JP2013195158A - Sound volume correcting method and sound testing apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a sound volume correcting method and a sound testing apparatus that allow sound testing to be accurately performed.SOLUTION: A sound volume correcting method includes: a detection step for detecting specific frequency components inserted into multiple places of a sound signal outputted by a sound output device by using a sound sensor which moves relatively to the sound output device; and a sound volume correcting step for correcting a sound volume of the sound signal on the basis of a sound volume of the multiple specific frequency components. A sound testing apparatus comprises: a sound sensor for detecting specific frequency components inserted into multiple places of a sound signal outputted by a sound output device by using a sound sensor which moves relatively to the sound output device; and a sound volume correcting unit for correcting a sound volume of the sound signal on the basis of a sound volume of the multiple specific frequency components.

Description

  The present invention relates to a volume correction method and a sound test apparatus.

  A sound test of a speaker provided in a personal computer or the like may be performed on a belt conveyor line. In the sensory inspection by a person, the judgment criteria may differ depending on the person, an erroneous judgment may be made due to the influence of noise in the factory, and there is a problem that inspection cost is increased. Therefore, Patent Document 1 discloses a technique for canceling noise by generating an erasing sound having a phase opposite to that of the noise waveform.

JP 2003-167484 A

  However, since the speaker to be inspected moves relative to the sound sensor on the belt conveyor line, it is difficult to perform a sound test with high accuracy only by silencing the noise.

  The present invention has been made in view of the above problems, and an object thereof is to provide a sound volume correction method and a sound test apparatus that can perform a sound test with high accuracy.

  In order to solve the above problem, the volume correction method disclosed in the specification is inserted into a plurality of positions of a sound signal output by the sound output device using a sound sensor that moves relative to the sound output device. A detection step for detecting the specific frequency component, and a volume correction step for correcting the volume of the sound signal based on the volume of the plurality of specific frequency components.

  In order to solve the above problems, the sound test apparatus disclosed in the specification is inserted into a plurality of positions of a sound signal output by the sound output apparatus using a sound sensor that moves relative to the sound output apparatus. A sound sensor that detects the specific frequency component, and a volume correction unit that corrects the volume of the sound signal based on the volume of the plurality of specific frequency components.

  According to the volume correction method and sound test apparatus disclosed in the specification, a sound test can be performed with high accuracy.

It is a figure for demonstrating the outline of the sound test apparatus used for a sound test. (A) is a figure showing the waveform of a chirp signal, (b) is the speaker output volume in which the volume in the low range and the high range is reduced due to the frequency characteristics of the speaker, and (c) is a microphone corresponding to the position of the speaker. It is a figure showing an example of the volume change of a recording signal. (A) is a block diagram for demonstrating the structure of the sound test apparatus and test object which concern on Example 1, (b) is a block diagram showing each function of a calculating part. It is a schematic diagram for demonstrating the positional relationship of a recording start sensor, a microphone, and a test object. It is a block diagram for demonstrating the hardware constitutions of a calculating part. (A) is a figure showing the sound source signal for a test used by a present Example, (b) is a figure showing each peak amplitude value in a specific frequency. (A) is a figure for demonstrating an example of the approximated curve calculated from each peak amplitude value, (b) is a figure showing a recording signal and a volume correction curve, (c) is a recording signal after correction | amendment. FIG. (A) is an example of the chirp signal extracted by the waveform extraction unit, and (b) is a speaker frequency characteristic graph obtained by the Fourier transform unit. It is a figure for demonstrating an example of the flowchart performed in the case of the sound test by a sound test apparatus.

  Prior to the description of the examples, the sound test will be described. The sound test is a test in which a sound output device provided in a personal computer, a mobile phone, an audio device, or the like is a test target and the sound output characteristics of the test target are inspected. FIG. 1 is a diagram for explaining an outline of a sound test apparatus used for a sound test. With reference to FIG. 1, in the sound test, a sound signal output from a speaker 2 moving on the conveyor line 1 is detected by a sound sensor (microphone) 3, and the characteristics of the detected sound signal are measured.

  For the purpose of suppressing the influence of relative movement between the speaker 2 and the microphone 3, there is a method of performing a sound test by moving the microphone 3 together with the speaker 2. However, in this method, the microphone 3 must be accurately placed right above the center of the speaker 2 for each test object. Accordingly, the microphone 3 must be moved relative to the second test object after the sound test of the first test object is completed. That is, the microphone 3 must be returned to the original position before the sound test. In this case, a large-scale mechanism is required and costs are increased. Therefore, in order to omit the mechanism for returning the microphone 3 to the original position, it is conceivable to use a wireless microphone. However, when a wireless microphone is used, a plurality of microphones are required, and the plurality of microphones need to have equivalent characteristics. Therefore, the cost increases.

  From the above, the method of fixing one microphone 3 to, for example, the ceiling is preferable. However, in this method, the volume detected by the microphone 3 changes as the speaker 2 moves on the belt conveyor line 1. That is, when the speaker 2 and the microphone 3 are close to each other, the detected sound volume increases, and when the speaker 2 and the microphone 3 are far from each other, the detected sound volume decreases. Therefore, an accurate sound test is difficult.

  Therefore, a method of correcting the sound volume detected by the microphone 3 is conceivable in order to avoid a change in sound volume due to relative movement between the speaker 2 and the microphone 3. For example, a method of correcting the detected sound volume by measuring the center position of the speaker 2 using a sound volume change characteristic acquired in advance can be considered. However, the center position of the speaker 2 cannot be directly detected, but is indirectly detected using a sensor that detects the approach or passage of the housing. In this case, if the test target is a multi-model, the mounting position of the speaker 2 varies depending on the test target model. Therefore, in order to detect the center position of the speaker with high accuracy from the detection by the sensor, a database such as the distance between the sensor for each mixed model and the center of the speaker and the volume change correction curve for each model is required, which is expensive. . Note that the volume change correction curve changes depending on not only the distance between the microphone 3 and the speaker 2 or the directivity of the microphone 3, but also the directivity of the speaker 2, the material of the housing that houses the speaker 2, the shape, and the like. .

  From the above, it is preferable to use a method in which the sound volume change characteristic accompanying the movement of the test object can be actually measured from the recording signal recorded through the microphone 3 regardless of the detection of the center position of the speaker 2. Therefore, there is a method in which test sound source signal data having a constant amplitude is continuously reproduced from the speaker 2, a change in volume of a signal recorded through the microphone 3 is measured, and correction is performed based on the change in volume.

  By the way, the signal recorded via the microphone 3 is a signal in which the volume change caused by the movement of the speaker 2 and the volume change caused by the frequency characteristic of the speaker 2 are overlapped. For the frequency characteristic test, a chirp signal may be used as a test sound source. The chirp signal is a swept sine wave signal having an audible range of 20 Hz to 20 kHz.

  FIG. 2A is a diagram illustrating the waveform of the chirp signal. In FIG. 2A, the horizontal axis represents time, and the vertical axis represents a drive signal (for example, current) for driving the speaker 2. With reference to FIG. 2A, the electric signal input to the speaker 2 has a constant amplitude at any frequency. In contrast, FIG. 2B is a diagram illustrating the waveform of the chirp signal output from the speaker 2. In FIG. 2B, the horizontal axis represents time, and the vertical axis represents the volume output from the speaker 2. With reference to FIG.2 (b), since the output becomes small with respect to the electric signal input in a low frequency range and a high frequency range by the frequency characteristic of a speaker, a sound volume will differ according to a frequency.

  From the above, the recording signal recorded through the microphone 3 has a complicated volume change by superimposing the volume change due to the frequency characteristic of the speaker 2 in addition to the volume change due to the relative movement of the speaker 2. . FIG. 2C is a diagram illustrating an example of a volume change according to the position of the speaker 2. In FIG. 2C, a plurality of chirp signals simplified by reducing the number of amplitudes are depicted. Referring to FIG. 2C, it can be seen that the recording signal has a complicated volume change depending on the position of the speaker 2. For the F characteristic test (frequency characteristic test) of the speaker 2, a sound test in a wide frequency range including a low frequency region to a high frequency region where the speaker does not output sufficiently is required. From the above, it is difficult for the above-described method to accurately perform a sound test of the sound output device.

  Therefore, in the following embodiments, a sound volume correction method and a sound test apparatus that can perform a sound test with high accuracy will be described.

  FIG. 3A is a block diagram for explaining the configuration of the sound test apparatus 100 and the test object 200 according to the first embodiment. With reference to FIG. 3A, the sound test apparatus 100 includes a recording start sensor 10, a microphone 20, an input amplifier 30, an A / D converter 40, and a calculation unit 50. The test target 200 includes a sound source data storage unit 201, a control unit 202, a D / A converter 203, an output amplifier 204, and a speaker 205.

  FIG. 3B is a block diagram illustrating each function of the calculation unit 50. The calculation unit 50 functions as a recording data storage unit 51, a sound source information storage unit 52, a volume correction unit 53, a waveform extraction unit 54, a noise processing unit 55, a Fourier transform unit 56, a determination unit 57, and an output unit 58.

  FIG. 4 is a schematic diagram for explaining the positional relationship among the recording start sensor 10, the microphone 20, and the test object 200. Referring to FIG. 4, test object 200 is placed on belt conveyor line 206. The recording start sensor 10 and the microphone 20 are disposed above the belt conveyor line 206. The microphone 20 is disposed downstream of the recording start sensor 10 in the moving direction of the belt conveyor line 206.

  FIG. 5 is a block diagram for explaining a hardware configuration of the arithmetic unit 50. Referring to FIG. 5, the calculation unit 50 includes a CPU 101, a RAM 102, a storage device 103, an interface 104, and the like. Each of these devices is connected by a bus or the like. A CPU (Central Processing Unit) 101 is a central processing unit. The CPU 101 includes one or more cores. A RAM (Random Access Memory) 102 is a volatile memory that temporarily stores programs executed by the CPU 101, data processed by the CPU 101, and the like. The storage device 103 is a nonvolatile storage device. As the storage device 103, for example, a ROM (Read Only Memory), a solid state drive (SSD) such as a flash memory, a hard disk driven by a hard disk drive, or the like can be used. When the CPU 101 executes a predetermined program, the calculation unit 50 includes a recording data storage unit 51, a sound source information storage unit 52, a volume correction unit 53, a waveform extraction unit 54, a noise processing unit 55, a Fourier transform unit 56, and a determination unit. 57 and the output unit 58.

  Next, the operation of each part of the test object 200 and the sound test apparatus 100 will be described. The sound source data storage unit 201 is a nonvolatile memory such as a ROM (read only memory), a hard disk, or a flash memory, and stores sound source signal data for sound tests. The control unit 202 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), and the like, and generates a sound source signal for sound test from the sound source signal data stored in the sound source data storage unit 201.

  The D / A converter 203 is a digital / analog converter that converts a digital signal into an analog signal such as current, and converts the sound source signal generated by the control unit 202 into an analog signal such as current. The output amplifier 204 is an amplifier and amplifies the analog signal generated by the D / A converter 203. The speaker 205 outputs sound according to the amplified analog signal.

  The recording start sensor 10 is a sensor that detects the passage of an object. In this embodiment, the recording start sensor 10 detects whether or not the passage of the test object 200 is started in the moving direction of the belt conveyor line 206. When the recording start sensor 10 detects the start of passage of the test object 200, the recording start sensor 10 inputs a signal related to the detection to the calculation unit 50. The microphone 20 is a sound sensor and converts sound output from the speaker 205 into an analog signal such as a voltage. The input amplifier 30 is an amplifier, and amplifies the analog signal output from the microphone 20. The A / D converter 40 is an analog / digital converter that converts an analog signal into a digital signal, and converts the analog signal amplified by the input amplifier 30 into a digital signal.

  When the calculation unit 50 receives a signal related to detection of the passage of the test object 200 from the recording start sensor 10, the calculation unit 50 starts recording. Specifically, the recording data storage unit 51 stores a digital signal output from the A / D converter 40 as recording data. The sound source information storage unit 52 stores information related to the sound source signal for the sound test. The computing unit 50 examines the sound output characteristics of the test target 200 based on the recording data stored in the recording data storage unit 51 and the information on the sound source signal stored in the sound source information storage unit 52. Next, details of the operation of the calculation unit 50 will be described.

  FIG. 6A shows a test sound source signal used in this embodiment. In FIG. 6A, the horizontal axis represents time, and the vertical axis represents the volume output from the speaker 205. In this embodiment, a chirp signal is used as a test sound source that is repeatedly reproduced. As described above, the chirp signal is a swept sine wave signal having an audible range of 20 Hz to 20 kHz. A chirp signal, also called a swept sine wave signal, is a signal in which the frequency of a sine wave signal is continuously changed (swept) from a low frequency to a high frequency or from a high frequency to a low frequency, and is used as a signal for measuring frequency characteristics. One of the commonly used signals.

  When a chirp signal is employed, when a chirp signal is reproduced once, a specific frequency appears once. Therefore, the specific frequency (Fp) is used as the reference frequency. The specific frequency (Fp) is preferably a frequency near the center where the frequency characteristics of the speaker 205 are relatively stable. The specific frequency (Fp) can be set to about 1 kHz, for example. The sound source signal that can be used in the present embodiment is not limited to the chirp signal, and any sound source signal can be used as long as it is a sound source signal that appears at a known location at a known sound volume with a specific frequency at least once. .

  The specific frequency (Fp), the chirp signal duration Ts_e, and the time Ts_p from the start of the chirp signal until the specific frequency (Fp) appears are stored in the sound source information storage unit 52 as information on the sound source signal for sound test. ing. The duration Ts_e and the time Ts_p can be measured in advance.

  The sound volume correction unit 53 stores the required number of chirp signals in the recording data storage unit 51 using the duration Ts_e stored in the sound source information storage unit 52. For example, if the required number is N (N is a predetermined natural number), recording may be performed for a time equal to or longer than (N + 1) × duration Ts_e. Next, the sound volume correction unit 53 reads the specific frequency (Fp) stored in the sound source information storage unit 52 and acquires the peak amplitude value Ap of the specific frequency (Fp) from each chirp signal. The sound volume correction unit 53 acquires peak amplitude values Ap1, Ap2,..., ApN at a specific frequency (Fp) for each chirp signal. Since the test object 200 moves relative to the microphone 20, each peak amplitude value is a different value with reference to FIG.

  The volume correction unit 53 generates an approximate curve f (t) most applicable to the point sequence data of each peak amplitude value. The approximate curve (regression curve) can be generated by a numerical calculation method such as high-order polynomial curve fitting (Curve Fitting) such as the least square method. The approximate curve is at least a quadratic expression, and is generated from point sequence data of three (degree of polynomial + 1) or more. FIG. 7A is a diagram for explaining an example of an approximate curve calculated from each peak amplitude value.

  The maximum amplitude value Apc, which is the maximum value of the approximate curve f (t), is estimated to correspond to the sound volume when the center of the speaker 205 passes directly below the microphone 20. Also, the time Tpc corresponding to the maximum amplitude value Apc is estimated to correspond to the time when the center of the speaker 205 passes directly below the microphone 20. Thus, even when the specific frequency (Fp) does not appear at the center of the speaker 205, the volume and time when the center of the speaker 205 passes directly under the microphone 20 can be estimated. Furthermore, the maximum amplitude value Apc can also be used as a target value for quality determination regarding the volume of the speaker 205.

  The volume correction unit 53 calculates a volume correction curve [Apc / f (t)] by multiplying the reciprocal of the approximate curve f (t) by the maximum amplitude value Apc. Next, referring to FIG. 7B, the volume correction unit 53 corrects the recording signal by matching the time and multiplying the recording signal by a volume correction curve [Apc / f (t)]. To do. In particular, since the maximum amplitude value Apc is used, each recording signal can be corrected to a state where the center of the speaker 205 is located immediately below the microphone 20. FIG. 7C shows the corrected recording signal. Referring to FIG. 7C, the influence of the relative movement of the speaker 205 is avoided in the corrected recording signal.

  Next, the waveform extraction unit 54 extracts a test target signal necessary for determining the quality of the speaker 205 from the corrected recording signal. For example, the waveform extraction unit 54 extracts a chirp signal having the maximum S / N ratio from each chirp signal. In the present embodiment, the maximum S / N ratio means that the amplitude measurement value at the specific frequency (Fp) is maximum. Specifically, the waveform extraction unit 54 acquires the maximum value ApM of the peak amplitude values Ap1, Ap2,..., ApN at the specific frequency (Fp) of the recording signal after correction. Next, the waveform extraction unit 54 extracts a recording signal up to TeM after the lapse of the duration Ts_e, with the time TsM going back by the time Ts_p from the measurement value of the appearance time TpM of the maximum value ApM as a starting point. FIG. 8A is an example of the chirp signal extracted by the waveform extraction unit 54.

  The Fourier transform unit 56 performs frequency analysis (such as short-time Fourier transform) on the chirp signal extracted by the waveform extraction unit 54. Short-time Fourier transform (StFt: Short-time Fourier Transform) is a method of analyzing a time change of a frequency spectrum by multiplying a window function while shifting it by a minute time Δt and sequentially performing Fourier transform. The short-time Fourier transform is a method generally used for a time-varying signal such as sound. A wavelet transform may be used for the same purpose.

  FIG. 8B is a speaker frequency characteristic graph obtained by the Fourier transform unit 56. In FIG. 8B, the horizontal axis represents frequency, and the vertical axis represents amplitude. In order to generate a sweep of the chirp signal so that the frequency of the sine wave is proportional to time or the logarithm of frequency is proportional to time, the horizontal axis of the F-characteristic graph can be replaced from time to frequency. The quality of the speaker 205 can be determined by determining whether the amplitude for each frequency is within the allowable range.

  With reference to FIG. 8B, an acceptable upper limit line and an acceptable lower limit line are drawn as an allowable range of amplitude for each frequency. If all the results obtained by the Fourier transform unit 56 are within the allowable range, the determination unit 57 determines that the target speaker is “good”. The output unit 58 outputs the determination result of the determination unit 57 to the external device.

  FIG. 9 is a diagram for explaining an example of a flowchart executed in the sound test by the sound test apparatus 100. Hereinafter, the flowchart of FIG. 9 will be described. First, the volume correction unit 53 reads the duration Ts_e of the chirp signal and the time Ts_p from the start point of the chirp signal to the specific frequency (Fp) from the sound source information storage unit 52 (step S1). Next, when the recording start sensor 10 detects the start of passage of the test object 200, the volume correction unit 53 causes the recording data storage unit 51 to record the sound detected by the microphone 20 (step S2).

  Next, the sound volume correction unit 53 ends the recording by the recording data storage unit 51 after (necessary number of chirps N + 1) × duration Ts_e or more (step S3). Next, the volume correction unit 53 acquires peak amplitude values Ap1, Ap2,..., ApN at a specific frequency (Fp) from the N chirp signals (step S4). Next, the volume correction unit 53 generates an approximate curve f (t) from each peak amplitude value Ap1, Ap2,..., ApN, and obtains the time Tpc and the maximum value Apc at the maximum point of the approximate curve f (t) ( Step S5).

  Next, the waveform extraction unit 54 searches for a time TpM of the maximum value Apm (maximum S / N ratio) of each peak amplitude value Ap1, Ap2,..., ApN (step S6). Next, the waveform extraction unit 54 subtracts the time Ts_p from the time TpM to obtain the start point TsM of the chirp signal. Further, the waveform extraction unit 54 obtains the end point TeM of the chirp signal by adding the duration Ts_e to the start point TsM (step S7). Next, the waveform extraction unit 54 extracts a section from the recording signal stored in the recording data storage unit 51 to the end point TeM as the chirp signal section with the maximum S / N ratio (step S8). .

  Next, the volume correction unit 53 multiplies the volume correction curve [Apc / f (t)] by the chirp signal extracted in step S8, thereby obtaining the S / N ratio maximum chirp signal after volume correction. (Step S9). Next, the Fourier transform unit 56 performs frequency analysis by performing short-time Fourier transform on the S / N ratio maximum chirp signal obtained in step S9 (step S10). Next, the determination unit 57 performs pass / fail determination based on the frequency analysis in step S10, and the output unit 58 outputs the determination result to the external device (step S11). When the sound test is performed on the next test object, the process is executed again from step S2. When the sound test is not performed, the flowchart of FIG. 9 ends.

  According to the present embodiment, even if the frequency characteristic of the speaker 205 and the volume change accompanying the relative movement between the microphone 20 and the speaker 205 overlap, only the volume change due to the relative movement between the microphone 20 and the speaker 205 is corrected. Can do. Thereby, a sound test can be performed with high accuracy.

  In addition, since the volume change characteristic accompanying the movement of the speaker 205 is automatically measured each time, even when test objects having different housing shapes, materials, and directivity characteristics of the speaker 205 are mixed, the speaker center position and the microphone 20 for each model are mixed. It is not necessary to store a database such as the distance to the sound and the volume change characteristics accompanying the movement. In addition, it is not necessary to accurately set the microphone in alignment with the position directly above the center of the speaker 205, and a mechanism for returning the microphone to the initial position when the next test object flows is unnecessary.

  Further, when the test target speaker 205 passes under the microphone 20, the sound test of each test target speaker 205 can be automatically performed sequentially. If the microphone 20 is fixed, alignment errors such as microphone installation do not occur. Moreover, since it is not necessary to use a plurality of microphones, it is not necessary to match the characteristics of the plurality of microphones. That is, it is possible to perform a sound test with very high reproducibility. Moreover, since the center position of the speaker 205 and the volume value thereof can be estimated by using the approximate curve f (t), the utterance start point is adjusted so that the specific frequency (Fp) appears at the center of the speaker 205. There is no need. Furthermore, since the section with the highest S / N ratio can be extracted accurately, the accuracy of the sound test is increased.

(Other examples)
A plurality of chirp signals may be extracted for removing external noise. For example, the waveform extraction unit 54 extracts a necessary number of chirp signals in descending order of S / N ratio. The noise processing unit 55 performs noise removal processing on the plurality of extracted chirp signals. A plurality of chirp signals after noise removal processing may be used as a test target.

  In the above embodiment, the sound recording signal is multiplied by the volume correction curve [Apc / f (t)] to realize a state where the center of the speaker 205 is located immediately below the microphone 20 for each recording signal. But it is not limited to that. That is, even if the maximum value Apc is not used, any correction curve proportional to the inverse of the approximate curve f (t) can be used for volume correction. Further, the multiplication target of the volume correction curve may be only the chirp signal having the maximum S / N ratio. In this case, the number of multiplication objects is reduced and the processing is simplified.

  Moreover, in the said Example, although an approximate curve is used, it is not restricted to it. For example, an approximate straight line can be used. Specifically, the volume of the recording signal can be corrected using an approximate straight line that increases as it approaches the maximum value Apc and an approximate straight line that decreases as the distance from the maximum value Apc decreases.

  If the whole volume sampling data of the recording signal is multiplied by a volume correction curve having a different value, the calculation takes time. By the way, when extracting the specific frequency (Fp), since the short-time Fourier transform with time resolution (Δt) is performed, it is meaningless to make the unit time smaller than Δt. Therefore, by replacing the volume correction value with the same value for each time width of Δt and replacing t / Δt = i, the approximate curve becomes f (i), and the volume correction curve becomes [Apc / f (i)]. The amount can be reduced.

  Further, all the waveform data of the recording signal may be multiplied by the same volume correction value [Apc / f (i)] for Δt, but all the volume corrections are the same during Δt. Therefore, at the time of the short-time Fourier transform, the sound volume correction value [Apc / f (i)] may be multiplied by the Fourier transform result for each Δt. Since the Fourier transform is a linear transform, the sound volume correction may be multiplied before or after the transform.

  When the volume change due to the relative movement of the speaker 205 is sufficiently gradual within the interval of the duration time Ts_e of the chirp signal, each chirp signal has [Apc / Ap1], [Apc / Ap2],... [Apc / ApN]. May be multiplied by the same volume correction value. In this case, the calculation can be simplified. Also in this case, the sound volume correction may be multiplied before or after the short-time Fourier transform. Since the pass / fail judgment has a comparison with the pass / fail judgment value, it is only necessary to perform volume correction multiplication before the pass / fail judgment.

  The noise removal processing can be performed in the frequency domain after the short-time Fourier transform, instead of the averaging operation on the time domain waveform data. For example, short-time Fourier transform may be performed on a plurality of chirp signals extracted in descending order of S / N ratio, and noise removal processing may be performed on those results. In this case, it is possible to obtain a set of short-time Fourier transform results after noise removal, which are finally used as the determination target data. Note that, as noise removal processing, averaging processing such as vector averaging and RMS averaging, and magnitude comparison operations such as minimum value, median value, and maximum value may be used. Even in this case, the volume correction may be performed either before or after the short-time Fourier transform. However, when performing short-time Fourier transform on a plurality of extracted chirp signals for noise removal, the volume correction multiplication processing is completed between the plurality of chirp signals before the noise removal processing. There is a need.

  Moreover, in the said Example, although the sound signal output periodically is made into a detection target, it is not restricted to it. If the sound signal has a specific frequency component inserted at a plurality of locations, the volume of the sound signal can be corrected based on the volume of the specific frequency component.

  Although the embodiments of the present invention have been described in detail above, the present invention is not limited to such specific embodiments, and various modifications and changes can be made within the scope of the gist of the present invention described in the claims. It can be changed.

DESCRIPTION OF SYMBOLS 10 Recording start sensor 20 Microphone 30 Input amplifier 40 A / D converter 50 Calculation part 51 Recording data storage part 52 Sound source information storage part 53 Sound volume correction part 54 Waveform extraction part 55 Noise processing part 56 Fourier transform part 57 Determination part 58 Output part 100 sound test equipment 101 CPU
102 RAM
DESCRIPTION OF SYMBOLS 103 Memory | storage device 200 Test object 201 Sound source data storage part 202 Control part 203 D / A converter 204 Output amplifier 205 Speaker 206 Belt conveyor line

Claims (12)

A detection step of detecting specific frequency components inserted in a plurality of locations of a sound signal output by the sound output device using a sound sensor that moves relative to the sound output device;
And a volume correction step of correcting the volume of the sound signal based on the volume of the plurality of specific frequency components.   The volume correction method according to claim 1, wherein in the volume correction step, the volume of the sound signal is corrected using an inverse of an approximate curve of volume of the plurality of specific frequency components.   In the volume correction step, the volume of the sound signal is corrected by multiplying the sound signal by a time obtained by multiplying the curve obtained by multiplying the reciprocal of the approximate curve by the maximum value of the approximate curve so as to match the time. The sound volume correction method according to claim 2. The sound signal is a sound signal output periodically,
The volume correction method according to claim 1, wherein at least one of the specific frequency components is included in each cycle.   5. The volume correction method according to claim 4, wherein the sound signal is a chirp signal output periodically.   6. The method according to claim 1, further comprising: a determination step of determining whether the frequency characteristics obtained by performing the short-time Fourier transform on the sound signal corrected in the volume correction step is good or bad. Volume correction method. Using a sound sensor that moves relative to the sound output device, a sound sensor that detects specific frequency components inserted in a plurality of locations of the sound signal output by the sound output device;
A sound test apparatus comprising: a volume correction unit that corrects the volume of the sound signal based on the volumes of the plurality of specific frequency components.   The sound test apparatus according to claim 7, wherein the volume correction unit corrects the volume of the sound signal using an inverse of an approximate curve of the volume of the plurality of specific frequency components.   The volume correction unit corrects the volume of the sound signal by multiplying the sound signal by a curve obtained by multiplying the reciprocal of the approximate curve by the maximum value of the approximate curve so that the time coincides with the sound signal. The sound test apparatus according to claim 8. The sound signal is a sound signal output periodically,
The sound test apparatus according to claim 7, wherein one or more of the specific frequency components are included for each period.   The sound test apparatus according to claim 10, wherein the sound signal is a chirp signal output periodically.   The determination part which determines the quality of the frequency characteristic obtained by performing short-time Fourier transform with respect to the sound signal correct | amended by the said volume correction | amendment part is provided. Sound test equipment.

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