• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The present invention relates to an automated acoustic equalization method, characterized in that it comprises the following steps: • Measurement of N impulse responses RI1, RI2, RIN after emission of a precalibrated sound signal received by N microphones; • Calculation of N corresponding frequency responses by Fast Fourier Transform; • Establishment of an average M of N frequency responses; • Logarithmic frequency scale translation of said average M of the N frequency responses; • Interpolation of a target sound signature curve Cec from a number of points selected by a user; • Logarithmic frequency scale translation of said target sound signature curve Cec; • comparing said averaged response M and said target response Cec, by calculating the difference between said averaged response M and said target sound signature response Cec; • Analysis of the curve Cdiff resulting from the difference between said averaged response M and said target response Cec; and • Determining filter parameters for reducing the difference between said averaged response M and said target response Cec by first processing the local maxima in descending order according to their gain, then the local minima, and performing successive iterations. ; said method further comprising a step of optimizing the parameters of the filters to improve the performance of the system. The present invention also relates to an automated acoustic equalization system.
    公开号:FR3018015A1
    申请号:FR1451504
    申请日:2014-02-25
    公开日:2015-08-28
    发明作者:Frederic Amadu；Delphine Devallez
    申请人:Arkamys SA；
    IPC主号:
    专利说明:

    [0001] FIELD OF THE INVENTION The present invention relates to the field of sound signal processing. The present invention relates more particularly to a method and an automated acoustic equalization system.
    [0002] A case of use of the present invention is as follows: in the automotive field: a plurality of microphones are placed in a vehicle and pre-calibrated sound sequences are broadcast in the vehicle speakers. A system compares the sound signals emitted and the sound signals received and recorded. We deduce the "acoustic signature" of the passenger compartment of the vehicle. The user then defines a target acoustic signature curve, which is different from the vehicle's native acoustic signature. A second algorithm calculates digital filter coefficients so that, when these filters are applied before sound signals are broadcast in the vehicle loudspeakers, the acoustic signature of the vehicle becomes the target sound signature curve, and not the native acoustic signature of the vehicle. In the context of the present invention, "IIR" or "Infinite Impulse Response" filters are used in English terminology.
    [0003] More particularly, in the context of the present invention, so-called "Biquad" filters of the second order are used. The method and the system according to the present invention concern the equalization of the amplitude of the frequency response of the passenger compartment.
    [0004] State of the art It is known in the state of the art the French patent application No. FR 2 967 848 (Scientific and Technical Building Center), which relates to a spectrum correction system intended in particular for a theater . This patent application of the prior art describes an electroacoustic system comprising a plurality of cells. In these cells are provided: an equalization device, a transmitter, a receiver, an amplification circuit for amplifying the signals from the receiver to said transmitter, and a computing element which will act, among other things, on the device of equalization. This technical solution of the prior art proposes to measure the emitting response, a theater observed at the receiver by using, in particular, a measurement signal supplied by a noise generator or any other measurement method making it possible to observe the system response in open loop. The equalizer device works to make said response come closest to a desired response. This technical solution of the prior art has for application the modification of the acoustic properties of theaters.
    [0005] The prior art also knows, from US Pat. No. 6,721,428 B1 (Texas Instruments), an automatic loudspeaker equalizer. This prior art US patent relates more particularly to a method for generating digital filters for equalizing a loudspeaker. First digital data is provided, for a tolerance interval for a tone-based target response response versus frequency for the loudspeaker. Second digital data is generated, for an actual acoustic signal response curve as a function of frequency for the loudspeaker. The first digital data is compared with the second digital data, and it is determined whether the actual response curve is in the tolerance range. If the actual response curve is not in the tolerance range, digital audio filters are iteratively generated, and the digital audio filters are applied to the second digital data to generate third digital data for a compensated response curve. . The frequency, gain and bandwidth of the digital audio filters are automatically optimized until the compensated response curve is within the tolerance range or a predetermined limit of the number of digital audio filters has been reached. of the two taking place first.
    [0006] Also known in the state of the art is the scientific publication "Filter Design Method for Loudspeaker Equalization Based on IIR Parametric Filters" by German Ramos and Jose J. Lopez.
    [0007] Disclosure of the Invention The present invention provides a method for providing equalization of a signal by determining filter parameters to reduce the difference between the amplitude of a frequency response representing the acoustic signature of a set of speakers in their environment and a target sound signature curve. For this purpose, the present invention relates, in its most general sense, to an automated acoustic equalization method, characterized in that it comprises the following steps: measurement of N impulse responses RI1, RI2, RIN after transmission of a precalibrated sound signal received by N microphones; - Calculation of N corresponding frequency responses by Fast Fourier Transform; - Establishment of an average M of N frequency responses; - Logarithmic frequency scale translation of said average M of the N frequency responses; - Interpolation of a target sound signature curve Cec from a number of points chosen by a user; - logarithmic frequency scale translation of said target sound signature curve Cec; Comparing said averaged response M and said target response Cec, by calculating the difference between said averaged response M and said target sound signature response Cec; - Analysis of the Cdiff curve resulting from the difference between said averaged response M and said target response Cec; and - determining filter parameters for reducing the difference between said averaged response M and said target response Cecen first processing the local maxima in decreasing order according to their gain, then the local minima, and performing successive iterations; said method further comprising a step of optimizing the parameters of the filters to improve the performance of the system. Thus, the method according to the present invention makes it possible to obtain automated acoustic equalization thanks to a precise and optimized calculation of filter parameters.
    [0008] Preferably, the interpolation step of the target sound signature curve is performed using the Hermite method. Advantageously, said method further comprises a step of automatic optimization of the offset of the target response Cec, repeated at each iteration. Advantageously, said method further comprises a step of smoothing the N frequency responses.
    [0009] Preferably, said method implements filters corresponding to the following types: "peak", "notch" "high-shelf" and "low-shelf" depending on the shape of local maxima and local minima.
    [0010] According to a particular mode of implementation, said method furthermore implements a global optimization algorithm to minimize the error. The present invention also relates to an automated acoustic equalization system, characterized in that it comprises means for: - measuring N impulse responses RI1, RI2, ..., RIN after transmission of a precalibrated sound signal received by N microphones; calculating the N corresponding frequency responses by Fast Fourier Transform; - establish an average M of N frequency responses; to translate into a logarithmic frequency scale said average M of the N frequency responses; interpolating a target curve Cec from a number of points defined by a user; translating into a logarithmic frequency scale said target curve C i - comparing said averaged response M and said target response C e, by calculating the difference between said averaged response M and said target response C e; analyzing the curve Cdiff resulting from the difference between said averaged response M and said target response Cec; and - determining filter parameters for reducing the difference between said averaged response M and said target response Cecen first processing the local maxima in descending order according to their gain, then the local minima, and performing successive iterations; said method further comprising means for optimizing filter parameters to improve system performance.
    [0011] BRIEF DESCRIPTION OF THE DRAWINGS The invention will be better understood by means of the following description, given for purely explanatory purposes, of one embodiment of the invention, with reference to the figures in which: FIG. the different steps of the process according to the present invention; FIG. 2 represents the target sound signature curve Cec within the meaning of the present invention, the frequency responses derived from the N impulse response measurements, as well as the average M; and - Figure 3 illustrates the detection and ranking of local maxima ("peaks") and local minima ("troughs").
    [0012] DETAILED DESCRIPTION OF THE EMBODIMENTS OF THE INVENTION FIG. 1 illustrates the different steps of the method according to the present invention. The automated acoustic equalization method according to the present invention comprises the following steps: In a first step, N impulse responses RI1, RI2, RIN are measured after transmission of a precalibrated sound signal received by N microphones. Then the corresponding N frequency responses are computed by Fast Fourier Transform. Then, an average M of the N calculated frequency responses is established. A logarithmic frequency scale translation of said average M of the N frequency responses is performed. A target sound signature curve Cc is interpolated and then translated into a logarithmic frequency scale. Next, the averaged response M and the target sound signature response C e are compared by calculating the difference between the averaged response M and the target response C e. The curve Cdiff resulting from the difference between said averaged response M and said target response Cc is analyzed. Finally, filter parameters are determined for the reduction of the difference between said averaged response M and said target response Cecen first processing the local maxima in descending order according to their gain, then the local minima, and performing iterations. successive. The method according to the present invention further comprises a step of optimizing the parameters of the filters in order to improve the performance of the system.
    [0013] Frequency responses can be averaged "standard" (that is, with identical weights), or with different weights.
    [0014] FIG. 2 represents the target sound signature curve Cec within the meaning of the present invention, the frequency responses derived from the N impulse response measurements, as well as the average M. In the context of the present invention, a comparison is made of the M averaged response and the target response Cec, calculating the difference between the averaged response M and the target response Cec. Figure 3 illustrates the detection and ranking of local maxima ("peaks") and local minima ("troughs"). In accordance with the present invention, the local maxima (peaks) are first processed in descending order according to their gain, then the local minima (troughs) are processed in ascending order. This makes it possible to determine filter parameters for reducing the difference between the averaged response M and the target response Cec. Successive iterations are performed.
    [0015] It has been shown in scientific studies that it is better to first equalize the peaks, then the troughs. Indeed, the human ear is more sensitive to peaks than hollows. In one embodiment, optimization of the offset of the target curve is performed as follows: The target curve and the average frequency response are recalculated on a logarithmic scale to approximate the nonuniform resolution of the auditory system. This is achieved by a smoothing function that resamples the frequency response on a logarithmic scale with for example a 1/48 octave frequency resolution. i) The "FreqRange" optimization frequency band is applied as a FreqWeight weight vector that is 0 outside the frequency band and 1 within the frequency band. ii) The initial Offset value (in dB) is calculated as the average value of the average frequency response in the equalization frequency band: Offset = mean (Ce, (nl: nf)) where neither and nf are respectively the first and the last of the frequency points of the logarithmic equalization frequency band. iii) The optimization algorithm consists in finding the optimal offset, Offset, which minimizes the error between M and Cc (= Shape + Offset), defined as follows: nf emean = 1 nf - ni + 1 IM (fk Ceak) k = ni With Cec = Offset + Shape This is done with the optimization algorithm, which iteratively calculates the emean error, and looks for the optimal offset within +/- 100 dB around the initial value.
    [0016] In addition to minimizing the emean error, a constraint is added to the optimization problem, in order to limit the gain of the peaks to Gmax in dB. It is defined as follows: max I M (fk) - Ce, (fk) I <Gmax Parameters and number of filters are optimized by means of an algorithm. The parameters f, Q and G (respectively central frequency, quality factor and gain of the biquads) are optimized from intervals of values that can be predefined by a user, and the ranges of values of Q and G may depend on frequency. Thus, for example in high frequencies, the low gain filters are more easily eliminated because they are not perceptible.
    [0017] In one embodiment, the objective is to find the optimal parameters (fcopt, Gopt, Qopt) of a filter and the optimal offset of the target curve Offsetopt The limits of the parameters are determined as follows: If lc 1 max 1, FreqRange (1) <fcop, <min fc X 2I, FreqRange (2) 2I l -G x 0.9 <Gopt <G x 1.1 if G <0 and - G x 1.1 <Gopt <G x 0.9 if G> 0 QRange (1) <(2 0pt <QRange (2) TargetGain - 100 <TargetGainopt <TargetGain + 100 where fc and G are respectively the center frequency and the gain of a biquad filter modeling the nth peak, and QRange is the range Q value factor is a post-optimization process, this post-optimization process consists of reclassifying the filters by increasing frequency and reoptimizing the coefficients.If a filter is canceled during this process, a new peak / trough is searched in order to output the maximum number of filters The optimization process is implemented j until the maximum number of filters is reached.
    [0018] In one embodiment, the interpolation step of the target curve is performed using the Hermite method. In one embodiment, the method according to the present invention further comprises a step of automatic optimization of the offset of the target response Cec, repeated at each iteration. In one embodiment, the method according to the present invention further comprises a step of smoothing the N frequency responses.
    [0019] In the context of the process according to the present invention, filters corresponding to the following types are used: "peak", "notch" "high-shelf" and "low-shelf" depending on the shape of the local maxima (peaks) and local minima (hollow). In some cases, it is better to choose a peak type filter.
    [0020] In other cases, it is better to choose a "shelf" filter. The selection of the filter is made according to whether or not a certain threshold is exceeded by the quality factor. In one embodiment, the method according to the present invention furthermore implements a global optimization algorithm to minimize the error. The present invention also relates to an automated acoustic equalization system, comprising means for: measuring N impulse responses RI1, RI2, RIN after emission of a precalibrated sound signal received by N microphones; calculating the N corresponding frequency responses by Fast Fourier Transform; - establish an average M of N frequency responses; to translate into a logarithmic frequency scale said average M of the N frequency responses; interpolating a target curve Cec from a number of points defined by a user; translating into a logarithmic frequency scale said target curve C i - comparing said averaged response M and said target response C e, by calculating the difference between said averaged response M and said target response C e; analyzing the curve Cdiff resulting from the difference between said averaged response M and said target response Cec; and - determining filter parameters for reducing the difference between said averaged response M and said target response Cecen first processing the local maxima in descending order according to their gain, then the local minima, and performing successive iterations; said system further comprising means for optimizing filter parameters to improve system performance.
    [0021] The invention is described in the foregoing by way of example. It is understood that the skilled person is able to realize different variants of the invention without departing from the scope of the patent.
    权利要求:
    Claims (7)
    [0001]
    REVENDICATIONS1. Automated acoustic equalization method, characterized in that it comprises the following steps: measurement of N impulse responses RI1, RI2, RIN after emission of a precalibrated sound signal received by N microphones; - Calculation of N corresponding frequency responses by Fast Fourier Transform; - Establishment of an average M of N frequency responses; - Logarithmic frequency scale translation of said average M of the N frequency responses; - Interpolation of a target sound signature curve Cec from a number of points chosen by a user; - logarithmic frequency scale translation of said target sound signature curve Cec; Comparing said averaged response M and said target response Cec, by calculating the difference between said averaged response M and said target sound signature response Cec; - Analysis of the Cdiff curve resulting from the difference between said averaged response M and said target response Cec; and - determining filter parameters for reducing the difference between said averaged response M and said target response Cecen first processing the local maxima in decreasing order according to their gain, then the local minima, and performing successive iterations; said method further comprising a step of optimizing the parameters of the filters to improve the performance of the system.
    [0002]
    An automated acoustic equalization method according to claim 1, characterized in that the step of interpolating the target sound signature curve is performed by means of the Hermite method.
    [0003]
    3. A method of automated acoustic equalization according to claim 1 or 2, characterized in that it further comprises a step of automatic optimization of the offset of the target response Cec, repeated at each iteration.
    [0004]
    4. A method of automated acoustic equalization according to claim 1, 2 or 3, characterized in that it further comprises a step of smoothing the N frequency responses.
    [0005]
    5. A method of automated acoustic equalization according to at least one of the preceding claims, characterized in that it implements filters corresponding to the following types: "peak", "notch" "high-shelf" and "low- shelf "according to the shape of local maxima and local minima.
    [0006]
    6. Acoustic acoustic equalization method according to at least one of the preceding claims, characterized in that it also implements a global optimization algorithm to minimize the error.
    [0007]
    7. automated acoustic equalization system, characterized in that it comprises means for: - measuring N impulse responses RI1, RI2, ..., RIN after emission of a precalibrated sound signal received by N microphones; calculating the N corresponding frequency responses by Fast Fourier Transform; - establish an average M of N frequency responses; to translate into a logarithmic frequency scale said average M of the N frequency responses; interpolating a target curve Cec from a number of points defined by a user; translating into a logarithmic frequency scale said target curve Cc, comparing said averaged response M and said target response Cc, by calculating the difference between said averaged response M and said target response Cc1; analyzing the curve Cdiff resulting from the difference between said averaged response M and said target response Cec; and - determining filter parameters for reducing the difference between said averaged response M and said target response Cecen first processing the local maxima in descending order according to their gain, then the local minima, and performing successive iterations; said system further comprising means for optimizing filter parameters to improve system performance.
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    优先权:
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    FR1451504A|FR3018015B1|2014-02-25|2014-02-25|AUTOMATED ACOUSTIC EQUALIZATION METHOD AND SYSTEM|FR1451504A| FR3018015B1|2014-02-25|2014-02-25|AUTOMATED ACOUSTIC EQUALIZATION METHOD AND SYSTEM|
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