Signal processing device, method, and program

Abstract

A signal processing device 2 is for causing a wearable device, which reproduces sound without completely shielding an external ear hole, to perform active noise control. The signal processing device 2 comprises at least one of: (1) a virtual microphone position noise signal estimation unit 22 that obtains an estimated value of a noise signal at a virtual microphone position by performing at least one of scaling by gp and delaying by τp samples for an estimated value of a noise signal at an error microphone position; (2) an error microphone position secondary sound source signal estimation unit 27; and (3) a virtual microphone position secondary sound source signal estimation unit 28.

Description

Signal processing device, method and program

[0001] The disclosed technology relates to active noise control.

[0002] Open-ear hearable devices have a large amount of sound leakage because they do not block the ears. For this reason, the open-ear hearable device of Non-Patent Document 1 employs technology to reduce sound leakage using directional speakers or near-field speakers (see, for example, Non-Patent Document 1).

[0003] NTT sonority, Inc., “nwm Technology,” [online], [searched January 17, 2024], Internet <URL: https: / / www.nwm.global / technology>

[0004] In order to improve the noise reduction performance of active noise control, which adaptively generates a signal that is out of phase with the surrounding noise at the location where noise is to be reduced, it is important to place the error microphone as close as possible to the location where noise is to be reduced.

[0005] However, with open-ear hearable devices that do not block the ears, it is difficult to place the error microphone near the ear canal where you want to mute noise. Also, if the error microphone is placed in a position where the influence of the negative phase wave is greater than that of the positive phase wave, the noise will be mute at the error microphone position, but conversely, the noise may be amplified at the desired mute position, resulting in no mute effect.

[0006] The disclosed technology aims to provide a signal processing device, method, and program that can obtain a noise reduction effect even when the error microphone is placed in a position where the influence of the negative phase wave is greater than the influence of the positive phase wave.

[0007] One aspect of the disclosed technology is a signal processing device for causing a wearable device that reproduces sound without completely blocking an external auditory canal to perform active noise control, wherein a virtual microphone realized based on an error microphone for performing active noise control is located between the entrance of the external auditory canal of a user wearing the wearable device and the eardrum, and the signal processing device includes: (1) a signal processing unit for processing a virtual microphone based on an error microphone for performing active noise control; p is a predetermined value, and τ pis a predetermined value, and the estimated noise signal at the error microphone position obtained from the error signal at the error microphone position is expressed as g p times and τ p a virtual microphone position noise signal estimator for obtaining an estimated value of the noise signal at the virtual microphone position by performing at least one of sample delay and sample delay processing; and (2) g ms is a predetermined value, and τ ms is a predetermined value, and the secondary sound source signal is processed using a filter that simulates the characteristics between the secondary sound source and the error microphone, and the resulting signal is ms times and τ ms an error microphone position secondary sound source signal estimator for obtaining an estimate of a secondary sound source signal at the error microphone position by performing at least one of sample delay and sample delay processing; and (3)g vs is a predetermined value, and τ vs is a predetermined value, and the secondary sound source signal is processed using a filter that simulates the characteristics between the secondary sound source and the virtual microphone, and the resulting signal is calculated using g vs times and τ vs and a virtual microphone position secondary sound source signal estimating unit that performs at least one of sample delay and sample delay processing to obtain an estimated value of the secondary sound source signal at the virtual microphone position.

[0008] According to the disclosed technology, even when the error microphone is placed at a position where the influence of the negative phase wave is greater than the influence of the positive phase wave, a noise reduction effect can be obtained.

[0009] FIG. 1 is a diagram for explaining an example of a wearable device. FIG. 2 is a diagram for explaining an embodiment. FIG. 3 is a diagram for explaining an embodiment. FIG. 4 is a diagram showing an example of the functional configuration of a signal processing device. FIG. 5 is a diagram showing an example of a processing procedure of a signal processing method. FIG. 6 is a diagram for explaining a modified example of the signal processing device. FIG. 7 is a diagram for explaining a modified example of the signal processing device. FIG. 8 is a diagram showing an example of noise reduction performance of active noise control of an embodiment. (A) is a diagram showing a case where a speaker is located in front of a dummy head. (B) is a diagram showing a case where a speaker is located on the left side of a dummy head. (C) is a diagram showing a case where a speaker is located behind a dummy head. (A) is a diagram for explaining the position of a microphone. (B) is a diagram for explaining the position of a microphone. (A) is a diagram showing an impulse response when a speaker is located in front of a dummy head and the microphone is located at A1. (B) is a diagram showing an impulse response when a speaker is located in front of a dummy head and the microphone is located at A2. (C) is a diagram showing the impulse response when the speaker is located in front of the dummy head and the microphone is positioned at A3. (D) is a diagram showing the impulse response when the speaker is located in front of the dummy head and the microphone is positioned at A4. (E) is a diagram showing the impulse response when the speaker is located in front of the dummy head and the microphone is positioned at A5. (A) is a diagram showing the impulse response when the speaker is located on the left side of the dummy head and the microphone is positioned at A1. (B) is a diagram showing the impulse response when the speaker is located on the left side of the dummy head and the microphone is positioned at A2. (C) is a diagram showing the impulse response when the speaker is located on the left side of the dummy head and the microphone is positioned at A3. (D) is a diagram showing the impulse response when the speaker is located on the left side of the dummy head and the microphone is positioned at A4. (E) is a diagram showing the impulse response when the speaker is on the left side of the dummy head and the microphone is at position A5. (A) is a diagram showing the impulse response when the speaker is behind the dummy head and the microphone is at position A1.(B) is a diagram showing an impulse response when the speaker is behind the dummy head and the microphone is positioned at A2. (C) is a diagram showing an impulse response when the speaker is behind the dummy head and the microphone is positioned at A3. (D) is a diagram showing an impulse response when the speaker is behind the dummy head and the microphone is positioned at A4. (E) is a diagram showing an impulse response when the speaker is behind the dummy head and the microphone is positioned at A5. (A) is a histogram of time delay. (B) is a histogram of average power of low frequencies of the second-order characteristic. Figure 15 is a diagram showing an example of the functional configuration of a computer.

[0010] Hereinafter, embodiments of the disclosed technology will be described with reference to the drawings. Note that components having the same functions in the drawings are given the same reference numerals, and redundant description will be omitted.

[0011] [Wearable Device] Examples of wearable devices that reproduce sound without completely blocking the ear canal include open-ear earphones, shoulder speakers, audio glasses, and smart glasses.

[0012] Note that "without completely blocking the external auditory canal" here means that the sound radiating unit is not placed in region R1, which corresponds to the axis passing through the entrance of the ear canal, as shown by the long dashed line in Figure 1. The sound radiating unit may be placed in peripheral region R2, such as the helix and earlobe, as shown by the dashed line in the same figure. An example of a device in which the sound radiating unit is placed in a peripheral region is audio glasses. Furthermore, the sound radiating unit may be placed in region R3, which is around the triangular fossa, antihelic crus, and navicular fossa, as shown by the dashed line in the same figure. An example of a device in which the sound radiating unit is placed in this region is open-ear earphones.

[0013] As shown in Fig. 2, a noise signal reaches the wearable device 1 from a primary sound source S1, in other words, a noise source. The wearable device 1 performs active noise control (ANC) to reduce the noise signal. To achieve this, the active noise control adaptively generates and radiates an anti-phase wave to cancel the noise signal. In this process, the anti-phase wave W1 is adaptively generated so as to minimize the error signal obtained by the error microphone 11.

[0014] In Fig. 2, position P1 is a position where the influence of the negative-phase-sequence wave W1 is greater than that of the positive-phase-sequence wave W2. In other words, a position where the influence of the negative-phase-sequence wave W1 is greater than that of the positive-phase-sequence wave W2 is a position where the negative-phase-sequence wave W1 is dominant. In Fig. 1, the position where sound is to be silenced is position P2.

[0015] The position where the influence of the anti-phase wave is greater than that of the positive phase wave may be determined in a free sound field or with the wearable device attached to the ear. The position where the influence of the anti-phase wave is greater than that of the positive phase wave may be determined taking into account the directivity of each speaker. Furthermore, the position where the influence of the anti-phase wave is greater than that of the positive phase wave may be determined by simulation.

[0016] As mentioned in the background art, if the error microphone 11 is placed at position P1 where the influence of the negative phase wave is greater than that of the positive phase wave, noise will be muted at this error microphone position P1. However, at position P2 where noise muting is desired, noise may be amplified, and no muting effect can be obtained.

[0017] Therefore, active noise control is achieved by using a virtual microphone realized based on the error microphone 11. Specifically, as shown in Fig. 3, the virtual microphone 12 realized based on the error microphone 11 is positioned between the entrance of the ear canal and the eardrum of the user wearing the wearable device 1. In the example of Fig. 3, the virtual microphone 12 realized based on the error microphone 11 is positioned at the entrance of the ear canal. In Fig. 3, H1 indicates a radiation hole for the anti-phase wave, and H2 indicates a radiation hole for the positive phase wave.

[0018] By performing active noise control to minimize the error signal obtained from the virtual microphone, a noise reduction effect can be obtained even if the error microphone is placed in a position where the influence of the negative phase wave is greater than the influence of the positive phase wave.

[0019] The error microphone does not have to be placed in a position where the influence of the negative phase wave is greater than the influence of the positive phase wave.

[0020] As will be described later, any of the feedback method, feedforward method, and hybrid method may be used as the active noise control.

[0021] As will be described later, there may be multiple error microphones 11. That is, the wearable device may further include at least one error microphone. In this case, both the error microphone 11 and the virtual microphone 12 may be used. In this case, active noise control may be performed using not only the error signal obtained from the virtual microphone 12, but also the error signal obtained from the error microphone 11. Also, multiple virtual microphones 12 may be used.

[0022] Furthermore, as will be described later, the number of secondary sound sources may be two or more. In other words, the wearable device may be provided with two or more speakers for outputting secondary sound source signals.

[0023] [Signal Processing Device and Method] An example of a signal processing device 2 and method for performing active noise control will now be described with reference to Figures 4 and 5. In this example, the signal processing device 2 performs feedback-type active noise control.

[0024] The signal processing device 2 is provided in the wearable device 1, for example.

[0025] Of course, the signal processing device 2 may be provided outside the wearable device 1. In this case, the error signal obtained by the error microphone provided in the wearable device 1 is transmitted to the signal processing device 2. The signal processing device 2 performs processing based on the received error signal obtained by the error microphone. In addition, the secondary sound source signal generated by the signal processing device 2 is transmitted to the wearable device 1 and output from the speaker of the wearable device 1.

[0026] As shown in FIG. 4 , the signal processing device 2 includes, for example, an error-microphone-position noise signal estimating unit 21, a virtual-microphone-position noise signal estimating unit 22, a virtual-microphone-position error signal estimating unit 23, a virtual-microphone-position noise signal estimating unit 24, a filter estimating unit 25, a filter processing unit 26, an error-microphone-position secondary sound source signal estimating unit 27, and a virtual-microphone-position secondary sound source signal estimating unit 28.

[0027] The signal processing method is realized, for example, by each component of the signal processing device 2 performing the processes from step S21 to step S28 shown in FIG.

[0028] In addition, the symbol " - "," "^," and "~" should be written directly above the character immediately following them, but due to limitations in text notation, they are written immediately before the character in question. In mathematical formulas, these symbols are written in their proper position, that is, directly above the character. For example, in a sentence, - X" is written in the formula as follows: Each component of the signal processing device 2 will now be described.

[0029] The error microphone position noise signal estimation unit 21 estimates the error signal e at the error microphone position obtained by the error microphone. m (n) and the estimated secondary sound source signal at the error microphone position ^y m (n) is entered.

[0030] The error microphone position noise signal estimation unit 21 estimates the error signal e at the error microphone position obtained by the error microphone. m (n) and the estimated secondary sound source signal at the error microphone position ^y m(n) and (n), the estimated noise signal at the error microphone position is calculated as ~d m (n) is calculated (step S21).

[0031] The estimated noise signal at the error microphone position is ~d. m (n) is output to the virtual microphone position noise signal estimation unit 22.

[0032] The virtual microphone position noise signal estimation unit 22 estimates the noise signal at the error microphone position by the estimated value d m (n) is entered.

[0033] The virtual microphone position noise signal estimation unit 22 estimates the noise signal at the error microphone position ~d m For (n), g p times and τ p By processing at least one of the sample delays, the noise signal estimate ~d at the virtual microphone position is obtained. v (n) is calculated (step S22).

[0034] Estimated noise signal at the virtual microphone position ~d v (n) is output to the virtual microphone position error signal estimation unit 23. In this example, since feedback active noise control is performed, the estimated value of the noise signal at the virtual microphone position ∼d v (n) is output as a noise signal x(n) to the virtual microphone position noise signal estimating unit 24 and the filtering unit 26.

[0035] g p is a predetermined value. p For example, g is a real number greater than 0. p may be a real number greater than 0 and less than or equal to 1.

[0036] τ p is a predetermined value. p is a positive real number greater than or equal to 0. For example, if the speed of sound is 340 m / s and the difference in distance between the error microphone and the virtual microphone relative to the noise source is 34 mm, then τ p It is appropriate to set the number of samples equivalent to 0.1 ms.

[0037] In FIG. 4, the square representing the virtual microphone position noise signal estimation unit 22 is marked with "g p z -τp This description means that the input signal is p Double and τ p This means that the signal is delayed by a sample. However, this description only shows one example of the process. This is the "g" in the box in FIG. 4 and other figures. p z -τp " "g ms z -τms " "g vs z -τvs The same applies to " etc.

[0038] [[Virtual microphone position error signal estimator 23]] The virtual microphone position error signal estimator 23 estimates the noise signal at the virtual microphone position ~d v (n) and the estimated secondary sound source signal at the virtual microphone position ^y v (n) is entered.

[0039] The virtual microphone position error signal estimator 23 estimates the noise signal at the virtual microphone position ~d v (n) and the estimated secondary sound source signal at the virtual microphone position ^y v (n) and (n), the estimated error signal at the virtual microphone position is calculated as ~e v (n) is calculated (step S23).

[0040] Estimated error signal at the virtual microphone position ~e v (n) is output to the filter estimation unit 25 .

[0041] [[Virtual microphone position noise signal estimator 24]] The virtual microphone position noise signal estimator 24 receives the noise signal x(n).

[0042] The virtual microphone position noise signal estimation unit 24 processes the noise signal x(n) using a filter that simulates the characteristics between the secondary sound source and the virtual microphone, and calculates g vs times and τ vsAt least one of the sample delay processes is performed to obtain an estimated value ^x(n) of the noise signal at the virtual microphone position (step S24).

[0043] The estimated value ^x(n) of the noise signal at the virtual microphone position is output to the filter estimation unit 25 .

[0044] g vs is a predetermined value. vs For example, g is a real number greater than 0. vs may be a real number greater than 0 and less than or equal to 2.

[0045] τ vs is a predetermined value. vs is a positive real number greater than or equal to 0. For example, τ vs is the number of samples equivalent to 0.05 ms.

[0046] In addition, " in Figure 4 - S v (z)" indicates a filter that simulates the characteristics between a secondary sound source and a virtual microphone.

[0047] The filter estimation unit 25 estimates the error signal at the virtual microphone position, v (n) and the estimated noise signal value ^x(n) at the virtual microphone position are input.

[0048] The filter estimation unit 25 estimates the error signal at the virtual microphone position ~e v At least (n) is used to estimate a filter for generating a secondary sound source signal for performing active noise control (step S25).

[0049] In this example, the filter estimation unit 25 estimates the error signal at the virtual microphone position, v (n) and the estimated noise signal value ^x(n) at the virtual microphone position are used to estimate a filter for generating a secondary sound source signal for active noise control.

[0050] The filter is estimated using an adaptive algorithm such as LMS, NLMS, RLS, etc. Of course, other suitable adaptive algorithms may also be used.

[0051] The filter is output to the filter processing unit 26 .

[0052] [[Filter Processing Unit 26]] The noise signal x(n) and a filter are input to the filter processing unit 26.

[0053] The filter processing unit 26 generates a secondary sound source signal y(n) using a filter (step S26).

[0054] 4, the box representing the filter processing unit 26 is marked with "W(z)." This marking means that processing is performed using the filter generated by the filter estimation unit 25.

[0055] The secondary sound source signal y(n) is output to an error microphone position secondary sound source signal estimating unit 27 and a virtual microphone position secondary sound source signal estimating unit 28 .

[0056] Furthermore, the secondary sound source signal y(n) is output from the speaker of the wearable device 1. The dashed lines in Fig. 4 represent sound wave interference in an actual acoustic space.

[0057] The secondary sound source signal y(n) output from the speaker of the wearable device 1 is affected by the characteristics between the secondary sound source and the virtual microphone in the actual acoustic space, and then the noise signal d v (n) and is output to the silencing area. v (z)" indicates the characteristics between the secondary sound source and the virtual microphone.

[0058] In addition, the secondary sound source signal y(n) output from the speaker of the wearable device 1 is affected by the characteristics between the secondary sound source and the error microphone in the actual acoustic space, and then the noise signal d m (n). m (z)" indicates the characteristics between the secondary sound source and the error microphone.

[0059] This combined signal is obtained by the error microphone of the wearable device 1, and the error signal e at the error microphone position is m (n). The error signal e at the error microphone position m (n) is output to the error microphone position noise signal estimation unit 21.

[0060] [[Error microphone position secondary sound source signal estimating unit 27]] The error microphone position secondary sound source signal estimating unit 27 receives the secondary sound source signal y(n).

[0061] The error microphone position secondary sound source signal estimation unit 27 processes the secondary sound source signal y(n) using a filter that simulates the characteristics between the secondary sound source and the error microphone, and calculates g ms times and τ ms By processing at least one of the sample delays, the secondary sound source signal estimate ^y m (n) is calculated (step S27).

[0062] The secondary source signal estimate ^y at the error microphone position m (n) is output to the error microphone position noise signal estimation unit 21.

[0063] g ms is a predetermined value. ms For example, g is a real number greater than 0. ms may be a real number greater than 0 and less than or equal to 1.

[0064] τ ms is a predetermined value. ms is a real number. For example, τ ms is the number of samples equivalent to 0.05 ms.

[0065] In addition, " in Figure 4 - S m (z)" indicates a filter that simulates the characteristics between the secondary sound source and the error microphone.

[0066] [[Virtual microphone position secondary sound source signal estimating unit 28]] The virtual microphone position secondary sound source signal estimating unit 28 receives the secondary sound source signal y(n).

[0067] The virtual microphone position secondary sound source signal estimation unit 28 performs processing on the secondary sound source signal y(n) using a filter that simulates the characteristics between the secondary sound source and the virtual microphone, and calculates g vs times and τ vsBy processing at least one of the sample delays, the secondary sound source signal estimate ^y v (n) is calculated (step S28).

[0068] The estimated secondary sound source signal at the virtual microphone position ^y v (n) is output to the virtual microphone position noise signal estimation unit 22.

[0069] g vs is a predetermined value. vs For example, g is a real number greater than 0. vs may be a real number greater than 0 and less than or equal to 2.

[0070] τ vs is a predetermined value. vs is a real number greater than or equal to 0. For example, τ vs is the number of samples equivalent to 0.05 ms.

[0071] In addition, " in Figure 4 - S v (z)" indicates a filter that simulates the characteristics between a secondary sound source and a virtual microphone.

[0072] The processes from step S21 to step S28 are repeated.

[0073] The position of the error microphone is different from the position of the virtual microphone. As a result, for example, the sound pressure of the noise signal at the position of the error microphone may differ from the sound pressure of the noise signal at the position of the virtual microphone. Furthermore, the time at which the noise signal arrives at the position of the error microphone may differ from the time at which the noise position arrives at the position of the virtual microphone. For example, when a noise signal arrives from the left in FIG. 3 , it is assumed that the sound pressure of the noise signal at the position of the error microphone 11 is greater than the sound pressure of the noise signal at the position of the virtual microphone 12, and that the time at which the noise signal arrives at the position of the error microphone 11 is earlier than the time at which the noise position arrives at the position of the virtual microphone 12.

[0074] Here, the signal to be controlled is a low frequency, around 100-1 kHz, and the distance between the error microphone and the virtual microphone is only a few centimeters. Therefore, the wavelength of the signal to be controlled is sufficiently longer than the distance between the error microphone and the virtual microphone, and the phase characteristics can be ignored.

[0075] Therefore, the noise signal at the virtual microphone position is approximated by a real number multiple of the noise signal at the error microphone position and / or a predetermined sample delay. For example, as performed in the virtual microphone position noise signal estimation unit 22, the estimated value of the noise signal at the error microphone position, ∼d m For (n), g p times and τ p By processing at least one of the sample delays, the noise signal estimate ~d at the virtual microphone position is obtained. v (n) is calculated. This will improve the noise reduction effect.

[0076] Furthermore, since the shapes of the pinnae of users are different from one another, the characteristics between the secondary sound source and the error microphone may be a real multiple of the characteristics of the actual acoustic space, and may be delayed by a predetermined number of samples.

[0077] Therefore, for example, as is done in the error microphone position secondary sound source signal estimation unit 27, processing using a filter that simulates the characteristics between the secondary sound source and the error microphone is performed on the secondary sound source signal y(n), and the obtained signal is calculated as g ms times and τ ms By processing at least one of the sample delays, the secondary sound source signal estimate ^y m Find (n).

[0078] Also, for example, as performed in the virtual microphone position secondary sound source signal estimation unit 28, processing using a filter that simulates the characteristics between the secondary sound source and the virtual microphone is performed on the secondary sound source signal y(n), and the obtained signal is calculated using g vs times and τ vs By processing at least one of the sample delays, the secondary sound source signal estimate ^y vAlso, for example, as performed by the virtual microphone position noise signal estimation unit 24, processing is performed on the noise signal x(n) using a filter that simulates the characteristics between the secondary sound source and the virtual microphone, and the obtained signal is calculated using g vs times and τ vs By performing at least one of the sample delay processes, an estimate value ^x(n) of the noise signal at the virtual microphone position is obtained.

[0079] These treatments can reduce the influence of individual differences in ear shape and improve the noise reduction effect.

[0080] Note that these parameters g p ,g ms ,g vs ,τ p ,τ ms ,τ vs The processing using the arithmetic unit is a relatively simple process such as multiplication and delay, and is not a complex convolution process. Therefore, it can be performed relatively quickly and it is expected that the amount of memory used can be reduced.

[0081] The user can specify these parameters g p ,g ms ,g vs ,τ p ,τ ms ,τ vs This setting can be performed using, for example, the input unit 2030 in FIG. 15. Note that these parameters g p ,g ms ,g vs ,τ p ,τ ms ,τ vs A plurality of sets of values ​​for the parameter g may be determined in advance, and the user or the signal processing device 2 may be able to select an appropriate set from the plurality of sets. In this case, the signal processing device 2 may determine the parameter g determined by the selected set. p ,g ms ,g vs ,τ p ,τ ms ,τ vsThe predetermined plurality of sets may be linked to a parameter such as "ear size." In this case, the signal processing device 2 selects a set linked to a parameter that matches the user's "ear size" or a parameter that is closest to the user's "ear size."

[0082] These parameters g p ,g ms ,g vs ,τ p ,τ ms ,τ vs may be estimated in advance using a dummy head. For example, the impulse response h of the primary sound source-virtual microphone measured by placing a microphone at the position of the virtual microphone (for example, the entrance of the ear canal) is p (n) and the impulse response of the primary sound source - error microphone - h p (n) and obtain these impulse responses h p (n), - h p (n) low frequency component lowpass(h p (n)), lowpass( - h p (n)). The cutoff frequency is set to, for example, 1k to 2kHz. Note that a bandpass filter is used to extract lowpass (h p (n)), lowpass( - h p (n)) may be extracted. p is lowpass(h p (n)), lowpass( - h p (n)) is calculated from the cross-correlation function of g p is lowpass(h p (n)), lowpass( - h p (n)) is calculated using the least squares solution for the average value of the amplitude. p It should be noted that the same processing may be performed in the frequency domain instead of the time domain.

[0083] Also, the parameter g vs,τ vs may be determined using the characteristics between the secondary sound source and the virtual microphone of the user wearing the wearable device, which are measured or estimated in advance. vs ,τ vs may be determined using a feature that represents some or all of the characteristics between the secondary sound source and the virtual microphone of the user wearing the wearable device, which have been measured or estimated in advance. The characteristics between the secondary sound source and the virtual microphone of the user wearing the wearable device can be estimated using an existing method such as the method described in Reference 1.

[0084] [Reference 1] Yuki Watanabe, Daisuke Chiba, Shihori Kozuka, Tatsuya Kako, Hiroaki Ito, Kenichi Noguchi, "Individual Analysis of Transfer Characteristics Based on Pinna Shape in Open-Ear Earphones," Proceedings of the Acoustical Society of Japan, September 2023. The signal processing device 2 uses features that represent the characteristics between the secondary sound source and the virtual microphone of the user wearing the wearable device, or some or all of those characteristics, to perform g vs ,τ vs The device may further include a determination unit 212 (shown by a dashed line in FIG. 4) that determines at least one of the above.

[0085] To estimate the characteristics between a secondary sound source and a virtual microphone of a user wearing a wearable device, it is possible to use an acoustic device that includes: a wearable device; a speaker arranged on the concha side of the wearable device; one or more microphones arranged on the wearable device; a measurement unit that collects sound based on a predetermined signal with the microphone; an estimation unit that estimates an HpTF by selecting one HpTF from a plurality of predetermined HpTFs based on information that is correlated with the HpTF contained in the sound signal collected by the measurement unit; and a correction unit that corrects the input signal to the acoustic device using the estimated HpTF.

[0086] An example of a feature that represents part of the characteristics between the secondary sound source of the user wearing the wearable device and the virtual microphone is the average power of the low-frequency band of the spectrum that represents the characteristics between the secondary sound source of the user wearing the wearable device and the virtual microphone. An example of the low-frequency band is 0.2 to 4 kHz. Similarly, the parameter g p ,gms ,τ p ,τ ms The wearable device may also be determined using a feature that represents the characteristics of the user wearing the wearable device, or some or all of those characteristics, which have been measured or estimated in advance.

[0087] (i) The estimated noise signal at the error microphone position is g p times and τ p (ii) performing processing using a filter that simulates the characteristics between the secondary sound source and the error microphone on the secondary sound source signal, and then performing processing using a filter that simulates the characteristics between the secondary sound source and the error microphone on the secondary sound source signal, and ... ms times and τ ms (iii) performing processing using a filter that simulates the characteristics between the secondary sound source and the virtual microphone on the secondary sound source signal and the noise signal, and then performing processing using a filter that simulates the characteristics between the secondary sound source and the virtual microphone on the secondary sound source signal and the noise signal, and ... vs times and τ vs Only some, but not all, of the sample delay and / or processing may be performed.

[0088] That is, for example, the signal processing device may include at least one of a virtual microphone position noise signal estimator 22, a virtual microphone position error signal estimator 23, an error microphone position secondary sound source signal estimator 27, and a virtual microphone position secondary sound source signal estimator 28.

[0089] [Modification] When there is a reproduction signal u(n) to be reproduced by the wearable device, the signal processing device 2 adds the secondary sound source signal y(n) and the reproduction signal u(n). In this case, the secondary sound source signal y(n) after addition is output from the speaker of the wearable device.

[0090] For example, as shown by the two-dot chain line in the example of Fig. 4, the adder 29 may add the reproduction signal u(n) to the secondary sound source signal generated by the filter processing unit 26 to obtain a secondary sound source signal y(n) after addition. In this case, this secondary sound source signal y(n) after addition is output to the error microphone position secondary sound source signal estimation unit 27. Furthermore, this secondary sound source signal y(n) after addition is output from the speaker of the wearable device 1. The signal processing device 2 may include an adder 29 that performs such addition.

[0091] The signal processing device 2 may perform other active noise control methods besides the feedback method, such as a feedforward method and a hybrid method.

[0092] For example, when the signal processing device 2 performs feedforward active noise control, the wearable device 1 is assumed to be equipped with a reference microphone. In this case, as shown in FIG. 6 , a noise signal x(n) at the position of the reference microphone obtained by the reference microphone is output to a virtual microphone position noise signal estimator 24 and a filter processor 26. The virtual microphone position noise signal estimator 24 and the filter processor 26 perform processing based on the noise signal x(n) at the position of the reference microphone obtained by the reference microphone. The other processing is the same as above, so repeated explanations will be omitted. It is assumed that the reference microphone is placed at a position where the secondary sound source signal y(n) is not collected.

[0093] There may be a plurality of error microphones 11. In this case, both error microphones and virtual microphones may be used. The number of secondary sound sources may be two or more.

[0094] For example, when the signal processing device 2 performs feedforward active noise control, there are two error microphones, one of which is a virtual microphone, and there are two secondary sound sources, the signal processing device 2 performs the processing shown in Fig. 7. It is assumed that the first error microphone is the actual error microphone and the second error microphone is the virtual microphone.

[0095] The following description will focus on the differences from the signal processing device 2 described with reference to Fig. 4. Duplicate descriptions of the same parts as those of the signal processing device 2 described with reference to Fig. 4 will be omitted.

[0096] The error microphone position noise signal estimator 21 calculates the error signal at the error microphone position obtained by the error microphone and the estimated value ^y m,1 (n),^y m,1 (n) and (n), the estimated noise signal at the error microphone position is calculated as ~d m,2 (n) is calculated (step S21).

[0097] The virtual microphone position noise signal estimation unit 22 estimates the noise signal at the error microphone position ~d m,2 For (n), g p,2 times and τ p,2 By processing at least one of the sample delays, the noise signal estimate ~d at the virtual microphone position is obtained. v,2 (n) is calculated (step S22). p,2 ,τ p,2 The definition of g p ,τ p is the same as the definition of

[0098] The virtual microphone position error signal estimator 23 estimates the noise signal at the virtual microphone position ~d v,2 (n) and the estimated secondary sound source signal at the virtual microphone position ^y v,1 (n),^y v,1 (n) and (n), the estimated error signal at the virtual microphone position is calculated as ~e v,2 (n) is calculated (step S23).

[0099] The virtual microphone position noise signal estimation unit 24 uses a filter that simulates the characteristics between the secondary sound source and the virtual microphone. - S v,2,1 (z) is used to process the noise signal x(n), and the resulting signal is vs,2,1 times and τ vs,2,1 By processing at least one of the sample delays, the noise signal estimate ^x at the virtual microphone position is obtained. 2,1 (n) (step S24). The virtual microphone position noise signal estimation unit 24 also calculates a filter simulating the characteristics between the secondary sound source and the virtual microphone. - S v,2,2 (z) is used to process the noise signal x(n), and the resulting signal is vs,2,2 times and τ vs,2,2 By processing at least one of the sample delays, the noise signal estimate ^x at the virtual microphone position is obtained. 2,2 (n) is calculated (step S24).

[0100] In more detail, -S v,2,1 (z) is a filter that simulates the characteristics between the first secondary sound source and the virtual microphone, - S v,2,2 (z) is a filter that simulates the characteristics between the second secondary sound source and the virtual microphone. vs,2,1 ,g vs,2,2 ,τ vs,2,1 ,τ vs,2,2 The definition of g vs ,τ vs is the same as the definition of

[0101] The signal processing device 2 in FIG. 7 further includes error microphone position noise signal estimating units 2101 and 2102 .

[0102] The error microphone position noise signal estimation unit 2101 uses a filter that simulates the characteristics between the secondary sound source and the error microphone. - S m,1,1 By processing the noise signal x(n) using (z), the estimated noise signal value ^x at the error microphone position is obtained. 1,1 (n) is calculated (step S24). The estimated noise signal value ^x at the error microphone position is calculated. 1,1 (n) is output to the filter estimation unit 251.

[0103] The error microphone position noise signal estimation unit 2102 also uses a filter that simulates the characteristics between the secondary sound source and the error microphone. - S m,1,2 By processing the noise signal x(n) using (z), the estimated noise signal value ^x at the error microphone position is obtained. 1,2 (n) is calculated (step S24). The estimated noise signal value ^x at the error microphone position is calculated. 1,2 (n) is output to the filter estimation unit 252.

[0104] In more detail, - S m,1,1 (z) is a filter that simulates the characteristics between the first secondary sound source and the first error microphone, - S m,1,2 (z) is a filter that simulates the characteristics between the second secondary sound source and the first error microphone.

[0105] 4. Filter estimation units 251 and 252 in FIG. 7 correspond to the filter estimation unit 25 in FIG.

[0106] The filter estimation unit 251 in FIG. 7 receives the error signal e obtained by the first error microphone. m,1 (n), the estimated noise signal at the error microphone position ^x 1,1 (n) and the estimated noise signal at the virtual microphone position ^x 2,1 The filter estimation unit 251 receives the error signal e (n) obtained by the first error microphone. m,1 (n) is used to estimate a filter for generating a secondary sound source signal for performing active noise control (step S25). In this example, the filter estimation unit 251 estimates a filter for generating a secondary sound source signal for performing active noise control using at least the error signal e obtained by the first error microphone. m,1 (n), the estimated noise signal at the error microphone position ^x 1,1 (n) and the estimated noise signal at the virtual microphone position ^x 2,1 (n) is used to estimate a filter for generating a secondary sound source signal for performing active noise control. The estimated filter is output to the filter processing unit 261.

[0107] The filter estimation unit 252 in FIG. 7 receives the error signal ∼e obtained by the virtual microphone. v,2 (n), the estimated noise signal at the error microphone position ^x 1,2 (n) and the estimated noise signal at the virtual microphone position ^x 2,2 The filter estimation unit 252 receives the error signal ~e obtained by the virtual microphone. v,2 (n) to estimate a filter for generating a secondary sound source signal for performing active noise control (step S25). In this example, the filter estimation unit 252 estimates a filter for generating a secondary sound source signal for performing active noise control using at least the error signal ~e obtained by the virtual microphone. v,2 (n), the estimated noise signal at the error microphone position ^x 1,2 (n) and the estimated noise signal at the virtual microphone position ^x 2,2 (n) is used to estimate a filter for generating a secondary sound source signal for performing active noise control. The estimated filter is output to the filter processing unit 262.

[0108] 4. Filter estimation units 261 and 262 in FIG. 7 correspond to the filter processing unit 26 in FIG.

[0109] The noise signal x(n) and the filter estimated by the filter estimation unit 251 are input to the filter processing unit 261. The filter processing unit 261 generates a secondary sound source signal y1(n) using the filter estimated by the filter estimation unit 251 (step 26).

[0110] The noise signal x(n) and the filter estimated by the filter estimation unit 252 are input to the filter processing unit 262. The filter processing unit 262 generates a secondary sound source signal y2(n) using the filter estimated by the filter estimation unit 252 (step 26).

[0111] y1(n) is the first secondary sound source signal, and y2(n) is the second secondary sound source signal.

[0112] The error microphone position secondary sound source signal estimation unit 27 uses a filter that simulates the characteristics between the secondary sound source and the error microphone. - S m,2,1 (z) is used to process the secondary sound source signal y1(n), and the resulting signal is ms,2,1 times and τ ms,2,1 By processing at least one of the sample delays, the secondary sound source signal estimate ^y m,1 (n) (step S27). The error microphone position secondary sound source signal estimation unit 27 also calculates a filter simulating the characteristics between the secondary sound source and the error microphone. - S m,2,2 (z) is used to process the secondary sound source signal y2(n), and the resulting signal is ms,2,2 times and τ ms,2,2 By processing at least one of the sample delays, the secondary sound source signal estimate ^y m,2 (n) is calculated (step S27).

[0113] In more detail, - S m,2,1 (z) is a filter that simulates the characteristics between the first secondary sound source and the error microphone, - S m,2,2(z) is a filter that simulates the characteristics between the second secondary sound source and the error microphone. g ms,2,1 ,g ms,2,2 ,τ ms,2,1 ,τ ms,2,2 The definition of g ms ,τ ms is the same as the definition of

[0114] The virtual microphone position secondary sound source signal estimation unit 28 uses a filter that simulates the characteristics between the secondary sound source and the virtual microphone. - S v,2,1 (z) is used to process the secondary sound source signal y1(n), and the resulting signal is vs,2,1 times and τ vs,2,1 By processing at least one of the sample delays, the secondary sound source signal estimate ^y v,1 (n) (step S28). The virtual microphone position secondary sound source signal estimation unit 28 also calculates a filter simulating the characteristics between the secondary sound source and the virtual microphone. - S v,2,2 (z) is used to process the secondary sound source signal y2(n), and the resulting signal is vs,2,2 times and τ vs,2,2 By processing at least one of the sample delays, the secondary sound source signal estimate ^y v,2 (n) is calculated (step S28).

[0115] In more detail, - S v,2,1 (z) is a filter that simulates the characteristics between the first secondary sound source and the virtual microphone, - S v,2,2 (z) is a filter that simulates the characteristics between the second secondary sound source and the virtual microphone. vs,2,1 ,g vs,2,2 ,τ vs,2,1 ,τ vs,2,2 The definition of g vs ,τ vs is the same as the definition of

[0116] If the wearable device is equipped with two or more error microphones, the signal processing device 2 may select, from among the two or more error microphones, an error microphone that is located at a position where the noise signal arrives earlier than the position of the virtual microphone. In this case, the signal processing device performs processing using this selected error microphone as the error microphone in the above-mentioned processing (for example, the processing of the signal processing device described with reference to FIG. 4). This allows processing using a more appropriate error microphone, thereby improving the noise reduction effect.

[0117] The signal processing device may further include a selection unit 211 that selects the error microphone. The selection unit 211 is shown by a dotted line in FIG. 4, for example.

[0118] The signal processing device 2 may perform only preprocessing of the virtual microphone processing. In other words, the signal processing device 2 does not need to include the virtual microphone position noise signal estimator 24, the filter estimator 25, and the filter processor 26. In other words, the signal processing device 2 may include the error microphone position noise signal estimator 21, the virtual microphone position noise signal estimator 22, the virtual microphone position error signal estimator 23, the error microphone position secondary sound source signal estimator 27, and the virtual microphone position secondary sound source signal estimator 28. In this case, the virtual microphone position error signal ~e obtained by the virtual microphone position error signal estimator 23 v (n) is used to perform active noise control using an existing active noise control module or library.

[0119] The specific configurations of the embodiments of the disclosed technology are not limited to those described above, and the specific configurations of the embodiments of the disclosed technology can be appropriately modified in design, etc., within the scope of the spirit of the embodiments of the disclosed technology.

[0120] The various processes described in the embodiments of the disclosed technology may not only be performed chronologically in the order described, but may also be performed in parallel or individually depending on the processing capacity of the device performing the processes or as needed.

[0121] For example, data may be exchanged directly between the components of the signal processing device 2, or may be exchanged via a storage unit (not shown).

[0122] Furthermore, a device (terminal) for using the device, system, or method of the present invention via a network (telecommunications line) may also be provided. The "device (terminal) for use" may be provided with functions (e.g., control function, decoding function, restoration function, input / output function, etc.) necessary to obtain the effects of implementing the device, system, or method of the present invention.

[0123] It goes without saying that other modifications are possible without departing from the spirit of the present invention.

[0124] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0125] [Experimental Example] First, we will show the results of an experiment to test the noise reduction effect of active noise control using a virtual microphone realized based on an error microphone.

[0126] A 30-second in-flight noise signal is output from speaker SP, which is the primary sound source. The wearable device is nwm MWE001, and the secondary sound source is the speaker of wearable device D. Speaker SP, which is the primary sound source, is placed in front of the dummy head, as shown in Figure 9(A). The distance between speaker SP and the dummy head is 80 cm.

[0127] The microphone placed at position A3 in Fig. 10(A) (position on the side of the wearable device D) is the error microphone in the above embodiment. Position A3 is a position where the influence of anti-phase waves is greater than that of positive phase waves. Also, a virtual microphone realized by this error microphone is placed at position A1 in Fig. 10(B) (entrance of the ear canal). Note that a microphone for measuring the noise reduction effect at the position of the virtual microphone is also placed at position A1 in Fig. 10(B) (entrance of the ear canal). An ECM with a diameter of 4 mm is used as the microphone.

[0128] The microphone placed at position A3 (a position on the side of the wearable device D) is used as an error microphone. The dotted line in Fig. 8 shows the noise reduction performance when conventional active noise control is performed, and the solid line in Fig. 8 shows the noise reduction performance when active noise control of the embodiment is performed. The horizontal axis in Fig. 8 represents frequency, and the vertical axis in Fig. 8 represents noise reduction performance. The smaller the noise reduction performance value, the higher the noise reduction performance. From Fig. 8, it can be seen that, unlike conventional active noise control, the active noise control of the embodiment achieves a noise reduction effect even when the error microphone is placed at a position where the influence of negative-phase waves is greater than that of positive-phase waves.

[0129] The noise reduction performance is, for example, L(f) = 20log 10 (|X(f) ANC-On | / |X(f) ANC-Off |), where f is the frequency. X(f) ANC-On is the logarithmic power spectrum obtained from the observed signal (noise + secondary sound source) when active noise control is performed. X(f) ANC-On is the logarithmic power spectrum obtained from the observed signal (noise + secondary sound source) without active noise control. The average is taken from the end of the observed signal for approximately 5 seconds (250 frames).

[0130] Next, we present the results of an experiment comparing the delay and sound pressure of the primary path.

[0131] 11 to 13 show impulse responses output from a speaker SP, which is a primary sound source, and measured by a microphone provided near a wearable device D attached to the left of a dummy head.

[0132] The distance between the speaker SP and the dummy head is 80 cm, and the speaker SP may be located in front of the dummy head as shown in Figure 9(A), on the left side of the dummy head as shown in Figure 9(B), or behind the dummy head as shown in Figure 9(C).

[0133] In each of the above cases, the impulse responses were measured when the microphone was located at positions A1 to A5 in Figures 10(A) and 10(B). Position A1 is the entrance of the ear canal, position A2 is the positive phase side, position A3 is the side of the wearable device D, position A4 is the front side of the ear, and position A5 is the back side of the ear.

[0134] In this experiment, the wearable device used was the nwm MWE001. A 4mm diameter ECM was used as the microphone. All impulse responses were filtered with a low-pass filter at a cutoff frequency of 2kHz, and the following arrival time differences and power ratios were calculated using the filtered impulse responses.

[0135] The arrival time difference is the delay of the impulse response being compared with the impulse response corresponding to the microphone placed at position A1. This delay can be expressed as, for example, argmax k {crosscorr(h,h ref ,k)}, where crosscorr is the cross-correlation function, h is the impulse response being compared, and h ref is the impulse response corresponding to the microphone placed at position A1, and k is the difference in the number of samples.

[0136] The power ratio is the ratio between the power of the impulse response being compared and the power of the impulse response corresponding to the microphone placed at position A1. This power ratio is, for example, 10 log 10 (mean(h 2 ) / mean(h ref 2 )) where mean means the average value.

[0137] Fig. 11(A) shows the impulse response when the speaker SP is located in front of the dummy head and the microphone is positioned at A1. Fig. 11(B) shows the impulse response when the speaker SP is located in front of the dummy head and the microphone is positioned at A2. Fig. 11(C) shows the impulse response when the speaker SP is located in front of the dummy head and the microphone is positioned at A3. Fig. 11(D) shows the impulse response when the speaker SP is located in front of the dummy head and the microphone is positioned at A4. Fig. 11(E) shows the impulse response when the speaker SP is located in front of the dummy head and the microphone is positioned at A5. The two numerical values ​​in the upper left corner of each of Figs. 11(A) to 11(E) are the arrival time difference and power ratio, respectively.

[0138] 11(A) to 11(E) show that when the speaker SP is located in front of the dummy head, the signal from the primary sound source arrives earliest when the microphone is located at position A4 (when the microphone is in front of the ear) as in Fig. 11(D). Also, when the speaker SP is located in front of the dummy head, the signal from the primary sound source arrives latest when the microphone is located at position A5 (when the microphone is behind the ear) as in Fig. 11(E).

[0139] Fig. 12(A) shows the impulse response when the speaker SP is located on the left side of the dummy head and the microphone is positioned at A1. Fig. 12(B) shows the impulse response when the speaker SP is located on the left side of the dummy head and the microphone is positioned at A2. Fig. 12(C) shows the impulse response when the speaker SP is located on the left side of the dummy head and the microphone is positioned at A3. Fig. 12(D) shows the impulse response when the speaker SP is located on the left side of the dummy head and the microphone is positioned at A4. Fig. 12(E) shows the impulse response when the speaker SP is located on the left side of the dummy head and the microphone is positioned at A5. The two numerical values ​​at the top left of each of Figs. 12(A) to 12(E) are the arrival time difference and power ratio, respectively.

[0140] From Figures 12(A) to 12(E), it can be seen that when the speaker SP is located on the left side of the dummy head, the signal from the primary sound source arrives earliest when the microphone is positioned at A3 (when the microphone is located on the side of the wearable device D) as shown in Figure 12(C).

[0141] Fig. 13(A) shows the impulse response when the speaker SP is behind the dummy head and the microphone is positioned at A1. Fig. 13(B) shows the impulse response when the speaker SP is behind the dummy head and the microphone is positioned at A2. Fig. 13(C) shows the impulse response when the speaker SP is behind the dummy head and the microphone is positioned at A3. Fig. 13(D) shows the impulse response when the speaker SP is behind the dummy head and the microphone is positioned at A4. Fig. 13(E) shows the impulse response when the speaker SP is behind the dummy head and the microphone is positioned at A5. The two numerical values ​​at the top left of each of Figs. 13(A) to 13(E) are the arrival time difference and power ratio, respectively.

[0142] 13(A) to 13(E) show that when the speaker SP is located behind the dummy head, the signal from the primary sound source arrives the earliest and the sound pressure is the largest when the microphone is positioned at A5 (when the microphone is behind the ear) as in Fig. 13(E). Also, when the speaker SP is located behind the dummy head, the signal from the primary sound source arrives the latest and the sound pressure is the smallest when the microphone is positioned at A4 (when the microphone is in front of the ear) as in Fig. 13(D).

[0143] As can be seen from this experimental example, the sound pressure of the noise signal at the error microphone position may differ from the sound pressure of the noise signal at the virtual microphone position, for example, placed at the entrance of the ear canal. Therefore, as in the above-described embodiment of the signal processing device and method, the noise signal at the virtual microphone position can be approximated by a real multiple of the noise signal at the error microphone position and / or a predetermined sample delay, thereby improving the noise cancellation effect. Furthermore, as described above, the selector 211 selects the error microphone based on the direction and localization information of the noise source. In other words, by selecting an error microphone located at a position where the noise signal arrives earlier than the virtual microphone position and performing processing using the selected error microphone, the noise cancellation effect can be further improved.

[0144] Next, we will show the results of an experiment that investigated individual differences in the secondary pathway in a wearable device that reproduces sound without completely blocking the external ear canal.

[0145] The response of the impulse output from the speaker of the wearable device, which was the secondary sound source, was measured with a microphone placed at the entrance of the ear canal. The number of impulse response data was 30 (number of subjects) x 2 (both ears) x 3 (number of measurements) = 180.

[0146] FIG. 14A shows a histogram of the time delay of the maximum index of the impulse response after filtering, where all impulse responses are filtered using a low-pass filter with a cutoff frequency of 2 kHz.

[0147] FIG. 14(B) shows a histogram of the average power of the low frequencies (200-2 kHz) of the secondary characteristic, in other words, the characteristic from the speaker of the wearable device, which is the secondary sound source, to the microphone placed at the entrance of the ear canal.

[0148] 14(A) and 14(B), there are individual differences in the secondary path. For this reason, by multiplying the secondary sound source signal at the virtual microphone position by a real number and / or delaying it by a predetermined number of samples, as in the above-described embodiment of the signal processing device and method, it is possible to reduce the influence of individual differences in the secondary path, in other words, individual differences in the shape of the pinna, and to improve the noise reduction effect.

[0149] [Program, Recording Medium] The functions realized by the components described in this specification may be implemented in circuitry or processing circuitry, including general-purpose processors, application-specific processors, integrated circuits, ASICs (Application Specific Integrated Circuits), CPUs (Central Processing Units), conventional circuits, and / or combinations thereof, programmed to realize the described functions. A processor includes transistors and other circuits and is considered to be circuitry or processing circuitry. A processor may also be a programmed processor that executes a program stored in a memory.

[0150] In this specification, a circuitry, unit, or means is hardware that is programmed to realize or performs the described functions, which may be any hardware disclosed herein or any hardware known to be programmed to realize or perform the described functions.

[0151] If the hardware is a processor considered to be a type of circuitry, the circuitry, means, or unit is a combination of the hardware and software used to configure the hardware and / or processor.

[0152] The various processes described above can be implemented by loading a program that executes each step of the above method into the recording unit 2020 of the computer 2000 shown in Figure 15, and operating the control unit 2010, input unit 2030, output unit 2040, display unit 2050, etc.

[0153] The program describing the processing contents can be recorded on a computer-readable recording medium, which may be, for example, a magnetic recording device, an optical disk, a magneto-optical recording medium, a semiconductor memory, or any other suitable recording medium.

[0154] The program may be distributed by, for example, selling, transferring, lending, etc. portable recording media such as DVDs and CD-ROMs on which the program is recorded. Furthermore, the program may be stored in a storage device of a server computer, and then transferred from the server computer to other computers via a network, thereby distributing the program.

[0155] A computer that executes such a program may first temporarily store the program recorded on a portable recording medium or transferred from a server computer in its own storage device. Then, when executing a process, the computer reads the program stored on its own recording medium and executes the process in accordance with the read program. Alternatively, the computer may read the program directly from a portable recording medium and execute the process in accordance with the program. Furthermore, the computer may execute the process in accordance with the program each time a program is transferred from a server computer to the computer. Alternatively, the server computer may not transfer the program to the computer, but may instead execute the process through a so-called ASP (Application Service Provider) service, which realizes the processing function by issuing an execution instruction and obtaining the results. Furthermore, the server computer may execute the process at the terminal using a so-called SaaS (Software as a Service) service, which allows users to use part of a server computer along with the program. In this embodiment, the program includes information used for processing by an electronic computer that is equivalent to a program (such as data that is not a direct instruction to a computer but has properties that dictate computer processing).

[0156] Furthermore, in this embodiment, the device is configured by executing a predetermined program on a computer, but at least a part of the processing contents may be realized by hardware.

Claims

1. A signal processing device for causing a wearable device that reproduces sound without completely blocking the external auditory canal to perform active noise control, wherein a virtual microphone realized based on an error microphone for performing the active noise control is located between the entrance of the external auditory canal of a user wearing the wearable device and the eardrum, and the signal processing device comprises: (1)g p is a predetermined value, and τ p is a predetermined value, and g is the estimated value of the noise signal at the error microphone position obtained from the error signal at the error microphone position. p times and τ p a virtual microphone position noise signal estimator for obtaining an estimated value of the noise signal at the virtual microphone position by performing at least one of sample delay and sample delay processing; and (2) g ms is a predetermined value, and τ ms is a predetermined value, and the secondary sound source signal is processed using a filter that simulates the characteristics between the secondary sound source and the error microphone, and the resulting signal is ms times and τ ms an error microphone position secondary sound source signal estimating unit for obtaining an estimated value of the secondary sound source signal at the error microphone position by performing at least one of sample delay and sample delay processing; and (3) g vs is a predetermined value, and τ vs is a predetermined value, and the secondary sound source signal is processed using a filter that simulates the characteristics between the secondary sound source and the virtual microphone, and the resulting signal is calculated using g vs times and τ vs and a virtual microphone position secondary sound source signal estimating unit that performs at least one of sample delay and sample delay processing to obtain an estimate of a secondary sound source signal at the virtual microphone position.

2. A signal processing device according to claim 1, comprising: a virtual microphone position error signal estimator that calculates an estimate of an error signal at the virtual microphone position by adding an estimate of a noise signal at the virtual microphone position and an estimate of a secondary sound source signal at the virtual microphone position; a filter estimator that uses at least the estimate of the error signal at the virtual microphone position to estimate a filter for generating a secondary sound source signal for performing the active noise control; and a filter processor that generates the secondary sound source signal using the filter.

3. A signal processing device according to claim 1 or 2, wherein the wearable device further includes at least one error microphone, and further includes an error microphone selection unit that selects, from the error microphone and the at least one error microphone, an error microphone that is located at a position where the noise signal arrives earlier than the position of the virtual microphone, and the signal processing device performs processing using the selected error microphone as the error microphone.

4. The signal processing device of claim 1, wherein the characteristics between the secondary sound source and the virtual microphone of the user wearing the wearable device, or a feature representing all or part of the characteristics, are used to calculate g vs ,τ vs The signal processing device further comprises a determination unit that determines at least one of the above.

5. A signal processing method for making a wearable device that reproduces sound without completely blocking the external auditory canal perform active noise control, wherein a virtual microphone realized based on an error microphone for performing the active noise control is located between the entrance of the external auditory canal of a user wearing the wearable device and the eardrum, and the signal processing method comprises: (1)g p is a predetermined value, and τ p is a predetermined value, and g is the estimated value of the noise signal at the error microphone position obtained from the error signal at the error microphone position. p times and τ p a virtual microphone position noise signal estimating step for obtaining an estimated value of the noise signal at the virtual microphone position by performing at least one of sample delay and sample delay processing; and (2) g ms is a predetermined value, and τ ms is a predetermined value, and the secondary sound source signal is processed using a filter that simulates the characteristics between the secondary sound source and the error microphone, and the resulting signal is ms times and τ ms an error microphone position secondary sound source signal estimating step for obtaining an estimate of a secondary sound source signal at the error microphone position by performing at least one of sample delay and sample delay processing; and (3) g vs is a predetermined value, and τ vs is a predetermined value, and the secondary sound source signal is processed using a filter that simulates the characteristics between the secondary sound source and the virtual microphone, and the resulting signal is calculated using g vs times and τ vs and a virtual microphone position secondary sound source signal estimating step of obtaining an estimate of a secondary sound source signal at the virtual microphone position by performing at least one of sample delay and sample delay processing.

6. A program for causing a computer to execute each step of the signal processing method of claim 5.

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