Parameter determination method, parameter determination apparatus and program

Abstract

To provide a sound processing method that reduces a load of work required for a user.SOLUTION: A parameter determination method that determines a parameter of a filter outputting a second sound signal in which a frequency characteristic is changed for a first sound signal comprises: calculating a first acoustic feature amount of the first sound signal; calculating a second acoustic feature amount of the second sound signal; and determining the parameter of the filter for a difference of a specific acoustic feature amount associated with audibility, of the first acoustic feature amount and the second acoustic feature amount to be less than or equal to a predetermined value.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] An embodiment of the present invention relates to a parameter determination method, a parameter determination device, and a program. [Background technology]

[0002] Patent Document 1 describes a digital mixer that allows multiple channels and multiple parameters to be displayed / operated / changed simultaneously. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-77497 A Summary of the Invention [Problem to be solved by the invention]

[0004] A user (e.g., an operator of an audio mixer) had to determine the filter processing parameters as pre-settings.

[0005] An object of one embodiment of the present invention is to provide a sound processing method that reduces the workload required of a user. [Means for solving the problem]

[0006] A parameter determination method according to one embodiment of the present invention is a parameter determination method for determining parameters of a filter that outputs a second sound signal having a changed frequency characteristic with respect to a first sound signal, the method comprising the steps of: calculating a first acoustic feature of the first sound signal; calculating a second acoustic feature of the second sound signal; and determining the parameters of the filter such that a difference between a specific acoustic feature related to audibility between the first acoustic feature and the second acoustic feature is equal to or smaller than a predetermined value. Effect of the Invention

[0007] According to one embodiment of the present invention, it is possible to reduce the workload required of a user. [Brief description of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a hardware configuration of an audio mixer 1. FIG. [Diagram 2] FIG. 2 is a diagram showing the functional configuration of a signal processing block. [Diagram 3] 1 is a flowchart showing a method for determining filter parameters. [Figure 4] 13 is a flowchart showing a filter parameter determination method according to Modification 1. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Fig. 1 is a block diagram showing the hardware configuration of the audio mixer 1. Fig. 2 is a diagram showing the functional configuration of the signal processing block of the audio mixer 1.

[0010] The audio mixer 1 is an example of a parameter determination device of the present invention. The audio mixer 1 inputs a sound signal from an audio device such as a microphone or a musical instrument. The audio mixer 1 performs signal processing such as mixing or effects on the input sound signal. The audio mixer 1 transmits the processed sound signal to an audio device such as a speaker.

[0011] The audio mixer 1 includes a touch panel display 101, an operation unit 102, an audio I / O (Input / Output) 103, a signal processing unit (DSP) 104, a network I / F (interface) 105, a USB I / F 106, a CPU 107, a flash memory 108, and a RAM 109. These components are connected via a bus 210.

[0012] CPU 107 is a control unit that controls the operation of audio mixer 1. CPU 107 performs various operations by reading a program stored in flash memory 108, which is a storage medium, into RAM 109 and executing the program. Note that the program does not need to be stored in flash memory 108 of the device itself. For example, the program may be downloaded each time from another device such as a server and read into RAM 109.

[0013] The CPU 107 inputs and outputs audio signals at the audio I / O 103, controls the mixing process in the signal processing unit 104, controls the effect process, and changes the values ​​of parameters related thereto.

[0014] Touch panel display 101 is composed of, for example, an LCD (Liquid Crystal Display) and a touch panel laminated on the LCD. Touch panel display 101 displays various information under the control of CPU 107. Touch panel display 101 also accepts operations from the user.

[0015] The operation unit 102 includes various operators such as switches, knobs, faders, etc., and receives operations on the audio mixer 1 from a user.

[0016] The signal processing unit 104 is composed of a DSP (Digital Signal Processor) for performing various signal processing such as mixing processing, effect processing, etc. The signal processing unit 104 performs signal processing such as mixing processing, effect processing, etc. on the sound signal input from the audio I / O 103, the network I / F 105, or the USB I / F 106. The signal processing unit 104 outputs the processed sound signal via the audio I / O 103, the network I / F 105, or the USB I / F 106.

[0017] 2, the signal processing block 901 is composed of an input channel 951, a bus 952, and an output channel 953. In this example, the input channel 951 has eight channels (1-8). The bus 952 has various buses such as a stereo bus, a MIX bus, and a MATRIX bus. The output channel 953 is a block that processes the sound signals sent from each bus.

[0018] Each channel of the input channels 951 performs signal processing such as high-pass filtering, low-pass filtering, equalization, or compression on the input sound signal. Each channel of the input channels 951 outputs the processed sound signal to a downstream bus 952. The level of the sound signal output by the input channel is adjusted by an operator such as a fader.

[0019] The bus 952 mixes the audio signals sent from each input channel and outputs the mixed signal to the output channel 953 .

[0020] The output channel 953 applies effect processing such as an equalizer or a compressor to the input sound signal. The sound signal after the signal processing is supplied to the audio I / O 103, the network I / F 105, or the USB I / F 106.

[0021] That is, the signal processing block 901 functions as a filter that outputs a second sound signal obtained by changing the frequency characteristics of the first sound signal.

[0022] The above signal processing is controlled based on the values ​​of various parameters. CPU 107 stores the current values ​​(current data) of various parameters in RAM 109. CPU 107 updates the current data when the user operates touch panel display 101 or operation unit 102.

[0023] 3 is a flowchart showing a method for determining parameters of the filter, among the operations of the CPU 107. The CPU 107 calculates a first acoustic feature of a first sound signal (S11), and calculates a second acoustic feature of a second sound signal (S12). Then, the CPU 107 determines parameters of the filter such that a difference between a specific acoustic feature related to auditory sensation, between the first acoustic feature and the second acoustic feature, is equal to or smaller than a predetermined value (S13).

[0024] The filter is, for example, a high-pass filter or a low-pass filter, and the parameter determined by the CPU 107 is the cutoff frequency. The cutoff frequency of the high-pass filter and the low-pass filter must be appropriately set according to the acoustic characteristics of the audio device that outputs the first sound signal. For example, a high-pass filter is used to remove unnecessary low-frequency sounds, such as hum noise of an electric instrument, background noise in the surrounding environment, or wind or breathing noise (pop noise) for a microphone. The higher the cutoff frequency of the high-pass filter, the more unnecessary low-frequency sounds can be removed, but the main band of each audio device is also removed, which increases the impact on hearing. The user sets an appropriate cutoff frequency that removes unnecessary low-frequency sounds and suppresses the impact on hearing according to the acoustic characteristics of the audio device.

[0025] Furthermore, the audio mixer 1 has multiple (eight in this embodiment) input channels. Therefore, the user needs to appropriately set the cutoff frequencies of the high-pass filters and low-pass filters of each of the multiple input channels according to the acoustic characteristics of the audio equipment for each channel. The user (e.g., the operator of the audio mixer) needs to determine the cutoff frequencies of all channels as a pre-setting, which imposes a very heavy workload.

[0026] The parameter determination method of the present embodiment determines the cutoff frequency by the above-mentioned processes of S11 to S13, thereby reducing the workload of the user. The CPU 107 calculates a first acoustic feature of the first sound signal and calculates a second acoustic feature of the second sound signal. The first acoustic feature and the second acoustic feature are, for example, frequency characteristics, and more specifically, are a spectral centroid or a spectral envelope.

[0027] For example, CPU 107 converts the sound signal into a frequency axis by a short-time Fourier transform, and acquires an amplitude spectrum of the sound signal. Calculation unit 52 averages the amplitude spectrum for a specific period, and acquires an average spectrum. Calculation unit 52 removes a bias (zeroth-order component of the cepstrum), which is an energy component, from the average spectrum, and acquires a spectral envelope. Either the averaging in the time axis direction or the removal of the bias may be performed first. That is, CPU 107 may first remove the bias from the amplitude spectrum, and then acquire the average spectrum averaged in the time axis direction as the spectral envelope. CPU 107 calculates the spectral center of gravity by dividing a value obtained by weighting the entire spectral envelope by frequency, by the entire spectral envelope. In the process of S11, the CPU 107 calculates, as a first acoustic feature of the first sound signal, for example, a first spectral centroid S1. In the process of S12, the CPU 107 calculates, as in S11, as a second acoustic feature of the second sound signal, for example, a second spectral centroid S2.

[0028] In the process of S13, the CPU 107 obtains a cutoff frequency such that the ratio (S2 / S1) of the first spectrum centroid S1 and the second spectrum centroid S2 becomes a predetermined value. The predetermined value is a value (slightly larger than 1) that does not significantly change the auditory sensation and can cut unnecessary low tones.

[0029] As described above, in a high-pass filter, the higher the cutoff frequency, the more unnecessary low frequencies can be cut, but the greater the impact on the sense of hearing. In a high-pass filter, the higher the cutoff frequency, the higher the spectral centroid, and therefore the higher the value of the ratio (S2 / S1) between the first spectral centroid S1 and the second spectral centroid S2. Therefore, such a ratio of spectral centroids (S2 / S1) is an example of a specific acoustic feature related to the sense of hearing. The CPU 107 calculates the ratio (S2 / S1) between the first spectral centroid S1 and the second spectral centroid S2 every time a specific period of time elapses, and updates the cutoff frequency using a predetermined algorithm such as LMS (Least Mean Square) or RLS (Recursive Least-Squares) so that the value of the ratio approaches a predetermined value (e.g., 1.02).

[0030] Alternatively, in the process of S13, the CPU 107 may obtain a cutoff frequency such that the ratio between the spectral envelope of the first sound signal and the spectral envelope of the second sound signal becomes a predetermined value. The higher the cutoff frequency, the higher the value of the ratio between the spectral envelope of the first sound signal and the spectral envelope of the second sound signal. Therefore, such a ratio of the spectral envelopes is also an example of a specific acoustic feature related to the auditory sensation. The CPU 107 may calculate the ratio between the spectral envelope of the first sound signal and the spectral envelope of the second sound signal every time a certain period of time elapses, and update the cutoff frequency using a predetermined algorithm so that the value of the ratio approaches a predetermined value.

[0031] CPU 107 updates the current data with the cutoff frequency of the determined high-pass filter (S14). Thereafter, signal processing in signal processing block 901 is performed based on the current data updated by CPU 107. That is, the filter in signal processing block 901 performs sound processing to change the frequency characteristics of the first sound signal with the parameters determined by CPU 107 and output a second sound signal.

[0032] As a result, the parameter determination method of the present embodiment can automatically set the parameters of various filters such as high-pass filters so as not to significantly change the auditory sensation. Therefore, the workload required of the user is reduced. In particular, in the case of an audio mixer having many channels, the workload of determining the cutoff frequencies of many channels is significantly reduced, so that the user can have a customer experience of realizing advance settings in an extremely short time, which was not possible in the past.

[0033] (Variation 1) Fig. 4 is a flowchart showing a filter parameter determination method according to Modification 1. The same components as those in Fig. 3 are given the same reference numerals and their description will be omitted. CPU 107 displays the determined cutoff frequency of the high-pass filter on touch panel display 101 (S104).

[0034] In this case, the user refers to the cutoff frequency of each channel displayed on touch panel display 101 and sets the cutoff frequency by operating touch panel display 101 or operation unit 102. The user can set the cutoff frequency determined by CPU 107 as is, or can change and set the cutoff frequency determined by CPU 107. For example, the user can reflect the automatic determination of parameters by CPU 107, or can adjust the parameters according to his or her own preferences.

[0035] (Variation 2) The CPU 107 according to the second modification determines the parameters by using a trained model that trains the relationship between the first acoustic feature amount, the second acoustic feature amount, and the filter parameters.

[0036] The first acoustic feature is, for example, the first spectral centroid as described above, and the second acoustic feature is, for example, the second spectral centroid.

[0037] In the training stage, the audio mixer 1 acquires a large number of data sets (training data) including the first spectral centroid, the second spectral centroid, and the parameter of the cutoff frequency of the high-pass filter. The audio mixer 1 trains the relationship between the first spectral centroid, the second spectral centroid, and the parameter of the cutoff frequency of the high-pass filter using a predetermined algorithm in a predetermined training model.

[0038] The algorithm for training the training model is not limited, and any machine training algorithm such as CNN (Convolutional Neural Network) or RNN (Recurrent Neural Network) can be used. The machine training algorithm may be supervised training, unsupervised training, semi-supervised training, reinforcement training, inverse reinforcement training, active training, transfer training, or the like. Furthermore, the calculation unit 52 may train the training model using a machine training model such as HMM (Hidden Markov Model) or SVM (Support Vector Machine).

[0039] The appropriate cutoff frequency has an optimal value for removing unnecessary low tones and suppressing the influence on the sense of hearing. In other words, the first spectrum centroid, the second spectrum centroid, and the cutoff frequency have a correlation. Therefore, the audio mixer 1 can train a predetermined training model on the relationship between the first spectrum centroid, the second spectrum centroid, and the parameters of the cutoff frequency of the high-pass filter, and generate a trained model.

[0040] In the initial stage, the audio mixer 1 inputs a first acoustic feature (first spectral centroid) of a first sound signal and a second acoustic feature (second spectral centroid) of a second sound signal to a trained model, and outputs a parameter of the cutoff frequency of the corresponding high-pass filter.

[0041] In this way, the parameter determination method of this embodiment can determine parameters for various filters, such as high-pass filters, that do not significantly change the auditory sensation, using a trained model that has been trained based on settings previously made by the user.

[0042] The description of the present embodiment should be considered as illustrative in all respects and not restrictive. The scope of the present invention is indicated by the claims, not by the above-described embodiments. Furthermore, the scope of the present invention includes the scope equivalent to the claims. [Explanation of symbols]

[0043] 1: audio mixer, 52: calculation unit, 101: touch panel display, 102: operation unit, 103: audio I / O, 104: signal processing unit, 105: network I / F, 107: CPU, 108: flash memory, 109: RAM, 210: bus, 901: signal processing block, 951: input channel, 952: bus, 953: output channel

Claims

1. A parameter determination method for determining parameters of a filter that outputs a second sound signal obtained by changing a frequency characteristic of a first sound signal, the method comprising the steps of: Calculating a first acoustic feature of the first sound signal; Calculating a second acoustic feature of the second sound signal; determining the parameters of the filter such that a difference between a specific acoustic feature related to audibility among the first acoustic feature and the second acoustic feature is equal to or smaller than a predetermined value; Parameter determination method.

2. The specific acoustic feature includes a spectral centroid, determining the parameters such that a ratio of a first spectral centroid of the first acoustic feature and a second spectral centroid of the second acoustic feature becomes a predetermined value; The parameter determination method according to claim 1 .

3. The specific acoustic feature includes a spectral envelope, determining the parameters such that a ratio between a first spectral envelope of the first acoustic feature and a second spectral envelope of the second acoustic feature becomes a predetermined value; The parameter determination method according to claim 1 .

4. Displaying the determined parameters. The parameter determination method according to any one of claims 1 to 3.

5. the filter performs sound processing to change a frequency characteristic of the first sound signal using the determined parameters and output the second sound signal. The parameter determination method according to any one of claims 1 to 3.

6. determining the parameters using a trained model that trains a relationship between the first acoustic feature, the second acoustic feature, and the parameters of the filter; The parameter determination method according to any one of claims 1 to 3.

7. the filter is a high-pass filter or a low-pass filter, The parameters include a cutoff frequency. The parameter determination method according to any one of claims 1 to 3.

8. A parameter determination device including a processor for determining a parameter of a filter that outputs a second sound signal obtained by changing a frequency characteristic of a first sound signal, The processor, Calculating a first acoustic feature of the first sound signal; Calculating a second acoustic feature of the second sound signal; determining the parameters of the filter such that a difference between a specific acoustic feature related to audibility among the first acoustic feature and the second acoustic feature is equal to or smaller than a predetermined value; Parameter determination device.

9. The specific acoustic feature includes a spectral centroid, the processor determines the parameters such that a ratio of a first spectral centroid of the first acoustic feature and a second spectral centroid of the second acoustic feature becomes a predetermined value. The parameter determination device according to claim 8.

10. The specific acoustic feature includes a spectral envelope, The processor determines the parameters such that a ratio between a first spectral envelope of the first acoustic feature and a second spectral envelope of the second acoustic feature becomes a predetermined value. The parameter determination device according to claim 8.

11. The processor displays the determined parameters on a display. The parameter determination device according to any one of claims 8 to 10.

12. the filter performs sound processing to change a frequency characteristic of the first sound signal using the determined parameters and output the second sound signal. The parameter determination device according to any one of claims 8 to 10.

13. The processor determines the parameters using a trained model that trains a relationship between the first acoustic feature, the second acoustic feature, and the parameters of the filter. The parameter determination device according to any one of claims 8 to 10.

14. the filter is a high-pass filter or a low-pass filter, The parameters include a cutoff frequency. The parameter determination device according to any one of claims 8 to 10.

15. A program for causing an information processing device to execute a process of determining parameters of a filter that outputs a second sound signal obtained by changing a frequency characteristic of a first sound signal, Calculating a first acoustic feature of the first sound signal; Calculating a second acoustic feature of the second sound signal; determining the parameters of the filter such that a difference between a specific acoustic feature related to audibility among the first acoustic feature and the second acoustic feature is equal to or smaller than a predetermined value; A program for causing the information processing device to execute processing.

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