Noise reduction device and noise reduction method

The present disclosure relates to a noise reduction device and a noise reduction method capable of reducing noise in a more stable and effective manner. Signal processing is performed to generate a reference signal representing a waveform of noise. Moreover, signal processing is performed for an error signal representing a waveform of an error measured by a microphone in accordance with an amplitude-frequency characteristic. Then, a filter coefficient with which the error signal becomes zero is calculated under adaptive algorithm with reference to the reference signal. The reference signal is filtered by using the filter coefficient to obtain a control signal. The control signal is supplied to the corresponding one of the predetermined number of output units. The present technology is applicable to a noise cancelling system equipped in a closed space such as an interior of a vehicle, for example.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a U.S. National Phase of International Patent Application No. PCT/JP2015/075160 filed on Sep. 4, 2015, which claims priority benefit of Japanese Patent Application No. JP 2014-188504 filed in the Japan Patent Office on Sep. 17, 2014. Each of the above-referenced applications is hereby incorporated herein by reference in its entirety.

TECHNICAL FIELD

The present disclosure relates to a noise reduction device, a noise reduction method, and a program, and more particularly to a noise reduction device, a noise reduction method, and a program capable of reducing noise in a more stable and effective manner.

BACKGROUND ART

There has been proposed a noise cancelling system which reduces noise by outputting a noise cancelling sound wave from a speaker.

For example, Patent Document 1 discloses an active vibration and noise reduction device which outputs noise cancelling sound waves from a plurality of speakers, and applies adaptive algorithm to each of a plurality of routes of the sound waves from the respective speakers to a microphone.

CITATION LIST

Patent Document

SUMMARY OF THE INVENTION

Problems to be Solved by the Invention

According to the conventional noise cancelling system, however, dips generated in the routes from the plurality of speakers to the microphone in a closed space, such as an interior of a vehicle, are difficult to cancel depending on positions of the speakers and the microphone. According to the configuration disclosed in foregoing Patent Document 1, for example, a dip generated in any one of the routes may adversely affect the adaptive algorithm even in the presence of the plurality of routes. In this case, stable noise reduction is difficult to achieve.

The present disclosure developed in consideration of the aforementioned circumstances reduces noise in a more stable and effective manner.

Solutions to Problems

A noise reduction device according to an aspect of the present disclosure includes: a reference signal processing unit that performs signal processing for generating a reference signal representing a waveform of noise corresponding to a reduction control target on the basis of an estimation value indicating estimation of an acoustic characteristic in a route from an output unit to an error measurement unit, the error measurement unit measuring an error corresponding to a waveform of a synthetic wave produced by synthesizing the noise, and a sound wave output from the output unit to cancel the noise; an error signal processing unit that performs signal processing for an error signal representing a waveform of the error measured by the error measurement unit, in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic; a filter coefficient calculation unit that calculates a filter coefficient with which the error signal becomes zero under adaptive algorithm with reference to the reference signal; and a filter unit that filters the reference signal by using the filter coefficient calculated by the filter coefficient calculation unit to obtain a control signal, and supplies the control signal to the output unit. The reference signal processing unit, the error signal processing unit, the filter coefficient calculation unit, and the filter unit are provided for each of a predetermined number of the output units.

A noise reduction method or a program according to an aspect of the present disclosure includes steps of: performing signal processing for generating a reference signal representing a waveform of noise corresponding to a reduction control target on the basis of an estimation value indicating estimation of an acoustic characteristic in a route from an output unit to an error measurement unit, the error measurement unit measuring an error corresponding to a waveform of a synthetic wave produced by synthesizing the noise, and a sound wave output from the output unit to cancel the noise; performing signal processing for an error signal representing a waveform of the error measured by the error measurement unit, in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic; calculating a filter coefficient with which the error signal becomes zero under adaptive algorithm with reference to the reference signal; and filtering the reference signal by using the filter coefficient to obtain a control signal, and supplying the control signal to the output unit. The signal processing for generating the reference signal, the signal processing for the error signal, the calculation of the filter coefficient, and the filtering of the reference signal are performed for each of a predetermined number of the output units.

According to an aspect of the present disclosure, signal processing is performed to generate a reference signal representing a waveform of noise corresponding to a reduction control target on the basis of an estimation value indicating estimation of an acoustic characteristic in a route from an output unit to an error measurement unit. In this case, the error measurement unit measures an error corresponding to a waveform of a synthetic wave produced by synthesizing the noise, and a sound wave output from the output unit to cancel the noise. Moreover, signal processing for an error signal representing a waveform of the error measured by the error measurement unit is performed. In this case, the signal processing for the error signal is performed in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic. Furthermore, a filter coefficient with which the error signal becomes zero is calculated under adaptive algorithm with reference to the reference signal. The reference signal is filtered by using the filter coefficient to obtain a control signal, and supplied the control signal to the output unit. In this case, the signal processing for generating the reference signal, the signal processing for the error signal, the calculation of the filter coefficient, and the filtering of the reference signal are performed for each of a predetermined number of the output units.

Effects of the Invention

According to an aspect of the present disclosure, more stable and effective noise reduction is achievable.

MODE FOR CARRYING OUT THE INVENTION

Specific embodiments to which the present technology has been applied are hereinafter described in detail with reference to the drawings.

A conventional adaptive filter is initially described with reference toFIGS. 1 through 3.

FIG. 1(A)andFIG. 1(B)are a view illustrating an example of a basic adaptive filter.FIG. 1(A)is a block diagram illustrating a configuration example of a noise cancelling system, whileFIG. 1(B)is a block diagram illustrating signal transmission in the noise cancelling system. Note that the system in the present specification represents a whole apparatus constituted by a plurality of devices.

As illustrated inFIG. 1(A), a noise cancelling system11includes microphones12and13, a speaker14, and a control device15.

The microphone12is a noise measurement unit which measures noise entering from the outside in real time. The microphone12supplies an electric signal representing a waveform of measured noise to the control device15as a reference signal x(n).

The microphone13is an error measurement unit which measures, as an error of noise cancelling control, a synthetic wave in real time produced by synthesizing noise corresponding to a reduction control target, and a noise cancelling sound wave output from the speaker14. The microphone13subsequently supplies an electric signal representing a waveform of the synthetic wave to the control device15as an error signal e(n). More specifically, the microphone13functions as an adder21which receives a control target signal d(n) representing a waveform of the noise corresponding to the reduction control target, and a control signal y(n) achieving reduction control of the noise as illustrated inFIG. 1(B). Then, the microphone13having received the respective signals d(n) and y(n) calculates an error signal e(n) indicating a cancellation between the control target signal d(n) and the control signal y(n), i.e., the error signal e(n) obtained by subtracting the control signal y(n) from the control target signal d(n), and supplies the calculated error signal e(n) to the control device15.

The speaker14is an output unit which outputs a sound wave having a waveform corresponding to the control signal y(n) supplied from the control device15.

The control device15generates the control signal y(n) on the basis of the reference signal x(n) received from the microphone12and the error signal e(n) received from the microphone13, and supplies the control signal y(n) to the speaker14. More specifically, the control device15includes a least mean square (LMS) algorithm block22and a finite impulse response (FIR) filter block23as illustrated inFIG. 1(B). The LMS algorithm block22generates a filter coefficient with which the error signal e(n) becomes zero for the FIR filter block23in real time under the adaptive algorithm with reference to the reference signal x(n). The LMS algorithm block22supplies the generated filter coefficient to the FIR filter block23. The FIR filter block23filters the reference signal x(n) by using the filter coefficient supplied from the LMS algorithm block22to generate the control signal y(n), and outputs the generated control signal y(n).

According to the noise cancelling system11having this configuration, the filter coefficient used by the FIR filter block23for filtering is updated in real time by the LMS algorithm block22under the adaptive algorithm. Accordingly, the noise cancelling system11is capable of outputting a noise cancelling sound wave from the speaker14to achieve noise reduction.

Incidentally, when viewed inFIGS. 1(A) and 1(B), the speaker14of the noise cancelling system11is disposed at a position in the vicinity of the microphone13corresponding to a control position. However, a certain distance is left from the speaker14to the control position in an actual situation. Accordingly, stability of a filter increases when consideration is given to an acoustic characteristic C exhibited in a transmission route from the speaker14to the microphone13.

FIGS. 2(A) and 2(B)referred to next is a view illustrating an example of an adaptive filter provided in consideration of an acoustic characteristic.FIG. 2(A)is a block diagram illustrating a configuration example of a noise cancelling system, whileFIG. 2(B)is a block diagram illustrating signal transmission in the noise cancelling system.

According to a noise cancelling system11A illustrated inFIGS. 2(A) and 2(B), a transmission route provided from the speaker14to the microphone13contains a filter block24setting a filter coefficient to the acoustic characteristic C between the FIR filter block23and the adder21as illustrated inFIG. 2(B). The noise cancelling system11A having this configuration calculates an estimation value C′ which indicates estimation of the acoustic characteristic C by measurement, and provides an estimation filter block25which sets a filter coefficient to the calculated estimation value C′ on the upstream side of the LMS algorithm block22.

More specifically, the control device15includes the estimation filter block25in addition to the LMS algorithm block22and the FIR filter block23. In this case, the estimation filter block25supplies, to the LMS algorithm block22, a filtering reference signal r(n) generated by filtering the reference signal x(n) using the estimation value C′ as a filter coefficient.

The noise cancelling system11A is therefore capable of cancelling noise in a stable manner in consideration of the acoustic characteristic C in the transmission route from the speaker14to the microphone13. The method which adds the estimation filter block25on the upstream side of the LMS algorithm block22in this manner is called Filtered-X.

FIGS. 3(A) and 3(B)referred to next is a view illustrating an example of an adaptive filter in a configuration including a plurality of speakers.FIG. 3(A)is a block diagram illustrating a configuration example of a noise cancelling system including a plurality of speakers, whileFIG. 3(B)is a block diagram illustrating signal transmission in the noise cancelling system including the plurality of speakers.

As illustrated inFIG. 3(A), a noise cancelling system11B includes the microphones12and13, M speakers14-1through14-M, and a control device15B.

In this way, according to the noise cancelling system11B including the M speakers14-1through14-M, FIR filter blocks23-1through23-M of the control device15B are provided for the M speakers14-1through14-M, respectively. In this case, the filter coefficient is updated in real time for each of the FIR filter blocks23-1through23-M by LMS algorithm blocks22-1through22-M, respectively.

Accordingly, the noise cancelling system11B is capable of generating control signals y0(n) through yM-1(n) for the corresponding speakers14-1through14-M in consideration of acoustic characteristics C0through CM-1to achieve effective noise cancellation.

Discussed hereinbelow is an application example of the noise cancelling system11B including the plurality of speakers14in a state equipped in a closed space such as an interior of a vehicle.

FIG. 4illustrates an example of the noise cancelling system11B equipped in a vehicle interior space. In this example, the five speakers14-1through14-5are disposed on a body of the vehicle, while the microphone13is disposed on a seat on which a driver sits.

According to the noise cancelling system11B having this configuration, it is estimated that a large number of peaks or dips (vertexes corresponding to tops or bottoms) are generated on a frequency axis by an effect of a standing wave in the interior of the vehicle forming a closed space, for example. When the acoustic characteristic C containing the large number of peaks or dips is measured and used without change, it is highly probable that the characteristic supplied to each of the FIR filter blocks23becomes extremely unnatural with a need for correction of the peaks or dips. This situation is generally overcome by changing the acoustic characteristic C to a natural characteristic. However, this change causes convergence of an original characteristic of each of the FIR filter blocks23to a different characteristic, in which condition stable reduction of noise becomes difficult.

Accordingly, it is proposed in this embodiment to provide a band-limiting filter for each peak or dip for removal of the corresponding peak or dip of the acoustic characteristic C, and input the band-limited error signal e(n) to the LMS algorithm block22.

The acoustic characteristics and the band-limiting filters are hereinafter described with reference toFIG. 5.

As illustrated in an upper part inFIG. 5, dips are generated at different frequencies for the acoustic characteristic C0and the acoustic characteristic C1, respectively. There are generated a number of peaks or dips particularly in a closed space. It is therefore estimated that the FIR filter blocks23do not function in the normal condition with filter coefficients generated by the corresponding LMS algorithm blocks22on the basis of the acoustic characteristics C0and C1in this state.

Accordingly, a band-limiting filter F0for limiting a frequency band containing the dip in the acoustic characteristic C0, and a band-limiting filter F1for limiting a frequency band containing the dip in the acoustic characteristic C1are provided as illustrated in a lower part inFIG. 5. As described above, it is proposed herein to produce a band-limiting filter F for each, and input the band-limited error signal e(n) to the corresponding LMS algorithm block22.

This method prohibits filtering by the FIR filter blocks23at frequencies out of specialty, and performs filtering by the FIR filter blocks23at frequencies of specialty in the respective routes. It is assumed that a frequency out of specialty is different for each route. Compensation for noise cancelling at a frequency out of specialty in a route is therefore achievable by noise canceling at a frequency of specialty in a different route.

A noise cancelling system according to a first embodiment to which the present technology has been applied is hereinafter described with reference toFIGS. 6 and 7.FIG. 6is a block diagram illustrating a configuration example of the noise cancelling system, whileFIG. 7is a block diagram illustrating signal transmission in the noise cancelling system. Note that blocks common to the configuration illustrated inFIGS. 3(A) and 3(B)and the configuration illustrated inFIGS. 6 and 7have been given common reference numbers. Detailed explanation of these common blocks is not repeated herein.

As illustrated inFIG. 6, a noise cancelling system51includes the microphones12and13, the M speakers14-1through14-M, and a control device61.

The microphone12is a noise measurement unit which measures noise corresponding to a reduction control target in real time. The microphone12supplies an electric signal representing a waveform of measured noise to the control device61as the reference signal x(n).

The microphone13is an error measurement unit which measures, as an error of noise cancelling control, a synthetic wave in real time produced by synthesizing noise corresponding to a reduction control target, and a plurality of sound waves output from the speakers14-1through14-M. The microphone13subsequently supplies an electric signal representing a waveform of the synthetic wave to the control device61as the error signal e(n).

Each of the speakers14-1through14-M is an output unit which outputs a sound wave having a waveform of the corresponding one of the control signals y0(n) through yM-1(n) supplied from the control device61. In addition, each of the sound waves output from the speakers14-1through14-M is changed in accordance with the corresponding one of the acoustic characteristics C0through CM exhibited from the speakers14-1through14-M to the microphone13, and is measured by the microphone13.

The control device61filters the reference signal x(n) received from the microphone12in accordance with the error signal e(n) received from the microphone13for each of the speakers14-1through14-M to obtain control signals y0(n) through yM-1(n), and supplies the control signals y0(n) through yM-1(n) to speakers14-1through14-M, respectively.

More specifically, the control device61includes M reference signal processing units62-1through62-M, M error signal processing units63-1through63-M, M coefficient calculation units64-1through64-M, and M filter units65-1through65-M. Note that respective configurations of the reference signal processing units62-1through62-M, respective configurations of the error signal processing units63-1through63-M, respective configurations of the coefficient calculation units64-1through64-M, and respective configurations of the filter units65-1through65-M have similar configurations as reference signal processing units, error signal processing units, coefficient calculation units, and filter units, respectively. Accordingly, the individual units are hereinafter collectively referred to as reference signal processing units62, error signal processing units63, coefficient calculation units64, and filter units65when distinction between the individual units is not necessary. Furthermore, the speakers14-1through14-M are referred to as speakers14similarly.

The estimation value C′ corresponding to estimation of the acoustic characteristic C exhibited from the corresponding speaker14to the microphone13is measured beforehand, and given to the corresponding reference signal processing unit62as a filter coefficient. Then, each of the reference signal processing unit62generates a filtering reference signal r(n) by filtering the reference signal x(n) received from the microphone12in accordance with the estimation value C′, and supplies the filtering reference signal r(n) to the reference signal processing unit62.

Each of the error signal processing units63performs signal processing for the error signal e(n) received from the microphone13in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic C exhibited from the corresponding speaker14to the microphone13which is measured beforehand, and supplies the error signal e(n) subjected to signal processing to the corresponding coefficient calculation unit64. For example, the error signal processing unit63functioning as a band-limiting filter block26as illustrated inFIG. 7performs band-limiting filtration for the error signal e(n) to cut peaks or dips in accordance with the amplitude-frequency characteristic, and supplies the band-limited error signal e(n) to the corresponding coefficient calculation unit64.

Each of the coefficient calculation units64generates a filter coefficient with which the error signal e(n) band-limited by the error signal processing unit63becomes zero for the corresponding filter unit65in real time under adaptive algorithm with reference to the filtering reference signal r(n) received from the reference signal processing unit62. Thereafter, the coefficient calculation unit64supplies the generated filter coefficient to the corresponding filter unit65.

Each of the filter units65filters the reference signal x(n) by using the filter coefficient received from the coefficient calculation unit64to generate the control signal y(n), and outputs the generated control signal y(n) to the corresponding speaker14.

According to the noise cancelling system51having this configuration, the respective error signal processing units63may cut peaks or dips in the manner described with reference toFIG. 5on the basis of the amplitude-frequency characteristics of the acoustic characteristics C0through CM-1measured beforehand for each of the plurality of routes. The band-limited error signal e(n) corresponding to each of the peaks or dips is then supplied to the corresponding coefficient calculation unit64to generate the filter coefficient. Accordingly, more stable and effective noise reduction is achievable.

More specifically, different routes are provided from the plurality of speakers14to the microphone13, wherefore respective dips and peaks are generated in different frequency bands on the frequency axis. The respective peaks or dips generated as described above are filtered by the error signal processing units63-1through63-M in such a manner as to limit the bands of the peaks or dips. In this case, the respective filter coefficients based on the error signals e(n) at the corresponding frequencies are not determined by the filter units65-1through65-M, but allowed to obtain slewing characteristics. Accordingly, stability increases in comparison with a configuration not limiting the band for each filter group.

Moreover, when the frequency subjected to band limitation is identical for each route, the corresponding band is not filtered. However, when the frequency subjected to band limitation is different for each of different routes, mutual compensation is realizable accordingly. Filtering for all frequencies is therefore achievable.

Note that the reference signal x(n) which indicates noise corresponding to a reduction control target may be measured by a sensor capable of detecting vibration of the vehicle, for example, in place of the microphone12.

A noise reduction process performed by the control device61is hereinafter described with reference to a flowchart shown inFIG. 8.

For example, the process starts in response to a start of supply of the reference signal x(n) from the microphone12, and a start of supply of the error signal e(n) from the microphone13. In step S11, the reference signal processing unit62generates the filtering reference signal r(n) by filtering the reference signal x(n) using the acoustic characteristic C measured beforehand as the estimation value C′, and supplies the generated filtering reference signal r(n) to the reference signal processing unit62.

In step S12, the error signal processing unit63performs band-limiting filtration for the error signal e(n) to cut peaks or dips in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic C. The error signal processing unit63supplies the band-limited error signal e(n) to the coefficient calculation unit64.

In step S13, the coefficient calculation unit64calculates a filter coefficient with which the error signal e(n) band-limited and supplied from the error signal processing unit63in step S12becomes zero under adaptive algorithm with reference to the filtering reference signal r(n) supplied from the reference signal processing unit62in step S11. Thereafter, the coefficient calculation unit64supplies the calculated filter coefficient to the filter unit65for update.

In step S14, the filter unit65generates the control signal y(n) by filtering the reference signal x(n) with the filter coefficient supplied from the coefficient calculation unit64in step S113, and outputs the generated control signal y(n) to the speaker14. As a result, a sound wave corresponding to the control signal y(n) is output from the speaker14, whereby noise measured by the microphone13is cancelled.

After completion of processing in step S14, the process returns to step S11to repeat processing in a similar manner.

As described above, the control device61calculates the filter coefficient using the error signal e(n) whose frequency band is limited to a band containing a generated peak or dip. Accordingly, the noise reduction process can reduce noise in a more stable and effective manner.

FIG. 9is a block diagram illustrating a modified example of the noise cancelling system inFIG. 6.

According to the noise cancelling system51illustrated inFIG. 9, each of the error signal processing units63of the control device61functions as a gain block27. More specifically, the gain block27is provided in place of the band-limiting filter block26illustrated inFIG. 7. In this case, the error signal processing unit63performs signal processing for the error signal e(n) supplied from the microphone13by gain control which decreases a gain in a route containing a large peak or dip, and increases a gain in a route containing a small peak or dip in accordance with an amplitude frequency characteristic.

According to the noise cancelling system51having this configuration, the FIR filter block23in a group containing a smaller peak or dip becomes more stable. In this case, a proportion of error signals of the more stable FIR filter blocks23becomes larger than a proportion of error signals of the less stable FIR filter blocks23. Accordingly, stability of the groups included in the noise cancelling system51improves as a whole.

As described above, more stable and effective noise reduction is achievable by providing the gain block27in the noise cancelling system51when the band-limiting filter block26is difficult to provide for a reason of implementation constraint, for example. This example is effective in a configuration given a smaller volume of resources for signal processing in comparison with the configuration including the band-limiting filter block26.

A noise cancelling system according to a second embodiment to which the present technology has been applied is hereinafter described with reference toFIGS. 10 and 11.FIG. 10is a block diagram illustrating a configuration example of the noise cancelling system, whileFIG. 11is a block diagram illustrating signal transmission in this noise cancelling system.

Note that blocks common to the noise cancelling system51illustrated inFIGS. 6 and 7and a noise cancelling system51A illustrated inFIGS. 10 and 11have been given common reference numbers. Detailed explanation of these blocks is not repeated herein.

More specifically, the noise cancelling system51A is similar to the noise cancelling system51illustrated inFIG. 6in that the microphones12and13, and the M speakers14-1through14-M are provided, and is different from the noise cancelling system51in that a control device61A having different configuration is provided. In addition, the control device61A is similar to the control device61illustrated inFIG. 6in that the M reference signal processing units62-1through62-M, the M error signal processing units63-1through63-M, the M coefficient calculation units64-1through64-M, and the M filter units65-1through65-M are provided. The control device61A further includes M peak/dip information acquisition units66-1through66-M in addition to these components.

Each of the peak/dip information acquisition units66measures a peak or dip of the corresponding filter unit65on the basis of fast Fourier transform (FFT) analysis performed for the corresponding filter unit65in real time to acquire peak/dip information. Thereafter, the peak/dip information acquisition unit66dynamically changes a frequency band for band limitation performed by the error signal processing unit63on the basis of the acquired peak/dip information. For example, the error signal processing unit63controls a cutoff frequency (fc) and a gain by using a parametric equalizer or the like to dynamically produce a band-limiting filter block28.

According to the noise cancelling system51illustrated inFIG. 6, for example, accurate measurement of the acoustic characteristic C is needed to produce the band-limiting filter block26. However, in case of implementation on vehicles, individual measurement for all types of vehicles is difficult to practice, for example. Moreover, even when the acoustic characteristic C is measured beforehand, it is estimated that the acoustic characteristic C changes in accordance with a passenger situation on a vehicle and a change of a vehicle with an elapse of time.

According to the noise cancelling system51A, however, the peak/dip information acquisition unit66calculates a peak or dip on the basis of frequency information or the like obtained by fast Fourier transform analysis for the filter coefficient of the filter unit65, based on which information the error signal processing unit63performs dynamical band limitation. Accordingly, while the noise cancelling system51illustrated inFIG. 6requires accurate measurement of the acoustic characteristic C, the noise cancelling system51A eliminates the necessity of accurate measurement of the acoustic characteristic C. Moreover, the noise cancelling system51A is easily adaptable to transitions of the acoustic characteristic C produced by a change of a passenger situation on a vehicle and a change of a vehicle with an elapse of time.

FIG. 12is a block diagram illustrating a modified example of the noise cancelling system illustrated inFIG. 10.

According to the noise cancelling system51A illustrated inFIG. 12, each of the error signal processing units63of the control device61functions as a gain block29. More specifically, the gain block29is provided in place of the band-limiting filter block28illustrated inFIG. 11. In this case, each of error signal processing units63A performs signal processing for the error signal e(n) supplied from the microphone13by dynamically decreasing a gain in a route containing a large peak or dip, and dynamically increasing a gain in a route containing a small peak or dip in accordance with an amplitude frequency characteristic.

As described above, more stable and effective noise reduction is also achievable by providing the gain block29in the noise cancelling system51A when the band-limiting filter block28is difficult to provide for a reason of implementation constraint, for example. This example is effective in a configuration given a smaller volume of resources for signal processing in comparison with the configuration including the band-limiting filter block26. Furthermore, reduction of noise is more stabilized by controlling the gain of the gain block29in accordance with the peak/dip information.

Note that the respective processes described with reference to the foregoing flowcharts need not be processed in time series in the orders shown in the respective flowcharts, but may include processes executed in parallel or individually (such as parallel processes or processes for each object). Moreover, the program may be processed by a single CPU, or by a plurality of CPUs for separate processing.

Moreover, a series of processes described above (information processing method) may be executed either by hardware or software. When the series of processes are executed by software, programs constituting the software are installed from a program recording medium where the programs are recorded, to a computer incorporated into a dedicated hardware, or a general-purpose personal computer or the like capable of executing various functions under various types of programs installed to the computer.

FIG. 13is a block diagram illustrating a configuration example of hardware of a computer which executes a series of the processes described above under programs.

A central processing unit (CPU)101, a read only memory (ROM)102, and a random access memory (RAM)103are connected with each other via a bus104in computer.

An input/output interface105is further connected with the bus104. Further connected with the input/output interface105are an input unit106constituted by a keyboard, a mouse, a microphone or the like, an output unit107constituted by a display, a speaker or the like, a storage unit108constituted by a hard disk, a non-volatile memory or the like, a communication unit109constituted by a network interface or the like, and a drive110which drives a removable medium111constituted by a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory or the like.

According to the computer having this configuration, the CPU101loads and executes programs stored in the storage unit108to the RAM103via the input/output interface105and the bus104to perform the foregoing series of processes, for example.

The programs executed by the computer (CPU101) are recorded in the removable medium111corresponding to a package medium constituted by a magnetic disk (including flexible disk), an optical disk (such as a compact disc-read only memory (CD-ROM) and a digital versatile disc (DVD)), a magneto-optical disk, a semiconductor memory or the like, or are presented via a wired or wireless transmission medium such as a local area network, the Internet, and digital satellite broadcasting.

In this case, the programs may be installed in the storage unit108via the input/output interface105with attachment of the removable medium111to the drive110. Alternatively, the programs may be received by the communication unit109via a wired or wireless transmission medium, and installed in the storage unit108. Instead, the programs may be installed in the ROM102and the storage unit108beforehand.

Note that the present technology may have the following configurations.

A noise reduction device including:

a reference signal processing unit that performs signal processing for generating a reference signal representing a waveform of noise corresponding to a reduction control target on the basis of an estimation value indicating estimation of an acoustic characteristic in a route from an output unit to an error measurement unit, the error measurement unit measuring an error corresponding to a waveform of a synthetic wave produced by synthesizing the noise, and a sound wave output from the output unit to cancel the noise;

an error signal processing unit that performs signal processing for an error signal representing a waveform of the error measured by the error measurement unit, in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic;

a filter coefficient calculation unit that calculates a filter coefficient with which the error signal becomes zero under adaptive algorithm with reference to the reference signal; and

a filter unit that filters the reference signal by using the filter coefficient calculated by the filter coefficient calculation unit to obtain a control signal, and supplies the control signal to the output unit, wherein

the reference signal processing unit, the error signal processing unit, the filter coefficient calculation unit, and the filter unit are provided for each of a predetermined number of the output units.

The noise reduction device according to (1) described above, wherein the error signal processing unit functions as a filter block that limits a frequency band containing a peak or a dip of amplitude on the basis of the amplitude-frequency characteristic.

The noise reduction device according to (1) described above, wherein the error signal processing unit functions as a gain block that controls a gain on the basis of the amplitude-frequency characteristic in accordance with a level of a peak or a dip of amplitude.

The noise reduction device according to any one of (1) through (3) described above, further including

a peak/dip information acquisition unit that supplies, to the error signal processing unit, information indicating the peak or the dip of the amplitude-frequency characteristic acquired by performing fast Fourier transform analysis for the control signal output from the filter unit in real time, wherein

the error signal processing unit dynamically performs signal processing on the basis of the information indicating the peak or the dip of the amplitude-frequency characteristic.

A noise reduction method including steps of:

performing signal processing for generating a reference signal representing a waveform of noise corresponding to a reduction control target on the basis of an estimation value indicating estimation of an acoustic characteristic in a route from an output unit to an error measurement unit, the error measurement unit measuring an error corresponding to a waveform of a synthetic wave produced by synthesizing the noise, and a sound wave output from the output unit to cancel the noise;

performing signal processing for an error signal representing a waveform of the error measured by the error measurement unit, in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic;

calculating a filter coefficient with which the error signal becomes zero under adaptive algorithm with reference to the reference signal; and

filtering the reference signal by using the filter coefficient to obtain a control signal, and supplying the control signal to the output unit, wherein

the signal processing for generating the reference signal, the signal processing for the error signal, the calculation of the filter coefficient, and the filtering of the reference signal are performed for each of a predetermined number of the output units.

A program under which a computer executes a noise reduction process that includes steps of:

performing signal processing for generating a reference signal representing a waveform of noise corresponding to a reduction control target on the basis of an estimation value indicating estimation of an acoustic characteristic in a route from an output unit to an error measurement unit, the error measurement unit measuring an error corresponding to a waveform of a synthetic wave produced by synthesizing the noise, and a sound wave output from the output unit to cancel the noise;

performing signal processing for an error signal representing a waveform of the error measured by the error measurement unit, in accordance with an amplitude-frequency characteristic obtained from the acoustic characteristic;

calculating a filter coefficient with which the error signal becomes zero under adaptive algorithm with reference to the reference signal; and

filtering the reference signal by using the filter coefficient to obtain a control signal, and supplying the control signal to the output unit, wherein

the signal processing for generating the reference signal, the signal processing for the error signal, the calculation of the filter coefficient, and the filtering of the reference signal are performed for each of a predetermined number of the output units.

Note that the present embodiment is not limited to the embodiment described above, but may be practiced with various modifications without departing from the subject matters of the present disclosure.

REFERENCE SIGNS LIST