Sound processing method, sound processing system and program

Abstract

To achieve both improved sound suppression performance of target sounds and weight reduction of speaker units.SOLUTION: An sound processing system comprises: a first processing unit 41 that generates an acoustic signal Bk for canceling a target sound by performing a first processing on an acoustic signal Ak representing the target sound; and a second processing unit 42 that performs a second processing on the acoustic signal Bk using a nonlinear model that simulates nonlinearity of characteristics parameter of a speaker unit to reduce nonlinear distortion of a reproduced sound from the speaker unit, to generate an acoustic signal Ck supplied to the speaker unit.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present disclosure relates to a technique for reducing target sounds such as environmental sounds.

Background Art

[0002] For example, noise cancellation techniques have been conventionally proposed that utilize the result of picking up environmental sounds existing around a listener to cancel the environmental sounds that the listener hears. For example, Patent Document 1 discloses a technique for generating a cancellation signal for canceling a muffled sound synchronized with the rotation of an automobile engine.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When the output delay of the speaker unit used for noise cancellation is large, there is a problem that the performance of reducing the target sound (hereinafter referred to as "noise cancellation performance") deteriorates. For example, if a high-performance speaker unit with small waveform distortion such as non-linear distortion is used, the output delay is suppressed, and as a result, it is possible to achieve sufficient noise cancellation performance. However, a large magnet is required to structurally reduce the waveform distortion, and it is difficult to reduce the weight of the speaker unit. In view of the above circumstances, one aspect of the present disclosure aims to achieve both an improvement in the noise cancellation performance of the target sound and a reduction in the weight of the speaker unit.

Means for Solving the Problems

[0005] In order to solve the above problems, an acoustic processing method according to one aspect of the present disclosure generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound, and performs a second process for reducing the non-linear distortion of the reproduced sound from the speaker unit using a non-linear model that simulates the non-linearity of the characteristic parameters related to the speaker unit on the second acoustic signal, thereby generating a third acoustic signal to be supplied to the speaker unit.

[0006] An acoustic processing system according to one aspect of the present disclosure includes a first processing unit that generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound, and a second processing unit that generates a third acoustic signal to be supplied to the speaker unit by performing a second process for reducing the non-linear distortion of the reproduced sound from the speaker unit using a non-linear model that simulates the non-linearity of the characteristic parameters related to the speaker unit on the second acoustic signal.

[0007] A program according to one aspect of the present disclosure causes a computer system to function as a first processing unit that generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound, and a second processing unit that generates a third acoustic signal to be supplied to the speaker unit by performing a second process for reducing the non-linear distortion of the reproduced sound from the speaker unit using a non-linear model that simulates the non-linearity of the characteristic parameters related to the speaker unit on the second acoustic signal.

Brief Description of Drawings

[0008]

Figure 1

Figure 2

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Figure 11

Figure 12

Figure 13

Mode for Carrying Out the Invention

[0009] A: Embodiment FIG. 1 is a schematic diagram illustrating the configuration of an acoustic system 100 according to an embodiment of the present disclosure. The acoustic system 100 is an in - vehicle system installed in a vehicle 10 such as an automobile. The vehicle 10 is a moving body including, for example, an engine 11, four tires 12, and four seats 13 - 1 to 13 - 4.

[0010] FIG. 2 is a block diagram illustrating the configuration of the acoustic system 100. As illustrated in FIGS. 1 and 2, the acoustic system 100 includes four microphones 20 - 1 to 20 - 4, four speaker units 30 - 1 to 30 - 4, and an acoustic processing system 40. Note that the four microphones 20 - 1 to 20 - 4 and the four speaker units 30 - 1 to 30 - 4 may be interpreted as elements constituting the acoustic processing system 40.

[0011] As illustrated in FIG. 1, the four microphones 20-1 to 20-4 are installed at different positions within the vehicle 10. Similarly, the four speaker units 30-1 to 30-4 are also installed at different positions within the vehicle 10. Specifically, one microphone 20-k (k = 1 to 4) and one speaker unit 30-k are installed at positions corresponding to each of the four seats 13-1 to 13-4 within the vehicle 10. That is, the microphone 20-k and the speaker unit 30-k are installed for each listener sitting on each seat 13-k. For example, each microphone 20-k is installed at a position corresponding to the seat 13-k on the ceiling of the passenger compartment, and each speaker unit 30-k is installed on the inner wall surface of the door corresponding to each seat 13-k.

[0012] Each of the four microphones 20-1 to 20-4 is a sound collection device that generates an acoustic signal Ak by collecting ambient sound. The acoustic signal Ak is a sample series representing the waveform of a sound wave. The sound represented by the acoustic signal Ak includes the ambient sound that the listener sitting on the seat 13-k listens to. The ambient sound in this embodiment is, for example, engine noise (e.g., engine idling sound) generated by the rotation of the engine 11 of the vehicle 10. Note that the illustration of the A / D converter that converts each acoustic signal Ak from analog to digital and the amplifier that amplifies the acoustic signal Ak are omitted for convenience. The acoustic signal Ak is an example of the "first acoustic signal".

[0013] The acoustic processing system 40 is a signal processing device that processes each acoustic signal Ak. For example, the acoustic processing system 40 is realized by a DSP (Digital Signal Processor) dedicated to the processing of the acoustic signal Ak. The acoustic processing system 40 is realized by, for example, one or more semiconductor chips.

[0014] As illustrated in FIG. 2, the acoustic processing system 40 includes four processing units U1 to U4 corresponding to different speaker units 30-k. Each processing unit Uk generates an acoustic signal Ck by processing an acoustic signal Ak. The acoustic signal Ck is a sample sequence for canceling the ambient sound included in the acoustic signal Ak. Specifically, each processing unit Uk generates an acoustic signal Ck representing the canceling sound. The canceling sound represented by the acoustic signal Ck is a sound having an inverse phase relationship with respect to the ambient sound of the acoustic signal Ak. The acoustic signal Ck is an example of the "third acoustic signal".

[0015] The acoustic signal Ck is supplied to the speaker unit 30-k. The speaker unit 30-k is a sound emitting device that emits the canceling sound represented by the acoustic signal Ck. Note that illustrations of a D / A converter for converting the acoustic signal Ck from digital to analog and an amplifier for amplifying the acoustic signal Ck are omitted for convenience.

[0016] FIG. 3 is a cross-sectional view of the speaker unit 30-k. The speaker unit 30-k includes a frame 31, a magnet 32, a voice coil 33, a diaphragm 34, an edge 35, and a damper 36.

[0017] The frame 31 is a structure that constitutes the exterior of the speaker unit 30-k. The magnet 32 is an annular permanent magnet. The voice coil 33 is a coil that can be displaced in the axial direction within the magnetic field generated by the magnet 32. The diaphragm 34 is a frustum-shaped structure. The inner peripheral edge of the diaphragm 34 is fixed to the voice coil 33. The outer peripheral edge of the diaphragm 34 is connected to the frame 31 via the edge 35. Also, the diaphragm 34 and the frame 31 are connected via the damper 36. The edge 35 and the damper 36 are annular elastic bodies. Sound waves are radiated when the diaphragm 34 reciprocates in the axial direction.

[0018] FIG. 4 is a block diagram illustrating the configuration of any one of the processing units Uk. Each processing unit Uk includes a first processing unit 41 and a second processing unit 42. Note that the first processing unit 41 and the second processing unit 42 may be realized by a single semiconductor chip or by a plurality of separate semiconductor chips.

[0019] The first processing unit 41 generates an acoustic signal Bk by performing signal processing (hereinafter referred to as "first processing") on the acoustic signal Ak. Similar to the acoustic signal Ck, the acoustic signal Bk is a sample sequence for canceling the ambient sound included in the acoustic signal Ak. That is, the first processing unit 41 generates an acoustic signal Bk representing the cancellation sound. The cancellation sound represented by the acoustic signal Bk is a sound that has an inverse phase relationship with the ambient sound of the acoustic signal Ak. As described above, the first processing is an active noise canceling (ANC) process that generates an acoustic signal Bk of the cancellation sound from the acoustic signal Ak. Note that the acoustic signal Bk is an example of the "second acoustic signal".

[0020] FIG. 5 is a block diagram illustrating the configuration of the first processing unit 41. The first processing unit 41 includes an adaptive filter 411 and a control unit 412. The adaptive filter 411 generates an acoustic signal Bk by performing filter processing on the acoustic signal Ak. The control unit 412 adaptively controls the frequency response of the adaptive filter 411 according to the acoustic signal Ak. The control signal Q of the vehicle 10 may be used for the control of the adaptive filter 411 by the control unit 412. The control signal Q is a periodic signal that varies with a period corresponding to, for example, the rotational speed of the engine 11.

[0021] The second processing unit 42 in FIG. 4 generates an acoustic signal Ck by performing signal processing (hereinafter referred to as "second processing") on the acoustic signal Bk. Nonlinear distortion resulting from the nonlinearity of each element constituting the speaker unit 30-k is associated with the sound wave (hereinafter referred to as "reproduced sound") radiated from the speaker unit 30-k by the supply of the acoustic signal Ck. The second processing is signal processing for reducing the nonlinear distortion of the reproduced sound. That is, the second processing unit 42 generates the acoustic signal Ck from the acoustic signal Bk so that the nonlinear distortion in the reproduced sound of the speaker unit 30-k is reduced.

[0022] Specifically, the second processing unit 42 reduces non-linear distortion by using a non-linear model M that simulates the behavior of the speaker unit 30-k. The non-linear model M is a non-linear mathematical model that simulates the non-linearity of the characteristic parameters related to the speaker unit 30-k.

[0023] FIG. 6 is a schematic diagram of the non-linear model M. The input voltage u(t) of the non-linear model M is the voltage supplied to the voice coil 33. That is, the signal level of the acoustic signal Ck corresponds to the input voltage u(t). Also, the input current i(t) is the current flowing through the voice coil 33.

[0024] The non-linear model M includes the displacement x(t) of the diaphragm 34 in the axial direction, the electrical resistance Re and inductance Le(x(t)) of the voice coil 33, and the force factor (electromagnetic conversion factor) Bl(x(t)) of the voice coil 33. The force factor Bl(x(t)) is the product of the magnetic flux density B of the voice coil 33 and the winding width l. Also, the non-linear model M includes the mechanical resistance Rms, mass Mms, and compliance Cms(x(t)) of the vibration system in the speaker unit 30-k. The compliance Cms(x(t)) is the reciprocal of the spring constant Kms(x(t)) of the vibration system.

[0025] FIG. 7 is an explanatory diagram of the non-linearity of the characteristic parameters related to the speaker unit 30-k. As illustrated in FIG. 7, the inductance Le(x(t)) changes non-linearly according to the displacement x(t) of the diaphragm 34. Similarly, the force factor Bl(x(t)) and the compliance Cms(x(t)) (=1 / Kms(x(t))) also change non-linearly according to the displacement x(t) of the diaphragm 34.

[0026] As described above, the inductance Le(x(t)), the force coefficient Bl(x(t)), and the spring constant Kms(x(t)) in the non-linear model M are characteristic parameters that change non-linearly according to the displacement x(t) of the diaphragm 34. The non-linear relationships (Fig. 7) between each characteristic parameter (Le(x(t)), Bl(x(t)), Kms(x(t))) and the displacement x(t) are measured in advance using the actual speaker unit 30-k. Note that the relationships between each characteristic parameter and the displacement x(t) may also be estimated by various simulations.

[0027] The non-linear model M applied to the second process differs for each processing unit Uk. Specifically, the non-linear model M used in the second process of the processing unit Uk simulates the behavior of the speaker unit 30-k. Since the operating characteristics differ for each speaker unit 30-k, the non-linear model M also differs for each speaker unit 30-k. That is, for the second process related to each speaker unit 30-k, the non-linear model M corresponding to that speaker unit 30-k is used. Specifically, the numerical values of various parameters (constant parameters and characteristic parameters) included in the non-linear model M differ for each speaker unit 30-k.

[0028] For example, the numerical values of constant parameters such as the electrical resistance Re, the mechanical resistance Rms, and the mass Mms in the non-linear model M differ for each speaker unit 30-k. Also, the numerical values of characteristic parameters such as the inductance Le(x(t)), the force coefficient Bl(x(t)), and the spring constant Kms(x(t)) in the non-linear model M differ for each speaker unit 30-k. For example, the characteristics of the change of each characteristic parameter with respect to the displacement x(t) of the diaphragm 34 (i.e., the relationship between the displacement x(t) and the characteristic parameter) differ for each speaker unit 30-k.

[0029] Focusing on speaker units 30-k1 (k1 = 1 to 4) and 30-k2 (k2 = 1 to 4, k2 ≠ k1) among the four speaker units 30-1 to 30-4 for convenience, for the second process related to speaker unit 30-k1, the non-linear model M corresponding to speaker unit 30-k1 is used, and for the second process related to speaker unit 30-k2, the non-linear model M corresponding to speaker unit 30-k2 is used. And the numerical values of the parameters are different between the non-linear model M used in the second process related to speaker unit 30-k1 and the non-linear model M used in the second process related to speaker unit 30-k2. Note that speaker unit 30-k1 is an example of the "first speaker unit", and speaker unit 30-k2 is an example of the "second speaker unit".

[0030] According to the above configuration, the characteristics unique to each speaker unit 30-k are reflected in each non-linear model M. Therefore, compared with the case where the non-linear model M used in the second process is in a common form for the four speaker units 30-1 to 30-4, the non-linear distortion caused by the characteristics unique to each speaker unit 30-k can be reduced with high precision by the second process.

[0031] In the non-linear model M described above, equations (1) and (2) hold. The symbol v(t) in equations (1) and (2) means the velocity of the diaphragm 34 (= ∂x / ∂t), and the symbol a(t) means the acceleration a(t) of the diaphragm 34 (= ∂ 2 x / ∂ 2 t).

Number

Number

[0032] FIG. 8 is a flowchart of the second process executed by the second processing unit 42. The second process is repeated for each sample of the acoustic signal Bk. The second process includes a linear process S31 and a non-linear process S32.

[0033] The linear processing S31 is a signal processing for calculating displacement parameters related to the displacement x(t) of the diaphragm 34. The displacement parameters include the displacement x(t), velocity v(t) (= ∂x / ∂t), and acceleration a(t) (= ∂ 2 x / ∂ 2 t) of the diaphragm 34.

[0034] A linear model is used for the linear processing S31. The linear model is a mathematical model in which the non-linear characteristic parameters (Le(x(t)), Bl(x(t)), Kms(x(t))) in the non-linear model M are replaced with constants independent of the displacement x(t). Specifically, the linear model is expressed by the following mathematical formulas (3) and (4).

Equation

Equation

[0035] The second processing unit 42 calculates ideal displacement parameters of the speaker unit 30-k with respect to the acoustic signal Bk by analyzing the simultaneous differential equations expressed by Equations (3) and (4) (i.e., linear simulation). Specifically, by applying the signal level of the acoustic signal Bk as the input voltage u(t) to each linearized equation, the displacement parameters (x(t), v(t), a(t)) when the acoustic signal Bk is supplied to the speaker unit 30-k assumed to be a linear system are calculated. The acoustic signal Bk corresponds to a target signal representing the reproduced sound to be radiated by the speaker unit 30-k. The target signal is a signal representing an ideal sound wave without accompanying non-linear distortion.

[0036] Note that for solving the simultaneous differential equations in the linear processing S31, a known method such as a general state - space model is arbitrarily adopted. For example, for the analysis using a state - space model, see, for example, Huang, X. Feng, S. Chen, and Y. Shen, “Analysis of total harmonic distortion of miniature loudspeakers used in mobile phones considering nonlinear acoustic damping,” The Journal of the Acoustical Society of America, vol. 149, no. 3, pp. 1579 - 1588, Mar. 2021, doi: 10.1121 / 10.0003644.

[0037] The non - linear processing S32 in FIG. 8 is a signal processing for generating an acoustic signal Ck using the non - linear model M expressed by Equations (1) and (2). Specifically, the second processing unit 42 generates the acoustic signal Ck of the input voltage u[n] to be supplied to the speaker unit 30 - k in order to displace the diaphragm 34 according to the displacement parameter calculated by the linear processing S31. The input voltage u[n] corresponds to the signal level of the acoustic signal Ck. Note that the symbol n means the number of one sample in the discrete signal. In the following description, each variable is expressed using the number n.

[0038] From the above - mentioned Equation (2), the following Equation (5) representing the input current i[n] is derived.

Equation

[0039] The second processing unit 42 calculates the input current i[n] by applying the displacement parameters (x(t), v(t), a(t)) calculated by the linear processing S31 to Equation (5). Note that the force coefficient Bl(x[n]) in Equation (5) is set to a numerical value corresponding to the displacement x(t) calculated by the linear processing S31 based on the non-linear relationship (Figure 7) previously measured for the force coefficient Bl(x(t)) and the displacement x(t). Similarly, the spring constant Kms(x[n]) in Equation (5) is set to a numerical value corresponding to the displacement x(t) calculated by the linear processing S31 based on the non-linear relationship (Figure 7) previously measured for the spring constant Kms(x[n]) and the displacement x(t).

[0040] Also, from the aforementioned Equation (1), the following Equation (6) representing the input voltage u[t] is derived. In Equation (6) as well, similar to Equation (5), the time t is replaced with the sample number n. The symbol i'[n] in Equation (6) means the time derivative of the input current i[n].

Equation

[0041] The second processing unit 42 calculates the input voltage u[n] by applying the displacement parameters (x(t), v(t), a(t)) calculated by the linear processing S31 and the input current i[n] calculated by Equation (5) to Equation (6). Note that the inductance Le(x[n]) in Equation (6) is set to a numerical value corresponding to the displacement x(t) calculated by the linear processing S31 based on the non-linear relationship (Figure 7) previously measured for the inductance Le(x(t)) and the displacement x(t).

[0042] The second processing unit 42 generates a time series of the input voltage u[n] by repeating the second processing exemplified above. The time series of the input voltage u[n] is supplied as the acoustic signal Ck to the speaker unit 30-k. Therefore, the non-linear distortion in the reproduced sound of the speaker unit 30-k is reduced.

[0043] As described above, in the present embodiment, displacement parameters (x(t), v(t), a(t)) of the diaphragm 34 are calculated by the linear processing S31 using the linear model, and an acoustic signal Ck is generated by applying the displacement parameters to the non-linear processing S32 using the non-linear model M. Therefore, non-linear distortion can be reduced with high precision by simple processing.

[0044] FIG. 9 is a flowchart of the processing executed by the acoustic processing system 40. For example, the processing in FIG. 9 is executed for each sample of the acoustic signal Ak. Further, the processing in FIG. 9 is executed in parallel in each of the four acoustic processing systems 40 of the acoustic system 100.

[0045] When the processing is started, the first processing unit 41 acquires the acoustic signal Ak (S1). The first processing unit 41 generates an acoustic signal Bk by executing the first processing on the acoustic signal Ak (S2). The second processing unit 42 generates an acoustic signal Ck by executing the second processing on the acoustic signal Bk (S3). As illustrated in FIG. 8, the second processing includes a linear processing S31 and a non-linear processing S32. The second processing unit 42 supplies the acoustic signal Ck to the speaker unit 30-k (S4).

[0046] As described above, for each of the four speaker units 30-1 to 30-4, generation of the acoustic signal Bk by the first processing and generation of the acoustic signal Ck by the second processing are executed. Therefore, ambient sound that the listener listens to can be reduced at a plurality of points corresponding to different speaker units 30-k.

[0047] As described above, in the present embodiment, the acoustic signal Bk for canceling the ambient sound is generated by the first processing, and further, the second processing using the non-linear model M is executed on the acoustic signal Bk, so that non-linear distortion in the reproduced sound from the speaker unit 30-k is reduced. As a result of the reduction of non-linear distortion, the output delay is reduced. The output delay is the delay from the collection of the ambient sound by the microphone 20-k to the radiation of the canceling sound by the speaker unit 30-k (for example, the processing delay by the acoustic processing system 40).

[0048] The smaller the output delay is, the better the noise reduction performance of the environmental sound by the first process. Therefore, even when the lightweight speaker unit 30-k with a relatively large output delay is used, the noise reduction performance of the environmental sound can be improved. That is, according to the present embodiment, it is possible to achieve both an improvement in the noise reduction performance of the environmental sound and a reduction in the weight of the speaker unit 30-k.

[0049] FIG. 10 shows the measurement results of the non-linear distortion (THD: Total Harmonic Distortion) associated with the reproduced sound. FIG. 10 shows both the non-linear distortion in the present embodiment in which the second process is executed on the acoustic signal Bk and the non-linear distortion in the form in which the second process is not executed (hereinafter referred to as "proportional comparison"). According to the present embodiment, it can be confirmed that the non-linear distortion is reduced by executing the second process on the acoustic signal Bk as compared with the proportional comparison. The effect of reducing the non-linear distortion is particularly remarkable in the frequency range of 100 Hz or less where environmental sound (engine noise) exists.

[0050] FIG. 11 shows the results of measuring the waveform of the reproduced sound when the acoustic signal Ak is a sine wave. FIG. 11 shows both the measurement results when the acoustic signal Ak is a 47 Hz sine wave and the measurement results when the acoustic signal Ak is a 59 Hz sine wave. The horizontal axis in FIG. 11 represents the sample number n. Each measurement result in FIG. 11 shows both the waveform of the reproduced sound in the present embodiment and the waveform of the reproduced sound in the proportional comparison. From FIG. 11, it can be confirmed that as a result of reducing the non-linear distortion by the second process, the delay of the reproduced sound is also reduced.

[0051] FIG. 12 shows the measurement results of the delay difference between the case where the second process is executed (this embodiment) and the case where it is not executed (comparative example). The difference in the rise time of the reproduced sound in this embodiment with respect to the rise time of the reproduced sound in the comparative example is illustrated as the delay difference on the vertical axis of FIG. 12. The delay difference is expressed in terms of the number of samples. The smaller the numerical value of the delay difference within the negative range, the more the output delay of the reproduced sound is improved by reducing the non-linear distortion. According to this embodiment, it can be confirmed from FIG. 12 that the delay of the reproduced sound is significantly reduced compared to the comparative example. Also, the effect of reducing the delay is particularly remarkable in the frequency range of 100 Hz or less where environmental sound (engine noise) exists. Therefore, environmental sound can be effectively reduced by the first process.

[0052] B: Modification Example Specific modification modes added to each of the aspects exemplified above are illustrated below. Two or more aspects arbitrarily selected from the following illustrations may be appropriately combined within a non-conflicting range.

[0053] (1) In the above-described aspect, engine noise was exemplified as the target to be canceled by the first process, but environmental sound is not limited to the above examples. For example, road noise caused by the contact between the road surface and each tire 12 of the vehicle 10 is also assumed to be environmental sound that is the target to be canceled by the first process. That is, the first process may be, for example, a road noise canceling (RNC) process that generates an acoustic signal Bk for canceling road noise from the acoustic signal Ak. In the first process for canceling road noise, in addition to the acoustic signal Ak, an acceleration signal may be used to control the frequency response of the adaptive filter 411. The acceleration signal is a signal detected by an acceleration sensor installed in the vehicle 10. The intensity of road noise correlates with the acceleration of the vehicle 10.

[0054] As understood from the above examples, the first process is comprehensively expressed as a process for canceling environmental sound such as, for example, engine noise or road noise, and the specific configuration or procedure for the first process is arbitrary.

[0055] (2) In the above-described embodiment, environmental sounds such as engine noise or road noise are exemplified as the sounds to be canceled, but the target of cancellation by the first process is not limited to environmental sounds. Any type of target sound that is not limited to environmental sounds is assumed to be the target of cancellation by the first process.

[0056] (3) In the above-described embodiment, a form in which the acoustic signal Bk is generated from the acoustic signal Ak generated by one microphone 20-k is exemplified, but a plurality of acoustic signals Ak generated by different microphones 20-k may be used for generating the acoustic signal Bk in the first process. For example, the first processing unit 41 of the processing unit Uk may generate the acoustic signal Bk by executing the first process on four acoustic signals A1 to A4 generated by different microphones 20-k.

[0057] (4) In the above-described embodiment, a form in which the numerical values of various parameters (constant parameters and characteristic parameters) included in the non-linear model M differ for each speaker unit 30-k is exemplified, but the non-linear model M may be common for a plurality of speaker units 30-k. For example, for a plurality of speaker units 30-k having common operating characteristics, the numerical values of the respective parameters in the non-linear model M may be made common.

[0058] (5) In each of the above-described embodiments, the acoustic system 100 including a plurality of sets of the microphone 20-k and the speaker unit 30-k is exemplified, but an acoustic system 100 including only one set of the microphone 20-k and the speaker unit 30-k is also assumed.

[0059] (6) In each of the above-described embodiments, a form in which the acoustic processing system 40 is realized by a DSP dedicated to processing the acoustic signal Ak is exemplified, but as illustrated in FIG. 13, the acoustic processing system 40 may be realized using a general-purpose computer system. The acoustic processing system 40 in FIG. 13 includes a control device 51 and a storage device 52.

[0060] The control device 51 is composed of one or more processors that control each element of the acoustic processing system 40. Specifically, for example, the control device 51 is composed of one or more types of processors such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an SPU (Sound Processing Unit).

[0061] The storage device 52 is one or more memories that store the programs executed by the control device 51 and the data used by the control device 51. The storage device 52 is composed of a known recording medium such as a magnetic recording medium or a semiconductor recording medium, for example. By executing the program stored in the storage device 52, the control device 51 functions as a first processing unit 41 and a second processing unit 42 for generating the acoustic signal Ck from the acoustic signal Ak.

[0062] In the configuration of FIG. 13, the functions of the acoustic processing system 40 are realized by the cooperation of one or more processors constituting the control device 51 and the program stored in the storage device 52. The program according to the present disclosure can be provided in a form stored in a computer-readable recording medium and installed in a computer. The recording medium is, for example, a non-transitory recording medium, and an optical recording medium (optical disk) such as a CD-ROM is a preferred example, but any known form of recording medium such as a semiconductor recording medium or a magnetic recording medium is also included. Note that the non-transitory recording medium includes any recording medium except a transitory, propagating signal, and a volatile recording medium is not excluded either. Also, in a configuration where a distribution device distributes a program via a communication network, the storage medium that stores the program in the distribution device corresponds to the aforementioned non-transitory recording medium.

[0063] C: Supplementary Note From the forms exemplified above, for example, the following configurations can be grasped.

[0064] An acoustic processing method according to one aspect (Aspect 1) of the present disclosure generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound, and uses a non-linear model that simulates the non-linearity of the characteristic parameters regarding the speaker unit to perform a second process for reducing the non-linear distortion of the reproduced sound from the speaker unit on the second acoustic signal, thereby generating a third acoustic signal to be supplied to the speaker unit.

[0065] According to the above configuration, a second acoustic signal for canceling the target sound is generated by the first process, and further, by performing the second process using the non-linear model on the second acoustic signal, the non-linear distortion in the reproduced sound from the speaker unit is reduced. As a result of reducing the non-linear distortion, the output delay is reduced. The smaller the output delay is, the better the sound cancellation performance of the target sound by the first process. Therefore, even when a lightweight speaker unit with a relatively large output delay is used, the sound cancellation performance of the target sound can be improved. That is, according to the present disclosure, it is possible to achieve both an improvement in the sound cancellation performance of the target sound and a reduction in the weight of the speaker unit.

[0066] The "target sound" is the sound to be canceled by the acoustic processing method of the present disclosure. For example, the ambient sound existing around the listener is an example of the "target sound". For example, assuming adoption for a moving body such as an automobile, engine noise generated by the rotation of the engine, road noise caused by the contact between the road surface and the tires, etc., for example, acoustic sounds in the low frequency range of 100 Hz or less are exemplified as the "target sound" (ambient sound).

[0067] The "first process" is a signal process (for example, noise cancellation process) for generating a second acoustic signal for canceling the target sound. The second acoustic signal is, for example, a signal representing a sound wave with a reverse phase to the target sound. The second acoustic signal is ideally a signal that can completely cancel the target sound, but a signal that cannot completely cancel the target sound but can reduce it is also included in the "second acoustic signal".

[0068] "Characteristic parameters" are various parameters related to the characteristics of the speaker unit. For example, the inductance of the voice coil in the speaker unit (Le(x(t))), the force factor (Bl(x(t))) which is the product of the magnetic flux density and the winding width, or the spring constant of the vibration system (Kms(x(t))), etc. are exemplified as characteristic parameters. The "nonlinearity" of the characteristic parameters means the relationship in which the characteristic parameters change nonlinearly according to the displacement of the diaphragm in the speaker unit.

[0069] The "nonlinear model" is a mathematical model that simulates the nonlinear relationship between the displacement parameters (such as displacement, velocity, or acceleration) related to the displacement of the diaphragm in the speaker unit and the characteristic parameters of the speaker unit.

[0070] In a specific example (Aspect 2) of Aspect 1, the second process includes a linear process of calculating displacement parameters related to the displacement of the diaphragm of the speaker unit from the second acoustic signal using a linear model that simulates the behavior of the speaker unit, and a nonlinear process of generating the third acoustic signal representing the signal level to be supplied to the speaker unit to displace the diaphragm according to the displacement parameters using the nonlinear model. In the above aspect, the displacement parameters of the diaphragm are calculated by the linear process using the linear model, and the third acoustic signal is generated by applying the displacement parameters to the nonlinear process using the nonlinear model. Therefore, nonlinear distortion can be reduced with high precision by a simple process. Note that the "linear model" is a mathematical model in which each characteristic parameter of the speaker unit is set to a constant that does not depend on the displacement of the diaphragm.

[0071] In a specific example (Aspect 3) of Aspect 1 or Aspect 2, the speaker unit is installed in a moving body having an engine and tires, and the target sound includes engine noise generated by the rotation of the engine or road noise caused by the contact between the road surface and the tires. In the above aspect, a third acoustic signal supplied to the speaker unit installed in the moving body is generated. The main components of noise such as engine noise (e.g., engine rumbling noise) or road noise are predominantly included in the low-frequency range of about 100 Hz or less. According to the second process using the non-linear model, the non-linear distortion in the low-frequency range is effectively reduced, and as a result, the output delay in the low-frequency range is reduced. As a result of reducing the output delay in the low-frequency range as described above, a second acoustic signal capable of effectively canceling the target sound specific to the moving body, such as engine noise (e.g., engine rumbling noise) or road noise, can be generated by the first process.

[0072] In a specific example (Aspect 4) of any one of Aspect 1 to Aspect 3, for each of the plurality of speaker units, generation of the second acoustic signal by the first process and generation of the third acoustic signal by the second process are executed. In the above aspect, the first process and the second process are executed for each of the plurality of speaker units. Therefore, the target sound listened to by the listener can be reduced at a plurality of points corresponding to different speaker units. The above aspect is particularly suitable for an environment where a plurality of listeners are located at different positions in a space (e.g., the interior space of a moving body such as an automobile).

[0073] In a specific example of Aspect 4 (Aspect 5), for the second process related to the first speaker unit among the plurality of speaker units, a non-linear model corresponding to the first speaker unit is used, and for the second process related to the second speaker unit other than the first speaker unit among the plurality of speaker units, a non-linear model corresponding to the second speaker unit is used. According to the above aspect, compared with the form in which the non-linear model used in the second process is common for a plurality of speaker units, the non-linear distortion caused by the characteristics unique to each speaker unit can be reduced with high precision by the second process. Since the output delay is reduced by reducing the non-linear distortion, the target sound can be reduced with high precision using each speaker unit.

[0074] An acoustic processing system according to one aspect (Aspect 6) of the present disclosure includes a first processing unit that generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound, and a second process that reduces non-linear distortion of the reproduced sound from the speaker unit by using a non-linear model that simulates non-linearity of characteristic parameters related to the speaker unit, and generates a third acoustic signal supplied to the speaker unit by performing the second process on the second acoustic signal.

[0075] A program according to one aspect (Aspect 7) of the present disclosure causes a computer system to function as a first processing unit that generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound, and a second processing unit that reduces non-linear distortion of the reproduced sound from the speaker unit by using a non-linear model that simulates non-linearity of characteristic parameters related to the speaker unit, and generates a third acoustic signal supplied to the speaker unit by performing the second process on the second acoustic signal.

Description of Reference Numerals

[0076] 100…Audio system, 10…Vehicle, 11…Engine, 12…Tire, 13-k (13-1 to 13-4)…Seat, 20-k (20-1 to 20-4)…Microphone, 30-k (30-1 to 30-4)…Speaker unit, 31…Frame, 32…Magnet, 33…Voice coil, 34…Diaphragm, 35…Edge, 36…Damper, 40…Audio processing system, 41…First processing unit, 42…Second processing unit, 51…Control device, 52…Storage device.

Claims

1. By executing a first process on a first acoustic signal representing a target sound, a second acoustic signal for canceling the target sound is generated. By executing a second process for reducing the nonlinear distortion of the reproduced sound from the speaker unit using a nonlinear model that simulates the nonlinearity of the characteristic parameters related to the speaker unit on the second acoustic signal, a third acoustic signal to be supplied to the speaker unit is generated. An acoustic processing method realized by a computer system.

2. The second process includes: A linear process of calculating a displacement parameter related to the displacement of the diaphragm of the speaker unit from the second acoustic signal using a linear model that simulates the behavior of the speaker unit, and A nonlinear process of generating the third acoustic signal representing the signal level to be supplied to the speaker unit to displace the diaphragm according to the displacement parameter using the nonlinear model. The acoustic processing method according to Claim 1.

3. The speaker unit is installed in a moving body having an engine and tires, The target sound includes engine noise generated by the rotation of the engine or road noise caused by the contact between the road surface and the tires. The acoustic processing method according to Claim 1 or Claim 2.

4. For each of a plurality of speaker units, Generation of the second acoustic signal by the first process and Generation of the third acoustic signal by the second process are executed. The acoustic processing method according to Claim 1.

5. In the second process for the first speaker unit among the plurality of speaker units, a non-linear model corresponding to the first speaker unit is used. In the second process for a second speaker unit other than the first speaker unit among the plurality of speaker units, a non-linear model corresponding to the second speaker unit is used. The acoustic processing method according to claim 4.

6. A first processing unit that generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound; A second processing unit that generates a third acoustic signal to be supplied to the speaker unit by performing a second process for reducing non-linear distortion of the reproduced sound from the speaker unit on the second acoustic signal, using a non-linear model that simulates non-linearity of characteristic parameters related to the speaker unit An acoustic processing system comprising:

7. A first processing unit that generates a second acoustic signal for canceling the target sound by performing a first process on a first acoustic signal representing the target sound, and A second processing unit that generates a third acoustic signal to be supplied to the speaker unit by performing a second process for reducing non-linear distortion of the reproduced sound from the speaker unit on the second acoustic signal, using a non-linear model that simulates non-linearity of characteristic parameters related to the speaker unit, A program that causes a computer system to function as such.

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