A method, device and equipment for directional broadcasting of a sound box and a storage medium

Abstract

The application relates to the technical field of broadcasting, and discloses a directional broadcasting method, device and equipment of a sound box and a storage medium, the method comprising the following steps: in a preset first time window, receiving a first sound signal by using a plurality of sound sensors; calculating a covariance matrix of the sound signal by using a linear constraint minimum variance algorithm, and determining a direction vector of a target direction; determining a target weight vector according to the direction vector of the target direction and a constraint condition thereof; the target weight vector is a beamforming weight vector; solving the target weight vector by using a Lagrange multiplier method to obtain a first optimal weight vector; performing weighted summation on the first sound signal by using the first optimal weight vector to generate an output signal; and playing the output signal by using the sound box. By using the technical scheme of the application, the signal of a required direction can be effectively enhanced, and the interference from other directions can be suppressed at the same time by using a reasonable signal processing and control strategy, so that high-quality audio output is realized.

Description

Technical Field

[0001] This invention relates to the field of broadcasting technology, specifically to a method, apparatus, device, and computer-readable storage medium for directional broadcasting of a speaker. Background Technology

[0002] In current directional broadcasting technology, traditional speaker designs often lack precise sound wave control mechanisms, resulting in poor directionality. This prevents sound from being effectively focused in a specific direction during propagation, and the utilization of speaker layout and sound wave interference phenomena is insufficient. Consequently, when sound disperses in all directions, the energy proportion in the desired direction is low. Listeners who are outside the intended receiving area have difficulty clearly receiving the broadcast content, significantly impacting the accuracy of information transmission.

[0003] Due to the presence of various noise sources in the environment, and the limited capabilities of current technologies in noise reduction and interference resistance, it is difficult to efficiently distinguish the target broadcast sound from these interfering signals. When multiple sounds are mixed together, the clarity and intelligibility of the broadcast sound decrease significantly. Furthermore, it is difficult to precisely control the coverage area of ​​some speakers. Either the coverage area is too large, causing sound energy dispersion and insufficient sound intensity at long distances; or the coverage area is too small, failing to meet the needs of actual scenarios, resulting in wasted resources and poor broadcast quality. This is mainly due to insufficient analysis of sound propagation models and the lack of effective algorithms for fine-tuning coverage area during signal processing. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a method, apparatus, device and computer-readable storage medium for directional broadcasting of a speaker, which can effectively enhance the signal in the desired direction and suppress interference from other directions through reasonable signal processing and control strategies, thereby achieving high-quality audio output.

[0005] According to one aspect of the present invention, a method for directional broadcasting of a speaker is provided, the method comprising: receiving a first sound signal using a plurality of sound sensors within a preset first time window;

[0006] The covariance matrix of the sound signal is calculated using the linear constraint minimum variance algorithm to determine the direction vector of the target direction; the target weight vector is determined based on the direction vector of the target direction and its constraints; the target weight vector is a beamforming weight vector.

[0007] The Lagrange multiplier method is used to solve for the target weight vector, and the first optimal weight vector is obtained.

[0008] The first sound signal is weighted and summed using the first optimal weight vector to generate an output signal;

[0009] The output signal is played using a speaker.

[0010] Specifically, this invention achieves directional broadcasting from a speaker using a linear constraint minimum variance algorithm. Through reasonable signal processing and control strategies, it can effectively enhance the signal in the desired direction while suppressing interference from other directions, thereby achieving high-quality audio output.

[0011] In one alternative approach, the target signal is determined based on the first sound signal and the direction vector of the target direction;

[0012] Based on the target signal and the output signal, the target weight vector is adjusted using the Least Mean Square (LMS) algorithm of the adaptive filter to obtain the second optimal weight vector;

[0013] The second sound signal is weighted and summed using the second optimal weight vector to generate a second output signal; the second sound signal is received by several sound sensors within a preset second time window;

[0014] The second output signal is played using a speaker.

[0015] Specifically, this invention uses the LMS algorithm to adjust the weights, employing a feedback mechanism (error signal) to adjust the weight vector in order to adaptively enhance the target signal in a dynamic environment. This process allows the system to automatically optimize its performance under different signal conditions, thereby achieving efficient directional broadcasting.

[0016] In one alternative approach, a linearly constrained minimum variance algorithm is used to calculate the covariance matrix of the first sound signal, determine the direction vector of the target direction, and determine the target weight vector based on the direction vector of the target direction and its constraints, including:

[0017] The expression for the covariance matrix of the first sound signal is:

[0018] R = E[x(n)x H (n)];

[0019] Where R is the covariance matrix of the first sound signal, E represents the expected value, and x H (n) is the conjugate transpose of x(n);

[0020] x(n) is the signal vector of the first sound signal, and its expression is:

[0021]

[0022] x N(n) represents the first sound signal received by the Nth sound sensor, where N = 1, 2, ..., M; and M is the number of sound sensors.

[0023] The expression for calculating the direction vector of the target direction is:

[0024]

[0025] Where α is the direction vector of the target direction, and j is the imaginary unit, satisfying j 2 =-1, d is the array spacing, and λ is the signal wavelength;

[0026] The expression for the constraint condition of the direction vector of the target direction is:

[0027] α H ω = 1;

[0028] Where ω is the target weight vector.

[0029] In one alternative approach, the Lagrange multiplier method is used to solve for the target weight vector, yielding a first optimal weight vector, including:

[0030] Differentiate the Lagrange function and substitute the differentiated Lagrange function into the constraint condition of the direction vector of the target direction to obtain the first optimal weight vector;

[0031] The expression for the Lagrange function is:

[0032] L(ω,λ)=ω H Rω-λ(α H ω-1);

[0033] The expression for the first optimal weight vector is:

[0034]

[0035] In one alternative approach, the derivative of the Lagrange function is calculated, and the differentiated Lagrange function is substituted into the constraint condition of the direction vector of the target direction to obtain the first optimal weight vector, specifically:

[0036] Find the partial derivatives of the Lagrange function with respect to ω and λ respectively, and set the partial derivatives to zero to obtain the objective equation;

[0037] The expression for the partial derivative of the Lagrange function with respect to ω is:

[0038]

[0039] The expression for the partial derivative of the Lagrange function with respect to λ is:

[0040]

[0041] The expression for the objective equation is:

[0042]

[0043] Substituting the objective equation into the constraint condition of the direction vector of the objective direction, the first optimal weight vector is obtained.

[0044] In one alternative approach, based on the target signal and the output signal, the target weight vector is adjusted using the least mean square (LMS) algorithm of an adaptive filter to obtain a second optimal weight vector, further comprising:

[0045] The error signal is obtained by subtracting the target signal from the output signal.

[0046] Based on the preset step size factor, the target weight vector is iteratively updated until the termination condition is met, and the second optimal weight vector is obtained.

[0047] ω(n+1)=ω(n)+μe(n)x'(n);

[0048] Where ω(n) is the target weight vector, ω(n+1) is the updated target weight vector, μ is the step size factor, e(n) is the error signal, and x'(n) is the signal vector of the second sound signal;

[0049] The expression for the signal vector of the second sound signal is:

[0050] x'(n)=[x1'(n), x2'(n),...,x M '(n)];

[0051] Where, x' N (n) represents the second sound signal received by the Nth sound sensor, where N = 1, 2, ..., M; and M is the number of sound sensors.

[0052] The termination conditions are: reaching the required number of iterations, the error signal being lower than the error threshold, or the mean square value of the error signal being lower than the preset mean square value threshold.

[0053] According to another aspect of the present invention, a directional broadcasting device for a speaker is provided, comprising: a receiving module, a weight calculation module, a signal calculation module, and an output module;

[0054] The receiving module is used to receive a first sound signal using several sound sensors within a preset first time window;

[0055] The weight calculation module is used to calculate the covariance matrix of the sound signal using a linearly constrained minimum variance algorithm to determine the direction vector of the target direction; based on the direction vector of the target direction and its constraints, it determines the target weight vector; the target weight vector is a beamforming weight vector; and the Lagrange multiplier method is used to solve for the target weight vector to obtain the first optimal weight vector.

[0056] The signal calculation module is used to perform weighted summation on the first sound signal using the first optimal weight vector to generate an output signal;

[0057] The output module is used to play the output signal using a speaker.

[0058] In one alternative embodiment, the apparatus further includes a weight update module;

[0059] The weight update module is used to determine the target signal based on the first sound signal and the direction vector of the target direction;

[0060] Based on the target signal and the output signal, the target weight vector is adjusted using the Least Mean Square (LMS) algorithm of the adaptive filter to obtain the second optimal weight vector;

[0061] The second sound signal is weighted and summed using the second optimal weight vector to generate a second output signal; the second sound signal is received by several sound sensors within a preset second time window;

[0062] The second output signal is played using a speaker.

[0063] According to another aspect of the present invention, a directional broadcasting device for a speaker is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; the memory is used to store at least one executable instruction, the executable instruction causing the processor to perform the operation of the directional broadcasting method for the speaker as described in any of the preceding embodiments.

[0064] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing at least one executable instruction that causes a directional broadcasting device / apparatus of a speaker to perform the operation of the directional broadcasting method of the speaker as described in any of the preceding embodiments.

[0065] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0066] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0067] Figure 1 A flowchart illustrating an embodiment of the directional broadcasting method for a speaker provided by the present invention is shown;

[0068] Figure 2 A schematic diagram of one embodiment of the directional broadcasting device for a speaker provided by the present invention is shown;

[0069] Figure 3 A schematic diagram of an embodiment of the directional broadcasting device for a speaker provided by the present invention is shown. Detailed Implementation

[0070] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0071] Example 1, Figure 1 A flowchart illustrating an embodiment of the directional broadcasting method for a speaker provided by the present invention is shown. This method is executed by a target device, which is a directional broadcasting device for a speaker. Figure 1 As shown, the method includes the following steps:

[0072] Step 110: Within a preset first time window, receive the first sound signal using several sound sensors.

[0073] Specifically, before receiving the first audio signal, the process includes: the target device confirming the number of linear arrays, such as the number of microphones or speakers (M), determining the location of the signal source and interference sources, and simultaneously confirming the target gain direction and constraints. The target device initializes the weight vector ω, which can be set to 0 or a random value. The target device sets the sampling frequency and time window, such as the length of the signal processing time window.

[0074] Specifically, the aforementioned sound sensors form a linear array with uniform spacing. This spacing should typically be less than or equal to half the shortest wavelength of the processed signal to ensure the array can effectively distinguish signals from different directions. The sound sensors receive signals from the environment, including the target sound source and background noise. The location of the sound source can be estimated using the time difference of the signal arrival at each sensor. The direction of the sound source can be identified based on the signal strength and phase received by the sensors. The sensor array can be used to distinguish between the target sound source and interfering sound sources. Based on sensor feedback, beamforming algorithms are used to adjust weights to maximize the target signal and suppress interfering signals.

[0075] Sound sensors are typically installed at a height of 1.5 to 2 meters to capture children's voices and avoid interference from ground reflections. They should face the main activity area and be away from large obstacles to reduce sound wave reflection and diffraction. Avoid placing them near noise sources to minimize background noise interference. Several sound sensors should be placed in front of or around the speaker to receive the sound emitted by the speaker, as well as echoes and interfering noises in the environment.

[0076] Step 120: Calculate the covariance matrix of the sound signal using the linear constraint minimum variance algorithm to determine the direction vector of the target direction; determine the target weight vector based on the direction vector of the target direction and its constraints; the target weight vector is the beamforming weight vector; solve for the target weight vector using the Lagrange multiplier method to obtain the first optimal weight vector.

[0077] In some embodiments of the present invention, the covariance matrix of the first sound signal is calculated using a linearly constrained minimum variance algorithm to determine the direction vector of the target direction. Based on the direction vector of the target direction and its constraints, a target weight vector is determined, including:

[0078] The expression for the covariance matrix of the first sound signal is:

[0079] R = E[x(n)x H (n)];

[0080] Where R is the covariance matrix of the first sound signal, E represents the expected value, and x H (n) is the conjugate transpose of x(n);

[0081] x(n) is the signal vector of the first sound signal, and its expression is:

[0082]

[0083] x N(n) represents the first sound signal received by the Nth sound sensor, where N = 1, 2, ..., M; and M is the number of sound sensors.

[0084] The expression for calculating the direction vector of the target direction is:

[0085]

[0086] Where α is the direction vector of the target direction, and j is the imaginary unit, satisfying j 2 =-1, d is the array spacing, and λ is the signal wavelength;

[0087] The expression for the constraint condition of the direction vector of the target direction is:

[0088] α H ω = 1;

[0089] Where ω is the target weight vector.

[0090] In some embodiments of the present invention, the Lagrange multiplier method is used to solve for the target weight vector to obtain the first optimal weight vector, including:

[0091] Differentiate the Lagrange function and substitute the differentiated Lagrange function into the constraint condition of the direction vector of the target direction to obtain the first optimal weight vector;

[0092] The expression for the Lagrange function is:

[0093] L(ω,λ)=ω H Rω-λ(α H ω-1);

[0094] The expression for the first optimal weight vector is:

[0095]

[0096] In some embodiments of the present invention, the derivative of the Lagrange function is calculated, and the differentiated Lagrange function is substituted into the constraint condition of the direction vector of the target direction to obtain the first optimal weight vector, specifically:

[0097] Find the partial derivatives of the Lagrange function with respect to ω and λ respectively, and set the partial derivatives to zero to obtain the objective equation;

[0098] The expression for the partial derivative of the Lagrange function with respect to ω is:

[0099]

[0100] The expression for the partial derivative of the Lagrange function with respect to λ is:

[0101]

[0102] The expression for the objective equation is:

[0103]

[0104] Substituting the objective equation into the constraint condition of the direction vector of the objective direction, the first optimal weight vector is obtained.

[0105] Specifically, the target device achieves optimal beamforming by minimizing power. The optimal weight vector was found using the Lagrange multiplier method, as follows:

[0106] Setting the partial derivative of the Lagrange function with respect to ω to zero, we get:

[0107] 2Rω-λα=0

[0108] We can obtain:

[0109]

[0110] This leads to the expression for ω:

[0111]

[0112] Setting the partial derivative of the Lagrange function with respect to λ to zero, we get:

[0113] α H ω-1=0

[0114] Substituting the expression for ω into the constraints, we get:

[0115]

[0116] Therefore, we can obtain the expression for λ:

[0117]

[0118] Substituting the expression for λ into the expression for ω, we get:

[0119]

[0120] Finally, the first optimal weight vector is obtained:

[0121]

[0122] Step 130: Use the first optimal weight vector to perform a weighted summation on the first sound signal to generate an output signal.

[0123] The input signal is weighted and summed using the obtained weight vector to generate the output signal: y(n)=ωH x(n).

[0124] Step 140: Play the output signal using a speaker.

[0125] In some embodiments of the present invention, the target signal is determined based on the first sound signal and the direction vector of the target direction;

[0126] Based on the target signal and the output signal, the target weight vector is adjusted using the Least Mean Square (LMS) algorithm of the adaptive filter to obtain the second optimal weight vector;

[0127] The second sound signal is weighted and summed using the second optimal weight vector to generate a second output signal; the second sound signal is received by several sound sensors within a preset second time window;

[0128] The second output signal is played using a speaker.

[0129] Specifically, this invention dynamically adjusts the weight vector as needed, updating the covariance matrix and weights each time a new signal arrives. This can be achieved through a recursive algorithm, such as using an adaptive filter, like the Least Mean Square (LMS) algorithm, to adjust the weight vector to adapt to environmental changes. This invention evaluates the quality of the output signal, checking the enhancement effect in the target direction and the suppression effect in other directions. If the effect is not ideal, the weight calculation method or constraints can be adjusted to achieve optimal performance.

[0130] In some embodiments of the present invention, based on the target signal and the output signal, the target weight vector is adjusted using the least mean square (LMS) algorithm of an adaptive filter to obtain a second optimal weight vector, and the method further includes:

[0131] The error signal is obtained by subtracting the target signal from the output signal.

[0132] Based on the preset step size factor, the target weight vector is iteratively updated until the termination condition is met, and the second optimal weight vector is obtained.

[0133] ω(n+1)=ω(n)+μe(n)x'(n);

[0134] Where ω(n) is the target weight vector, ω(n+1) is the updated target weight vector, μ is the step size factor, e(n) is the error signal, and x'(n) is the signal vector of the second sound signal;

[0135] The expression for the signal vector of the second sound signal is:

[0136] x'(n)=[x1'(n), x2'(n),...,xM '(n)];

[0137] Where, x' N (n) represents the second sound signal received by the Nth sound sensor, where N = 1, 2, ..., M; and M is the number of sound sensors.

[0138] The termination conditions are: reaching the required number of iterations, the error signal being lower than the error threshold, or the mean square value of the error signal being lower than the preset mean square value threshold.

[0139] This invention achieves directional broadcasting from a speaker using a linearly constrained minimum variance algorithm. Through reasonable signal processing and control strategies, it can effectively enhance the signal in the desired direction while suppressing interference from other directions, thereby achieving high-quality audio output.

[0140] This invention uses the LMS algorithm to adjust weights, employing a feedback mechanism (error signal) to modify the weight vector, thereby adaptively enhancing the target signal in a dynamic environment. This process allows the system to automatically optimize its performance under different signal conditions, thus achieving efficient directional broadcasting.

[0141] Figure 2 A schematic diagram of one embodiment of the directional broadcasting device for a speaker provided by the present invention is shown; as follows: Figure 2 As shown, the device 200 includes: a receiving module 210, a weight calculation module 220, a signal calculation module 230, and an output module 240.

[0142] The receiving module 210 is used to receive a first sound signal using a plurality of sound sensors within a preset first time window;

[0143] The weight calculation module 220 is used to calculate the covariance matrix of the sound signal using a linear constraint minimum variance algorithm to determine the direction vector of the target direction; determine the target weight vector based on the direction vector of the target direction and its constraints; the target weight vector is a beamforming weight vector; and solve the target weight vector using the Lagrange multiplier method to obtain the first optimal weight vector.

[0144] Signal calculation module 230 is used to perform weighted summation on the first sound signal using the first optimal weight vector to generate an output signal;

[0145] Output module 240 is used to play the output signal using a speaker.

[0146] In an alternative embodiment, the device 200 further includes a weight update module;

[0147] The weight update module is used to determine the target signal based on the first sound signal and the direction vector of the target direction;

[0148] Based on the target signal and the output signal, the target weight vector is adjusted using the Least Mean Square (LMS) algorithm of the adaptive filter to obtain the second optimal weight vector;

[0149] The second sound signal is weighted and summed using the second optimal weight vector to generate a second output signal; the second sound signal is received by several sound sensors within a preset second time window;

[0150] The second output signal is played using a speaker.

[0151] In one optional approach, the weight calculation module 220 uses a linearly constrained minimum variance algorithm to calculate the covariance matrix of the first sound signal, determine the direction vector of the target direction, and determine the target weight vector based on the direction vector of the target direction and its constraints, including:

[0152] The expression for the covariance matrix of the first sound signal is:

[0153] R = E[x(n)x H (n)];

[0154] Where R is the covariance matrix of the first sound signal, E represents the expected value, and x H (n) is the conjugate transpose of x(n);

[0155] x(n) is the signal vector of the first sound signal, and its expression is:

[0156]

[0157] x N (n) represents the first sound signal received by the Nth sound sensor, where N = 1, 2, ..., M; and M is the number of sound sensors.

[0158] The expression for calculating the direction vector of the target direction is:

[0159]

[0160] Where α is the direction vector of the target direction, and j is the imaginary unit, satisfying j 2 =-1, d is the array spacing, and λ is the signal wavelength;

[0161] The expression for the constraint condition of the direction vector of the target direction is:

[0162] α H ω = 1;

[0163] Where ω is the target weight vector.

[0164] The Lagrange multiplier method is used to solve for the target weight vector, yielding the first optimal weight vector, which includes:

[0165] Differentiate the Lagrange function and substitute the differentiated Lagrange function into the constraint condition of the direction vector of the target direction to obtain the first optimal weight vector;

[0166] The expression for the Lagrange function is:

[0167] L(ω,λ)=ω H Rω-λ(α H ω-1);

[0168] The expression for the first optimal weight vector is:

[0169]

[0170] Differentiating the Lagrange function and substituting the differentiated Lagrange function into the constraint condition of the direction vector of the target direction, we obtain the first optimal weight vector, specifically:

[0171] Find the partial derivatives of the Lagrange function with respect to ω and λ respectively, and set the partial derivatives to zero to obtain the objective equation;

[0172] The expression for the partial derivative of the Lagrange function with respect to ω is:

[0173]

[0174] The expression for the partial derivative of the Lagrange function with respect to λ is:

[0175]

[0176] The expression for the objective equation is:

[0177]

[0178] Substituting the objective equation into the constraint condition of the direction vector of the objective direction, the first optimal weight vector is obtained.

[0179] In an alternative embodiment, the weight update module adjusts the target weight vector using the least mean square (LMS) algorithm of an adaptive filter based on the target signal and the output signal to obtain a second optimal weight vector, and further includes:

[0180] The error signal is obtained by subtracting the target signal from the output signal.

[0181] Based on the preset step size factor, the target weight vector is iteratively updated until the termination condition is met, and the second optimal weight vector is obtained.

[0182] ω(n+1)=ω(n)+μe(n)x'(n);

[0183] Where ω(n) is the target weight vector, ω(n+1) is the updated target weight vector, μ is the step size factor, e(n) is the error signal, and x'(n) is the signal vector of the second sound signal;

[0184] The expression for the signal vector of the second sound signal is:

[0185] x'(n)=[x1'(n), x2'(n),...,x M '(n)];

[0186] Where, x' N (n) represents the second sound signal received by the Nth sound sensor, where N = 1, 2, ..., M; and M is the number of sound sensors.

[0187] The termination conditions are: reaching the required number of iterations, the error signal being lower than the error threshold, or the mean square value of the error signal being lower than the preset mean square value threshold.

[0188] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0189] Figure 3 The diagram shows a structural schematic of an embodiment of the directional broadcasting device for a speaker provided by the present invention. The specific embodiments of the present invention do not limit the specific implementation of the directional broadcasting device for a speaker.

[0190] like Figure 3 As shown, the directional broadcasting device of the speaker may include: a processor 302, a communications interface 304, a memory 306, and a communication bus 308.

[0191] The processor 302, communication interface 304, and memory 306 communicate with each other via communication bus 308. Communication interface 304 is used to communicate with other network elements such as clients or other servers. The processor 302 executes program 310, specifically performing the relevant steps described in the embodiment of the directional broadcasting method for speakers.

[0192] Specifically, program 310 may include program code, which includes computer-executable instructions.

[0193] Processor 302 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The directional broadcasting device of the speaker may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0194] Memory 306 is used to store program 310. Memory 306 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0195] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Furthermore, the embodiments of this invention are not directed to any particular programming language.

[0196] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. Similarly, for the sake of brevity and to aid in understanding one or more aspects of the invention, in the description of exemplary embodiments of the invention above, various features of the embodiments are sometimes grouped together in a single embodiment, figure, or description thereof. The claims, which follow the detailed description, are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0197] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components, except that at least some of such features and / or processes or units are mutually exclusive.

[0198] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. A method for directional broadcasting from a speaker, characterized in that, The method includes: Within a preset first time window, a first sound signal is received using several sound sensors; The covariance matrix of the sound signal is calculated using the linear constraint minimum variance algorithm to determine the direction vector of the target direction; the target weight vector is determined based on the direction vector of the target direction and its constraints; the target weight vector is a beamforming weight vector. The Lagrange multiplier method is used to solve for the target weight vector, and the first optimal weight vector is obtained. The first sound signal is weighted and summed using the first optimal weight vector to generate an output signal; The output signal is played using a speaker; The target signal is determined based on the first sound signal and the direction vector of the target direction; Based on the target signal and the output signal, the least mean square of the adaptive filter is used. LMS The algorithm adjusts the target weight vector to obtain the second optimal weight vector; The second sound signal is weighted and summed using the second optimal weight vector to generate a second output signal; the second sound signal is received by several sound sensors within a preset second time window; The second output signal is played using a speaker.

2. The directional broadcasting method for a speaker according to claim 1, characterized in that, Using the linearly constrained minimum variance algorithm, the covariance matrix of the first sound signal is calculated to determine the direction vector of the target direction. Based on the direction vector of the target direction and its constraints, the target weight vector is determined, including: The expression for the covariance matrix of the first sound signal is: R=E [ x ( n ) x H ( n )]； in, R Let be the covariance matrix of the first sound signal. E Indicates the expected value. x H ( n )yes x ( n The conjugate transpose of ) x ( n Let be the signal vector of the first sound signal, and its expression is: x N ( n ) is the first N The first sound signal received by the sound sensor. N =1, 2, ..., M ; M The number of sound sensors; The expression for calculating the direction vector of the target direction is: in, The direction vector is the direction of the target. j It is the imaginary unit, satisfying j 2 =-1, d It is the array spacing. λ It is the signal wavelength; θ The angle of the target direction; Let N be the direction vector of the Nth sound sensor, where N = 1, 2, ..., M; and M represents the number of sound sensors. The expression for the constraint condition of the direction vector of the target direction is: ； in, This is the target weight vector.

3. The directional broadcasting method for a speaker according to claim 2, characterized in that, The Lagrange multiplier method is used to solve for the target weight vector, yielding the first optimal weight vector, which includes: Differentiate the Lagrange function and substitute the differentiated Lagrange function into the constraint condition of the direction vector of the target direction to obtain the first optimal weight vector; The expression for the Lagrange function is: ； The expression for the first optimal weight vector is: 。 4. The directional broadcasting method for a speaker according to claim 3, characterized in that, Differentiating the Lagrange function and substituting the differentiated Lagrange function into the constraint condition of the direction vector of the target direction, we obtain the first optimal weight vector, specifically: Find the Lagrange function with respect to... and λ The partial derivatives are calculated, and the partial derivatives are set to zero to obtain the objective equation. Among them, the Lagrange function is related to The expression for the partial derivative is: Lagrange function with respect to λ The expression for the partial derivative is: The expression for the objective equation is: Substituting the objective equation into the constraint condition of the direction vector of the objective direction, the first optimal weight vector is obtained.

5. The directional broadcasting method for a speaker according to claim 1, characterized in that, Based on the target signal and the output signal, the target weight vector is adjusted using the Least Mean Square (LMS) algorithm of the adaptive filter to obtain a second optimal weight vector, and the method further includes: The error signal is obtained by subtracting the target signal from the output signal. Based on the preset step size factor, the target weight vector is iteratively updated until the termination condition is met, and the second optimal weight vector is obtained. ； in, For the target weight vector, For the updated target weight vector, Step size factor e ( n ) represents the error signal. x '( n ) is the signal vector of the second sound signal; The expression for the signal vector of the second sound signal is: x ’( n )=[ x 1’( n )， x 2’( n )，...， x M ’( n )]； in, x ' N ( n ) is the first N The second sound signal received by the sound sensor N =1, 2, ..., M ; M The number of sound sensors; The termination conditions are: reaching the required number of iterations, the error signal being lower than the error threshold, or the mean square value of the error signal being lower than the preset mean square value threshold.

6. A directional broadcasting device for a speaker, characterized in that, The device includes: a receiving module, a weight calculation module, a signal calculation module, and an output module; The receiving module is used to receive a first sound signal using several sound sensors within a preset first time window; The weight calculation module is used to calculate the covariance matrix of the sound signal using a linearly constrained minimum variance algorithm to determine the direction vector of the target direction; based on the direction vector of the target direction and its constraints, it determines the target weight vector; the target weight vector is a beamforming weight vector; and the Lagrange multiplier method is used to solve for the target weight vector to obtain the first optimal weight vector. The signal calculation module is used to perform weighted summation on the first sound signal using the first optimal weight vector to generate an output signal; An output module is used to play the output signal using a speaker; The weight update module determines the target signal based on the first sound signal and the direction vector of the target direction; adjusts the target weight vector using the least mean square (LMS) algorithm of the adaptive filter based on the target signal and the output signal to obtain a second optimal weight vector; uses the second optimal weight vector to perform a weighted summation on the second sound signal to generate a second output signal; the second sound signal is received by several sound sensors within a preset second time window; and plays the second output signal using a speaker.

7. A directional broadcasting device for a speaker, characterized in that, include: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction that causes the processor to perform the operation of the directional broadcasting method of the speaker as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The storage medium stores at least one executable instruction, which, when executed on the speaker's directional broadcasting device / apparatus, causes the speaker's directional broadcasting device / apparatus to perform the operation of the speaker's directional broadcasting method as described in any one of claims 1-5.

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