatial correlation filter Vector[size] according to the first embodiment and an example of its application. Figure 4 In the example of , the spatial correlation filter coefficients are calculated in such a way as to maximize the signal-to-noise ratio (SNR) of the signal component at the current moment.

[0060] In addition, the general direction difference can be determined based on one element of the spatial correlation filter Vector[size]. The details of the method for determining the general direction difference will be referred to in Figure 5 To be described later.

[0061] Alternatively, a plurality of elements of the spatial correlation filter Vector[size] may be used. For example, one or more elements of the spatial correlation filter Vector[size] may be used for parameter adjustment of general direction estimation.

[0062] Furthermore, by multiplying the spatial correlation filter Vector[size] by each element of the acoustic signal after the time-frequency conversion, the signal at the current time can be emphasized.

[0063] Return to Figure 2 The direction estimation unit 6 estimates general direction information based on partial elements of one or more spatial correlation filters. The general direction information is not strict direction information, but approximate information such as left-right information. For example, the general direction information is a direction represented by an angle of θ or -θ, left or right, front or back, and up or down.

[0064] The generalized directional information is used, for example, to control the result notification of the recognition mode. In addition, by using the spatial correlation filter obtained from the spatial correlation matrix of the sound and the noise, the tolerance to the surrounding noise can be enhanced. In addition, since only the generalized directional information is estimated, the calculation cost can be saved. In addition, the estimation of the generalized directional information is also less likely to be affected by the distance between the microphones and the movement of the target sound source.

[0065] The control unit 7 changes the control based on the voice recognition mode recognized from the sound signal based on the general direction information. For example, the control unit 7 estimates whether the sound is from the driver's seat or the passenger seat based on the general direction information, and changes the control based on the voice recognition mode based on the estimation result.

[0066] Figure 5 1 is a diagram showing an example of the functional configuration of the direction estimating unit 6 according to the first embodiment. The direction estimating unit 6 according to the first embodiment includes an extracting unit 61 and an estimating unit 62 .

[0067] The extraction unit 61 extracts one element of the spatial correlation filter coefficient as a main element. As described above, when the eigenvalue is set to two dimensions, four element components are generated. The extraction unit 61 reduces the four element components to one element. Specifically, the extraction unit 61 extracts an element containing all information of multiple channels (for example, information indicating the phase difference of multiple channels) as a main element. The extraction unit 61 can extract uniquely according to the effect (the estimated accuracy of the generalized directional information) when there are multiple elements containing all information of multiple channels, or can extract or change one element later.

[0068] The extraction unit 61 may of course extract not only one element but also multiple elements simultaneously and calculate their differences, etc. Furthermore, the extraction unit 61 may extract auxiliary elements other than the main elements, and the estimation unit 62 may weight the auxiliary elements in order to correct the local direction information.

[0069] The estimation unit 62 outputs the estimated local direction as generalized direction information based on the main elements, or the main elements and the auxiliary elements extracted by the extraction unit 61. For example, the estimation unit 62 determines the tendency (trend) of a specific frequency within a specific time based on the main elements, estimates the local direction information represented by the tendency, and outputs the generalized direction information based on the local direction information. Specifically, since the main elements of the spatial correlation filter coefficients are information for each frequency, the estimation unit 62 sums and averages the main elements according to the aggregated frequency bands. Then, the estimation unit 62 outputs the local direction information representing the averaged main elements as generalized direction information.

[0070] Fig. 6A 6B are diagrams showing general estimation examples 1 and 2 of direction information according to the first embodiment. Fig. 6A The value of the main component of 6B represents the local direction information obtained based on the partial elements (e.g., 1 element) included in the spatial correlation filter. The local direction information includes the tendency (trend) of a specific frequency within a specific time. Fig. 6A 6B shows an example in which general direction information estimated from the main elements of the spatial correlation filter is a direction of +30 degrees and a direction of -30 degrees.

[0071] The estimation unit 62 estimates the local direction information based on whether the tendency of a specific frequency within a specific time is greater than a predetermined value. Fig. 6A And in the example of 6B, the specified value is 0.

[0072] exist Fig. 6A In the example, the positive value of the main component representing the local direction is greater than the negative value. Therefore, the estimation unit 62 obtains Fig. 6A In the case of local direction information, it is estimated that the sound is from the +30 degree direction (for example, the sound from the passenger seat).

[0073] On the other hand, Figure 6B In the example, the negative value of the main component representing the local direction is greater than the positive value. Therefore, the estimation unit 62 obtains Figure 6B In the case of local direction information, it is estimated that the sound is from the -30 degree direction (for example, the sound from the driver's seat).

[0074] In addition, the estimation unit 62 may also add an arbitrary adjustment value to the local direction information. By adding the adjustment value, the threshold value of the determination can be adjusted. Fig. 6A In the example of 6B, by adjusting the value, it is possible to adjust whether the value of the main component near 0 represents the sound in the +30 degree direction or the sound in the -30 degree direction. By adjusting the value, the estimation accuracy of the general direction information can be further improved.

[0075] In addition, the aggregated frequency band may be the entire frequency band from the low frequency band to the high frequency band, or may stay within the range of the sound frequency band containing more sound components. In addition, the estimation unit 62 may also assign weights to specific frequency components. In addition, the estimation unit 62 may also average the local direction information in the time direction. Through these averages, the local direction can be output as a more general direction.

[0076] [Example of estimation method]

[0077] Figure 7 1 is a flowchart showing an example of the estimation method of the first embodiment. First, the conversion unit 1 receives input of sounds (acoustic signals) of multiple channels (step S1), and performs time-frequency conversion of the input acoustic signals (step S2). Next, the spatial correlation calculation unit 3 calculates the spatial correlation matrix of the sound and the noise based on the frequency spectrum X[ch][size] obtained by the time-frequency conversion (step S3).

[0078] Next, the extraction unit 61 extracts a partial element (for example, one element) of the spatial correlation filter coefficient as a main element (step S4). Next, the estimation unit 62 calculates general direction information based on the partial element included in the spatial correlation filter (step S5).

[0079] Next, the control unit 7 changes the control of the voice recognition mode based on the general direction information (step S6).

[0080] As described above, in the estimation device 10 of the first embodiment, the conversion unit 1 obtains a frequency spectrum by performing time-frequency conversion on the sound signals of multiple channels. The spatial correlation calculation unit 3 calculates a spatial correlation matrix based on the frequency spectrum. The spatial correlation filter unit 5 calculates a spatial correlation filter based on the above spatial correlation matrix. Then, the direction estimation unit 6 estimates general direction information based on some elements included in the above spatial correlation filter.

[0081] As described above, according to the estimation device 10 of the first embodiment, it is possible to robustly estimate the arrival direction of a sound source at a lower calculation cost.

[0082] (Second embodiment)

[0083] Next, a second embodiment will be described. In the description of the second embodiment, the same description as the first embodiment will be omitted, and the differences from the first embodiment will be described.

[0084] [Example of functional configuration]

[0085] Figure 8 1 is a diagram showing an example of the functional configuration of the direction estimating unit 6-2 of the second embodiment. The direction estimating unit 6-2 of the second embodiment includes an extracting unit 61, an estimating unit 62, and a smoothing unit 63. In the second embodiment, the smoothing unit 63 is further added to the configuration of the first embodiment.

[0086] The estimation unit 62 estimates a local direction represented by a tendency (trend) of a specific frequency within a specific time based on the partial elements extracted by the extraction unit 61 .

[0087] The smoothing processing unit 63 adjusts the local direction information obtained by the estimation unit 62, and finally outputs the adjusted local direction information as general direction information. For example, the smoothing processing unit 63 performs smoothing correction on at least one of the time direction and the frequency band direction, and outputs general direction information based on the local direction information after smoothing correction. By performing smoothing correction on the local direction information in at least one of the time direction and the frequency band direction (the time direction, the frequency band direction, or both), the strictness of the estimation result of the direction information can be further reduced. As a result, general direction information that is more resistant to interference factors can be output.

[0088] [Example of estimation method]

[0089] Fig. 9 This is a flowchart showing an example of the estimation method according to the second embodiment. Steps S11 to S14 are the same as steps S1 to S4 in the first embodiment, and thus their description is omitted.

[0090] The estimating unit 62 estimates a local direction including a trend (tendency) of a specific frequency within a specific time based on the partial elements extracted by the extracting unit 61 (step S15 ).

[0091] Next, the smoothing processing unit 63 smoothes the local direction obtained by the estimating unit 62 and calculates general direction information (step S16 ).

[0092] Step S17 is the same as step S6 in the first embodiment, and therefore its description is omitted.

[0093] Finally, an example of the hardware configuration of the estimation device 10 according to the first and second embodiments will be described.

[0094] [Hardware configuration example]

[0095] Fig.10 2 is a diagram showing an example of the hardware configuration of the estimation device 10 according to the first and second embodiments. The estimation device 10 according to the first and second embodiments includes a processor 201, a main storage device 202, an auxiliary storage device 203, a display device 204, an input device 205, and a communication device 206. The processor 201, the main storage device 202, the auxiliary storage device 203, the display device 204, the input device 205, and the communication device 206 are connected via a bus 210.

[0096] In addition, the estimation device 10 may not include a part of the above-mentioned configuration. For example, when the estimation device 10 can use the input function and display function of an external device, the estimation device 10 may not include the display device 204 and the input device 205 .

[0097] The processor 201 executes a program read from the auxiliary storage device 203 to the main storage device 202. The main storage device 202 is a memory such as a ROM and a RAM. The auxiliary storage device 203 is a HDD (Hard Disk Drive) or a memory card.

[0098] The display device 204 is, for example, a liquid crystal display, etc. The input device 205 is an interface for operating the estimation device 10. The display device 204 and the input device 205 may also be implemented by a touch panel having a display function and an input function, etc. The communication device 206 is an interface for communicating with other devices.

[0099] For example, the program executed by the estimation device 10 is recorded in an installable or executable file on a computer-readable storage medium such as a memory card, hard disk, CD-RW, CD-ROM, CD-R, DVD-RAM, and DVD-R, and provided as a computer program product.

[0100] Furthermore, for example, a configuration may be adopted in which the program executed by the estimation device 10 is stored in a computer connected to a network such as the Internet and provided by being downloaded via the network.

[0101] In addition, for example, the program executed by the estimation device 10 may be provided via a network such as the Internet without being downloaded. Specifically, the estimation process may be performed using a so-called ASP (Application Service Provider) type server that implements the processing function only by executing instructions and obtaining results without transmitting the program from the server computer.

[0102] Furthermore, for example, the program of the estimation device 10 may be installed in advance in a ROM or the like and provided.

[0103] The program executed by the estimation device 10 is a module structure including the functions that can be realized by the program in the above-mentioned functional structure. Each of these functions is, as actual hardware, loaded into the main storage device 202 by the processor 201 reading the program from the storage medium and executing it. That is, the above-mentioned functional blocks are generated on the main storage device 202.

[0104] In addition, part or all of the above functions may be realized by hardware such as IC (Integrated Circuit) instead of software.

[0105] Furthermore, each function may be implemented using a plurality of processors 201 . In this case, each processor 201 may implement one of each function, or may implement two or more of each function.

[0106] Several embodiments of the present invention have been described, but these embodiments are presented as examples and are not intended to limit the scope of the invention. These new embodiments can be implemented in various other ways, and various omissions, substitutions, and changes can be made without departing from the scope of the invention. These embodiments and their variations are included in the scope and purpose of the invention, and are included in the invention described in the scope of the patent claim and the scope equivalent thereto.

Claims

1. An estimation device comprising: a conversion unit that performs time-frequency conversion on the sound signals of the plurality of channels to obtain a frequency spectrum; A spatial correlation calculation unit, which calculates a spatial correlation matrix according to the frequency spectrum; a spatial correlation filter unit that calculates a spatial correlation filter based on the spatial correlation matrix; and The direction estimating unit estimates general direction information based on some elements included in the spatial correlation filter.

2. The estimation device according to claim 1, wherein: The direction estimating unit includes: an extracting unit that extracts a main element including information indicating the phase difference of the plurality of channels from the spatial correlation filter; and The estimating unit specifies a tendency of a specific frequency within a specific time period based on the main elements, estimates local direction information represented by the tendency, and outputs the general direction information based on the local direction information.

3. The estimation device according to claim 1, wherein: The direction estimating unit includes: an extracting unit that extracts a main element including information indicating the phase difference of the plurality of channels from the spatial correlation filter; an estimating unit that determines a tendency of a specific frequency within a specific time based on the main elements, and estimates local direction information represented by the tendency; and The smoothing processing unit performs smoothing correction on the local direction information in at least one of a time direction and a frequency band direction, and outputs the general direction information based on the local direction information after the smoothing correction.

4. The estimation device according to claim 2 or 3, wherein: The estimating unit estimates the local direction information based on whether the tendency of the specific frequency within the specific time is greater than a predetermined value.

5. The estimation device according to claim 4, wherein: The estimating unit adjusts the predetermined value by increasing an adjustment value for estimating accuracy of the generalized direction information.

6. The estimation device according to any one of claims 1 to 3, wherein: The above-mentioned generalized direction information indicates any one of the direction indicated by the angle of +θ or −θ, left or right, front or back, and up or down.

7. The estimation device according to any one of claims 1 to 3, wherein: The estimation device further includes a control unit configured to change control based on a voice recognition pattern recognized from the acoustic signal based on the general direction information.

8. A presumption method comprising: The estimating device performs time-frequency conversion on the sound signals of the multiple channels to obtain a frequency spectrum; The estimating device calculates a spatial correlation matrix based on the frequency spectrum; The estimating device calculates a spatial correlation filter based on the spatial correlation matrix; as well as The estimating means is a step of estimating general direction information based on partial elements included in the spatial correlation filter.

9. A storage medium storing a program, wherein: The above program enables the computer to perform the following functions: a conversion unit that performs time-frequency conversion on the sound signals of the plurality of channels to obtain a frequency spectrum; A spatial correlation calculation unit, which calculates a spatial correlation matrix according to the frequency spectrum; A spatial correlation filter unit, which calculates a spatial correlation filter according to the spatial correlation matrix; as well as The direction estimating unit estimates general direction information based on some elements included in the spatial correlation filter.

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