CN112116914A - Sound processing method and system based on variable step length LMS algorithm - Google Patents
Sound processing method and system based on variable step length LMS algorithm Download PDFInfo
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Abstract
The invention discloses a sound processing method and a sound processing system based on a variable step length LMS algorithm, wherein the sound processing method comprises the following steps: s1, calculating a gain g (n) at the current time, where the gain g (n) is calculated by the following formula: g (n-1) + u (n-1) e (n-1) Px(n-1); wherein, Px(n-1) is the power value of the sound input signal at the previous moment, u (n-1) is the step factor of the previous moment, e (n-1) is the error value of the previous moment, g (n-1) is the gain value of the previous moment, and n is the serial number of the sound input signal at the current moment; s2, gain processing is carried out to the sound input signal x (n) at the current moment according to the gain value obtained by calculation to obtain the output signal y (n), and the output signal y (n) is calculated to be y (n) (g) (n) x (n)And the uncomfortable feeling of the auditory sense is reduced.
Description
Technical Field
The invention relates to a sound signal processing technology, in particular to a voice signal processing method and system based on an adaptive algorithm.
Background
In the process of acquiring and outputting the sound signal, signal processing is generally required. One of the most common processing means is to perform gain control processing on the audio signal to achieve balanced output of the audio signal. At present, most AGC algorithms are used and are based on an algorithm of energy comparison, the maximum amplitude of a signal in a nearest time slice is searched, and if the searched power value of the current frame is larger than the existing maximum power value, the maximum power value is updated; according to the searched maximum power value, comparing with a preset expected value to obtain an expected gain; calculating the actual gain of the current frame by using a first-order recursive smoothing filter according to the expected gain of the current frame and the actual gain of the previous frame; and finally, multiplying all the sampling points of the current frame by the gain value to obtain the output signal of the current frame. Although the AGC algorithm used at present can prevent the overload phenomenon of the speech signal, linear distortion is generated when the speech is suddenly changed, because the algorithm does not consider the situation that the power variation range of the speech signal in each frame may be wide, and the same processing mode for the upper and lower flow signals and the linear area signal increases the processing error.
In addition, adaptive LMS, NMLS, RLS and other algorithms are also gradually applied in the sound signal processing, however, there are also problems that the error generated by linear distortion is large when the voice suddenly changes, the voice signal adjusting speed is slow, even the delay is delayed, so that the hearing comfort of the listener is not ideal.
Disclosure of Invention
The present invention aims to solve the above problems, and provide an improved sound processing method and system based on a variable step LMS algorithm, which can effectively avoid a large error caused by linear distortion when a voice suddenly changes, so that the voice signal adjustment speed is fast, the voice can be kept in a certain amplitude range, and the hearing comfort of a listener is improved.
One of the purposes of the present invention is to provide a sound processing method based on a variable step length LMS algorithm, which comprises the following steps:
s1, calculating a gain g (n) at the current time, where the gain g (n) is calculated by the following formula:
g(n)＝g(n-1)+u(n-1)*e(n-1)*Px(n-1)；
wherein ,Px(n-1) is the power value of the sound input signal at the previous moment, u (n-1) is the step factor at the previous moment, e (n-1) is the error value at the previous moment, g (n-1) is the gain value at the previous moment, n is the serial number of the sound input signal at the current moment, n is a positive integer, and n is more than or equal to 2;
s2, gain processing is carried out to the sound input signal x (n) at the current time according to the gain value obtained by calculation to obtain an output signal y (n),
y(n)＝g(n)*x(n)。
preferably, the method further comprises the following steps:
s3, calculating power value P of sound input signal at current momentx(n), a step size factor u (n) at the current time, and an error value e (n) at the current time;
s4, iteratively calculating a gain value g (n +1) at the next time, wherein the calculation formula is g (n +1) ═ g (n) + u (n) · e (n) × Px(n)；
S5, the audio input signal x (n +1) at the next time is subjected to gain processing based on the gain value g (n +1) to obtain the audio output signal y (n +1) at the next time, and the calculation formula is y (n +1) ═ g (n +1) × (n + 1).
Preferably, the power value P of the voice input signal at the current momentxThe calculation formula of (n) is:
Px(n)＝λPx(n-1)+(1-λ)x2(n)，
wherein, λ is a smoothing factor, x2(n) is the square of the audio input signal x (n) at the current time.
Preferably, the step-size factor u (n) at the current time is calculated by:
wherein ,
or ,
in the above-mentioned formula, the compound of formula,
a (n-1) is the square value of the gradient at the previous moment, the value range of beta is more than 0 and less than 1, the value range of theta is more than 0 and less than 1, Py(n-1) is the power value of the sound output signal at the previous moment, P2 x(n) is the power value P of the voice input signal at the current momentxThe square of (n).
Preferably, the sound output signal power PyThe calculation formula of (n) is:
Py(n)＝g(n)*g(n)*Px(n)。
preferably, error value e (n) ═ P at the current time is setexp-Py(n)，PexpTo a desired value, PexpThe value range is more than 0 and less than Pexp＜1。
The invention also discloses a sound processing system based on the variable step LMS algorithm, which comprises:
a signal input unit for acquiring a sound input signal;
a gain control processing unit for calculating the gain value of the voice input signal at the current time and calculating the output signal according to the calculated gain value,
a signal output unit which performs gain processing on the voice input signal according to the calculated output signal and outputs the voice signal after the gain processing;
the signal parameter calculation unit comprises a power calculation module for calculating the power value of the sound input signal at the current moment, an error calculation module for calculating the error value between the expected power value of the sound output signal and the power value of the sound output signal after gain processing, and a step length calculation module for calculating the step length factor at the current moment;
the storage unit is used for storing the calculation process data and providing the gain control processing unit for calling;
the formula of the gain control processing unit for calculating the gain value is as follows:
g(n)＝g(n-1)+u(n-1)*e(n-1)*Px(n-1)
wherein ,Px(n-1) is the power value of the sound input signal at the previous moment, u (n-1) is the step factor at the previous moment, e (n-1) is the error value at the previous moment, g (n-1) is the gain value at the previous moment, n is the serial number of the sound input signal at the current moment, n is a positive integer, and n is more than or equal to 2;
the output signal is calculated as:
y (n) ═ g (n) × (n), where x (n) is the current time voice input signal.
Compared with the prior art, the remarkable progress of the invention is at least reflected in that: the sound processing based on the improved LMS algorithm provided by the invention can reduce the amplitude of a large signal and amplify a small signal, so that the amplitude of the whole speech is kept relatively consistent, the transition zone is small, and the sound gain speed is high. The gain value can quickly respond according to the change amplitude of the sound signal, and when the sound amplitude changes suddenly, the gain value can also be changed quickly, so that the effect of slow amplification or amplitude reduction is effectively avoided, and the sense of discomfort of hearing is reduced.
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FIG. 1 is a schematic diagram illustrating an algorithm derivation process in a sound processing method according to an embodiment of the present invention;
FIG. 2 is a time domain comparison graph of an input signal and an output signal according to an embodiment of the present invention;
FIG. 3 is a graph reflecting input speech and gain curves according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating a sound processing method according to an embodiment of the invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings and specific examples. It should be noted that the embodiments of the present invention are not limited to the examples provided.
The embodiment of the invention provides a sound processing method based on a variable step length LMS algorithm, which comprises the following steps:
s1, calculating a gain g (n) at the current time, where the gain g (n) is calculated by the following formula:
g(n)＝g(n-1)+u(n-1)*e(n-1)*Px(n-1)；
wherein ,Px(n-1) is the power value of the sound input signal at the previous moment, u (n-1) is the step factor at the previous moment, e (n-1) is the error value at the previous moment, g (n-1) is the gain value at the previous moment, n is the serial number of the sound input signal at the current moment, n is a positive integer, and n is more than or equal to 2;
in this embodiment, the gain value g (n) is used as the iteration weight of the variable step length LMS algorithm, and the value of g (n) is the power value P of the sound input signal passing the previous momentx(n-1), step size factor u (n-1), error value e (n-1), and gain value g (n-1).
S2, calculating output signal y (n)
According to the gain value obtained by calculation, the gain processing is carried out on the sound input signal x (n) at the current moment to obtain an output signal y (n), namely
y(n)＝g(n)*x(n)。
It is understood that the digital audio output signal sequence y (n) after the automatic gain control process is generated as a product of the input signal sequence x (n) and the gain parameter sequence g (n).
It will be appreciated that the iterative calculation of gain values from the second acoustic input signal is performed with the first acoustic input signal as an initial value and the gain processing performed on the corresponding acoustic input signal. The initial value setting includes: the initial gain value g (1) is 1, the step factor u (1) is 0, and the error value e (1) is Pexp-Px(1) Value of power Px(1)＝x2(1) And calculating a gain value of the second sound input signal according to the initial value.
Preferably, after the signal output is completed once, the processing of the input signal at the next time is performed, and the method specifically includes the steps of:
the gain value g (n +1) at the next time is iteratively calculated, and the calculation formula is g (n +1) ═ g (n) + u (n) × e (n) × Px(n)；
The audio input signal x (n +1) at the next time is subjected to gain processing based on the gain value g (n +1) to obtain an audio output signal y (n +1) at the next time, and the calculation formula is g (n +1) × x (n + 1).
In some embodiments, the power value P of the sound input signal at the current momentxThe calculation formula of (n) is:
Px(n)＝λPx(n-1)+(1-λ)x2(n)，
the lambda is a smoothing factor, the influence of the previous moment on the current moment is determined by the lambda value, the larger the lambda value is, the larger the influence of the previous moment is, the more gradual the power change is, and otherwise, the larger the power change is. Preferably, λ is recommended to be 0.9. x is the number of2(n) is the square of the audio input signal x (n) at the current time.
It should be noted that the value of the error value e (n) at the current time is the desired power value PexpWith the power value P of the output signal y (n) calculated after each iterationyThe difference between (n), i.e. e (n) ═ Pexp-Py(n)，PexpThe value range is more than 0 and less than PexpIf < 1, the value is suggested to be 0.2. In some embodiments, the sound output signal power calculated after each iteration is Py(n) the calculation formula is:
Py(n)＝g(n)*g(n)*Px(n)。
it is understood that, taking the processing of the speech signal as an example, in the processing of the speech signal, in order to keep the amplitude of the speech signal relatively consistent, the adjustment change of the speech signal needs a gain value for adjustment. For example, when the voice signal is small, the gain value is large, and when the voice signal is large, the gain value is small. In the embodiment of the invention, the adjustment of the gain value is iteratively adjusted through a variable-step LMS algorithm (least mean square), the input and output energy value of the signal is used as the input and output signals of the variable-step LMS algorithm, and the mechanism of the variable-step LMS algorithm is to perform adaptive iteration on the output signal which is continuously close to the expected value.
It can be further understood that the core idea of the LMS algorithm is to use the square error instead of the mean square error to calculate the gradient value of the current time point, the error signal is equivalent to a paraboloid in the two-dimensional graph, the lowest point is the minimum error point, the output signal is the expected signal at this time, the gradient value of each point on the paraboloid represents the magnitude of the error signal, the gradient amplitude is large in the initial stage, and is small and tends to 0 in the steady state. If the step value of the LMS algorithm with fixed step length is set to be too small, the signal convergence speed is too low, iteration is needed for many times to reach the minimum value point, if the step length is too large, the signal convergence speed is very high, but when the step length is close to an expected signal, an error signal always swings left and right at the bottom of a bowl on the performance surface due to the fact that the step length is too large, and a steady-state error is large. The fixed step LMS algorithm cannot equalize between the steady state error and the convergence speed. The variable-step LMS algorithm adopted in the embodiment of the invention can carry out iterative computation according to the current gradient value, and when the current iteration gradients are larger, the dithering is caused due to the overlarge step length, and the step length is reduced to reduce the dithering; when the gradient of the current rounds of iteration is small, the step length is increased to accelerate the iteration. Therefore, balance between the steady-state error and the convergence rate is achieved, and the calculation efficiency is improved.
It should be noted that, in a sudden change speech signal that is large and small in a period of time, how to quickly adjust the gain value of the signal is critical to avoid a large transition band of speech output. To achieve fast adjustment of the gain value, in some embodiments, the step size factor u (n) at the current time varies in real time according to the sampling point, and is calculated as:
wherein ,μ0The suggested value is 0.1 for the initial step length; the setting of e is to prevent the case that the denominator is 0, e can be set to be a very small positive number, and as an embodiment, the value of e is 10-6. The maximum value of the step length is mu according to the calculation formula of the step length factor0I e, the error goes to 0 as the desired value is approached. Correspondingly, the gain value calculation formula shows that the updated value of the gain also tends to 0, the gain is accelerated to be infinitely small, the iteration change is gradually reduced, and finally tends to 0, so that the optimal weight value is reached.
It can be understood that, in the scheme of this embodiment, in the current speech scene, when the gain change is aggressive and the gradient value is large, the step size is controlled to be relatively reduced to increase the stability, so as to avoid the occurrence of jitter due to an excessively large step size. And when the output signal is gradually close to the expected signal, the step length is properly increased, so that the convergence speed is increased. The problem that in a traditional mode of fixing the step length, when an error performance surface tends to be in a stable state, the step length is updated slowly along with the reduction of error change, and more iteration times are needed before the error performance surface approaches to a stable state but an optimal point is not reached is solved.
In order to improve the stability of gain, the consistency of the volume after the voice gain is kept, and the algorithm can have faster tracking performance when processing the sudden change of the volume. In the embodiment, the step length is adjusted by using historical gradient information, the aggressiveness of gain change is measured by introducing a historical gradient square value, and the aggressiveness is increased when the value is larger. In some embodiments of the present invention, the,
wherein ,
is composed of
The square of the square,
for error performance surface gradient values, it can be expressed as:
in order to record gradient information for a longer period of time, a value of 0.9 is suggested for beta. The LMS algorithm in this embodiment uses the square e of the instantaneous error2(n) instead of the mean square error, the gradient of the instantaneous error signal squared is taken as the estimate of the gradient of the mean square error function. The adaptation step size will get smaller and smaller over time if only the square root of the square of all historical gradients is used as the denominator. Therefore, in this embodiment, the average value of the past short time gradient is estimated by using the moving average, the gradient value can be smoothed, and if a local discontinuity occurs, the value of the square value a (n) of the gradient at the current time is obtainedThe gradient value a (n-1) of the previous moment with larger weight can be relied on, the sudden change of the step length can not be caused, and the problem that the speed of the self-adaptive step length decaying along with the time is too aggressive can be avoided. In this embodiment, since a (n) measures the average of the gradient of the previous period including the current time, the step size of the current point can be adjusted and controlled by using a (n) as the empirical information.
Considering that the historical gradient mean value inaccurate phenomenon of estimation may be generated in the early stage of iteration, the problem is solved by introducing bias correction as a preferred embodiment. The formula after adding the deviation correction is as follows:
where θ is greater than 0 and less than 1, θ is suggested to be 0.1, n is the serial number of the sound input signal at the current time, and is a positive integer, for example, if the sound input signal at the current time is the 3 rd sound input signal, n is 3.
Referring to fig. 1, it is shown that an algorithm derivation flowchart in the sound processing method according to the embodiment of the present invention is shown, as shown in the figure, a gain value g (n) is obtained by calculating a gain adaptive adjustment algorithm (i.e. a calculation formula of g (n) in step S1), and is obtained by calculating four paths of input data, where z-1 represents delaying an input signal, i.e. obtaining a signal parameter of a previous time point, i.e. obtaining a power value P of a sound input signal of the previous time pointx(n-1), the step factor u (n-1) at the previous moment, the error value e (n-1) at the previous moment and the gain value g (n-1) at the previous moment are calculated as calculation parameters to obtain the gain value g (n) at the current moment. Step size dynamic adjustment algorithm (i.e. calculation formula)
) Then the data is passed through two paths (i.e., e (n) and P)x(n)) are calculated. Finally, the gain value g (n) at the current moment obtained by calculation is multiplied by the sound input signal x (n) at the current moment to obtain an output signal y (n).
In order to verify the significant progress of the present invention, a section of voice signals with different amplitudes are input, and the voice gain processing is performed on the voice signals by the voice processing method based on the variable step LMS algorithm provided by the present invention, and referring to fig. 2 showing a comparison graph of the input signal and the output signal, it can be seen that after the adjustment processing is performed by the method of the present invention, the voice signal with a larger amplitude can be reduced, and the voice signal with a smaller amplitude can be amplified, so that the amplitude of the whole section of voice keeps relatively consistent, and the transition band is small, which indicates that the voice gain speed is faster.
Reference is made to FIG. 3, which shows a reflection of the input speech and gain curve at a sampling frequency of 16kHZ, at 2.3X 1053.3X 10 th5And (3) a small-amplitude voice segment range of the sampling points at the positions, wherein the upper graph is the original voice of the segment, and the lower graph is the gain value processed by the gain scheme. The overall amplitude of the original speech signal is small, but the relative amplitude variation is large. After the sound processing method based on the variable step length LMS algorithm is carried out, the gain value can quickly react according to the change amplitude of the voice, and the gain value can also be quickly changed when the voice amplitude changes suddenly. Therefore, the voice gain range of the voice processing method based on the variable step LMS algorithm is large, and the convergence rate of the new variable step LMS causes that the gain speed is changed quickly and the transition section from small voice to large voice is narrower when a section of jump voice is processed. Avoid the slow amplification or amplitude reduction effect and reduce the uncomfortable feeling of the auditory sense.
The embodiment of the invention also provides a sound processing system based on the variable step length LMS algorithm, which comprises:
the signal input unit is used for acquiring a sound input signal at the current moment;
a gain control processing unit for calculating the gain value of the voice input signal at the current time and calculating the output signal according to the calculated gain value,
a signal output unit which performs gain processing on the voice input signal according to the calculated output signal and outputs the voice signal after the gain processing;
the signal parameter calculation unit comprises a power calculation module for calculating the power value of the sound input signal at the current moment, an error calculation module for calculating the error value between the expected power value of the sound output signal and the power value of the sound output signal after gain processing, and a step length calculation module for calculating the step length factor at the current moment;
the storage unit is used for storing the calculation process data and providing the gain control processing unit for calling;
the formula of the gain control processing unit for calculating the gain value is as follows:
g(n)＝g(n-1)+u(n-1)*e(n-1)*Px(n-1)
wherein ,Px(n-1) is the power value of the sound input signal at the previous moment, u (n-1) is the step factor at the previous moment, e (n-1) is the error value at the previous moment, g (n-1) is the gain value at the previous moment, n is the serial number of the sound input signal at the current moment, the value is a positive integer, and n is more than or equal to 2;
the output signal is calculated as:
y (n) ═ g (n) × (n), where x (n) is the current time voice input signal.
It will be appreciated that the gain values are calculated iteratively starting from the second acoustic input signal, with the first acoustic input signal as an initial value. The initial value setting includes: the initial gain value g (1) is 1, the step factor u (1) is 0, and the error value e (1) is Pexp-Px(1) Value of power Px(1)＝x2(1) And calculating a gain value of the second sound input signal according to the initial value.
Preferably, the power value P of the voice input signal at the current momentxThe calculation formula of (n) is:
Px(n)＝λPx(n-1)+(1-λ)x2(n)，
wherein, lambda is a smoothing factor, and the suggested value is 0.9, x2(n) is the square of the audio input signal x (n) at the current time.
Preferably, the step-size factor u (n) at the current time is calculated by:
wherein ,
or ,
in the above-mentioned formula, the compound of formula,
a (n-1) is the gradient value of the previous moment, the value range of beta is more than 0 and less than 1, the suggested value is 0.9, the value range of theta is more than 0 and less than 1, the suggested value is 0.1, Py(n-1) is the power value of the sound output signal at the previous moment, P2 x(n) is the power value P of the voice input signal at the current momentxThe square of (n).
The value of the error value e (n) of the sampling point at the current time is the expected power value PexpWith the power value P of the output signal y (n) calculated after the iterative gainyThe difference between (n), i.e. e (n) ═ Pexp-Py(n)，PexpThe value range is more than 0 and less than PexpIf < 1, the value is suggested to be 0.2. In some embodiments, the sound output signal power calculated after each iteration of the gain is Py(n) the calculation formula is:
Py(n)＝g(n)*g(n)*Px(n)。
referring to fig. 4, in the sound processing system based on the variable step LMS algorithm according to the embodiment of the present invention, after parameter initialization is completed, VAD detection (silence detection) is performed to determine whether an input is a silence segment, if the input is the silence segment, a gain value is set to 1, otherwise, gain calculation processing is performed, after the gain value is determined, an output signal y (n) is calculated, and amplitude limiting processing is performed on the input signal according to the calculated y (n) to output a signal. It can be understood that when the signal processing needs to be continued, the power value P of the sound input signal at the current moment needs to be calculatedx(n), a step factor u (n), and an error value e (n), and iteratively calculates a gain value g (n +1) at the next time, wherein g (n +1) ═ g (n) + u (n) · e (n) × Px(n); further, the method can be used for preparing a novel materialThen, the audio input signal x (n +1) at the next time is subjected to gain processing based on the gain value g (n +1) to obtain the audio output signal y (n +1) at the next time, and the calculation formula is given as y (n +1) ═ g (n +1) × x (n + 1).
The embodiments of the present invention have been described in detail, but the embodiments are merely examples, and the present invention is not limited to the embodiments described above. Any equivalent modifications and substitutions to those skilled in the art are also within the scope of the present invention. Accordingly, equivalent changes and modifications made without departing from the spirit and scope of the present invention should be covered by the present invention.
Claims (10)
1. The sound processing method based on the variable step length LMS algorithm is characterized by comprising the following steps:
s1, iteratively calculating a gain g (n) at the current time, where the gain g (n) is calculated by the following formula:
g(n)＝g(n-1)+u(n-1)*e(n-1)*Px(n-1)；
wherein ,Px(n-1) is the power value of the sound input signal at the previous moment, u (n-1) is the step factor of the previous moment, e (n-1) is the error value of the previous moment, g (n-1) is the gain value of the previous moment, n is the serial number of the sound input signal at the current moment, n is a positive integer, and n is more than or equal to 2.
S2, gain-processing the audio input signal x (n) at the current time according to the calculated gain value to obtain an output signal y (n):
y(n)＝g(n)*x(n)。
2. the sound processing method based on the variable step LMS algorithm according to claim 1, further comprising the steps of:
s3, calculating power value P of sound input signal at current momentx(n), a step size factor u (n) at the current time, and an error value e (n) at the current time;
s4, iteratively calculating a gain value g (n +1) at the next time, wherein the calculation formula is g (n +1) ═ g (n) + u (n) · e (n) × Px(n)；
S5, the audio input signal x (n +1) at the next time is subjected to gain processing based on the gain value g (n +1) to obtain the audio output signal y (n +1) at the next time, and the calculation formula is y (n +1) ═ g (n +1) × (n + 1).
3. Sound processing method based on the step-size-variable LMS algorithm as claimed in claim 2, characterized in that the power value P of the sound input signal at the current time isxThe calculation formula of (n) is:
Px(n)＝λPx(n-1)+(1-λ)x2(n)，
wherein, lambda is a smoothing factor, the value range of lambda is more than 0 and less than 1, and x2(n) is the square of the audio input signal x (n) at the current time.
4. A sound processing method based on a variable step LMS algorithm according to claim 2, characterized in that: the step size factor u (n) at the current time is calculated as:
wherein ,
or ,
in the above-mentioned formula, the compound of formula,
a (n-1) is the square value of the gradient at the previous moment, the value range of beta is more than 0 and less than 1, the value range of theta is more than 0 and less than 1, Py(n-1) is the power value of the sound output signal at the previous moment, P2 x(n) is the power value P of the voice input signal at the current momentxThe square of (n).
5. Method according to claim 4 based on a variable step LMS algorithmA sound processing method, characterized by: the sound output signal power PyThe calculation formula of (n) is:
Py(n)＝g(n)*g(n)*Px(n)。
6. a sound processing method based on a variable step LMS algorithm according to claim 4, characterized in that: error value e (n) at current time Pexp-Py(n)，PexpTo a desired value, PexpThe value range is more than 0 and less than Pexp＜1。
7. A sound processing system based on a variable step LMS algorithm, comprising:
a signal input unit for acquiring a sound input signal;
a gain control processing unit for calculating the gain value of the voice input signal at the current time and calculating the output signal according to the calculated gain value,
a signal output unit which performs gain processing on the voice input signal according to the calculated output signal and outputs the voice signal after the gain processing;
the signal parameter calculation unit comprises a power calculation module for calculating the power value of the sound input signal at the current moment, an error calculation module for calculating the error value between the expected power value of the sound output signal and the power value of the sound output signal after gain processing, and a step length calculation module for calculating the step length factor at the current moment;
the storage unit is used for storing the calculation process data and providing the gain control processing unit for calling;
the formula of the gain control processing unit for calculating the gain value is as follows:
g(n)＝g(n-1)+u(n-1)*e(n-1)*Px(n-1)
wherein ,Px(n-1) is the power value of the sound input signal at the previous moment, u (n-1) is the step factor of the previous moment, e (n-1) is the error value of the previous moment, g (n-1) is the gain value of the previous moment, n is the serial number of the sound input signal at the current moment, n is a positive integerAnd n is more than or equal to 2;
the output signal is calculated as:
y (n) ═ g (n) × (n), where x (n) is the current time voice input signal.
8. Sound processing system based on the step-size-variable LMS algorithm of claim 7, characterized in that the power P of the sound input signal at the current momentxThe calculation formula of (n) is:
Px(n)＝λPx(n-1)+(1-λ)x2(n), wherein lambda is a smoothing factor, lambda is in a value range of 0 < lambda < 1, and x2(n) is the square of the audio input signal x (n) at the current time.
9. A sound processing system based on a variable step LMS algorithm according to claim 8, wherein the step size factor u (n) at the current time is calculated as:
wherein ,
or ,
in the above-mentioned formula, the compound of formula,
a (n-1) is the gradient value of the previous moment, the value range of beta is more than 0 and less than 1, the value range of theta is more than 0 and less than 1, Py(n-1) is the power value of the sound output signal at the previous moment, P2 x(n) is the power value P of the voice input signal at the current momentxThe square of (n).
10. Sound processing system based on a variable step LMS algorithm according to claim 9The system is characterized in that the value of the error value e (n) of the sampling point at the current time is the expected power value PexpWith the calculated power value P of the output signal y (n)yThe difference between (n), i.e. e (n) ═ Pexp-Py(n)，PexpThe value range is more than 0 and less than Pexp< 1, the power of the acoustic output signal calculated after the iterative gain is Py(n) the calculation formula is:
Py(n)＝g(n)*g(n)*Px(n)。
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002026788A (en) * | 2000-07-13 | 2002-01-25 | Matsushita Electric Ind Co Ltd | Receiver |
| US20130259159A1 (en) * | 2010-11-02 | 2013-10-03 | CrestCom, Inc, | Transmitter linearized in response to derivative signal and method therefor |
| CN106443597A (en) * | 2016-12-06 | 2017-02-22 | 上海机电工程研究所 | Self-adaption anti-deception system and self-adaption anti-deception method for resisting active decoy jamming |
| CN107393550A (en) * | 2017-07-14 | 2017-11-24 | 深圳永顺智信息科技有限公司 | Method of speech processing and device |
| CN109643554A (en) * | 2018-11-28 | 2019-04-16 | 深圳市汇顶科技股份有限公司 | Adaptive voice Enhancement Method and electronic equipment |
| CN110677796A (en) * | 2019-03-14 | 2020-01-10 | 深圳市攀高电子有限公司 | Audio signal processing method and hearing aid |
| CN111052767A (en) * | 2017-08-28 | 2020-04-21 | 索尼公司 | Audio processing device, audio processing method, and information processing device |
-
2020
- 2020-08-03 CN CN202010766086.4A patent/CN112116914B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002026788A (en) * | 2000-07-13 | 2002-01-25 | Matsushita Electric Ind Co Ltd | Receiver |
| US20130259159A1 (en) * | 2010-11-02 | 2013-10-03 | CrestCom, Inc, | Transmitter linearized in response to derivative signal and method therefor |
| CN106443597A (en) * | 2016-12-06 | 2017-02-22 | 上海机电工程研究所 | Self-adaption anti-deception system and self-adaption anti-deception method for resisting active decoy jamming |
| CN107393550A (en) * | 2017-07-14 | 2017-11-24 | 深圳永顺智信息科技有限公司 | Method of speech processing and device |
| CN111052767A (en) * | 2017-08-28 | 2020-04-21 | 索尼公司 | Audio processing device, audio processing method, and information processing device |
| CN109643554A (en) * | 2018-11-28 | 2019-04-16 | 深圳市汇顶科技股份有限公司 | Adaptive voice Enhancement Method and electronic equipment |
| CN110677796A (en) * | 2019-03-14 | 2020-01-10 | 深圳市攀高电子有限公司 | Audio signal processing method and hearing aid |
Non-Patent Citations (2)
| Title |
|---|
| TALADA APPALA NAIDU: "Control of DVR using Variable Step-Size Griffith"s LMS with Optimized tuning of Proportional Integrator Gains", 《2019 INTERNATIONAL CONFERENCE ON POWER ELECTRONICS APPLICATIONS AND TECHNOLOGY IN PRESENT ENERGY SCENARIO (PETPES)》 * |
| 吴振宙: "音频信号AGC及响度控制算法的研究", 《中国优秀硕士学位论文全文数据》 * |
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