A local sound reinforcement system based on AES audio processing

Abstract

The present application relates to the field of audio processing technology, and in particular to a local sound amplification system based on AES audio processing. The audio acquisition module is used to collect each initial audio signal to obtain an initial audio signal list Y; the audio scoring module is used to obtain a corresponding initial audio difficulty scoring list set F according to each initial audio signal in Y; the audio processing module is used to allocate each initial audio signal to the corresponding processor core for audio processing according to Y, F and the current computing resource remaining rate of each processor core in the preset multi-core audio processor, and obtain a corresponding target audio signal list M; the local sound amplification module is used to locally amplify each target audio signal according to M. The present application makes the load of the processor core (total computing resource occupancy rate) as balanced as possible, saves the overall audio processing time, and ensures that the audio signal is locally amplified without delay and with high quality.

Description

Background Art

[0002] When building a complex local sound reinforcement system for multiple people speaking at the same time, the computing requirements for audio processing have increased significantly, becoming a challenge that cannot be ignored. To meet this challenge, advanced multi-core audio processors are used in related technologies, and their powerful multi-processor core architecture provides a solid foundation for efficient processing of audio data. However, given the strict requirements of local sound reinforcement systems for real-time sound transmission, how to intelligently allocate audio processing tasks to each core to ensure that audio signals can be output without delay and with high quality has become a key link in the implementation of the technology. Summary of the invention

[0003] The technical problem to be solved by this application is: how to intelligently allocate audio processing tasks to each core to ensure that the audio signal can be output without delay and with high quality.

[0004] In view of the above technical problems, according to the first aspect of the present application, a local sound amplification system based on AES audio processing is provided, the system comprising: an audio acquisition module, an AES module, an audio scoring module, an audio processing module and a local sound amplification module; wherein,

[0005] The audio acquisition module is used to collect each initial audio signal to obtain an initial audio signal list Y=(Y 1 , Y 2 , …, Y i , …, Y n ), i=1, 2, ..., n, where n is the number of initial audio signals collected; Y i is the i-th initial audio signal collected; each initial audio signal has a unique corresponding sound receiving device;

[0006] The AES module is used to transmit each initial audio signal in Y to the scoring processor corresponding to the audio scoring module;

[0007] The audio scoring module is used to obtain the corresponding initial audio difficulty score list set F=(F 1 , F 2 , …, F i , …, F n ), where F i Y i Corresponding initial audio difficulty rating list; F i =(FS i , FZ i ,FH i ,FD i );FS i Y i The processing difficulty score of the corresponding preprocessing; FZi Y i Corresponding environmental noise processing difficulty score; FH i Y i The processing difficulty score corresponding to the echo interference; FD i Rate the processing difficulty of the automatic gain;

[0008] The audio processing module is used to allocate each initial audio signal to the corresponding processor core for audio processing according to Y, F and the current computing resource surplus rate of each processor core in the preset multi-core audio processor, and obtain the corresponding target audio signal list M=(M 1 , M 2 , …, M i , …, M n ), where M i Y i A target audio signal obtained through audio processing;

[0009] The local amplification module is used to perform local amplification on each target audio signal according to M.

[0010] This application has at least the following beneficial effects:

[0011] The local sound amplification system based on AES audio processing provided by the present application includes an audio acquisition module, an AES module, an audio scoring module, an audio processing module and a local sound amplification module, wherein after the audio signal is collected and transmitted, the audio scoring module is used to assign a corresponding score to each initial audio signal. Since the effect of the sound received by each sound receiving device is different, the sound processing method and the processing difficulty of each processing method are also different. In the present application, the audio is firstly scored for the processing difficulty in pre-processing difficulty, environmental noise elimination difficulty, echo interference elimination difficulty and automatic gain processing difficulty, so as to obtain the comprehensive difficulty of processing the initial audio signal. Then, according to the current computing resource surplus rate of each processor core in the multi-core audio processor, a suitable processor core is allocated for each initial audio signal for audio processing, so that the load of the processor core (total computing resource occupancy rate) is as balanced as possible to obtain a list of processed target audio signals. Finally, local sound amplification is performed.

[0012] The present application obtains the difficulty score of each initial audio and predicts the computing resource occupancy rate required for processing each initial audio, and then allocates a suitable processor core for audio processing to each initial audio signal according to the current computing resource surplus rate of each processor core in the multi-core audio processor, so that the load of the processor core (total computing resource occupancy rate) is as balanced as possible, saving the overall audio processing time and ensuring that the audio signal is locally amplified without delay and with high quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0014] Figure 1 A structural block diagram of a local sound reinforcement system based on AES audio processing provided by one embodiment of the present application. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0016] like Figure 1 As shown, a local sound reinforcement system 100 based on AES audio processing provided by an embodiment of the present application includes:

[0017] Audio collection module 110, AES module 120, audio scoring module 130, audio processing module 140 and local amplification module 150; wherein,

[0018] The audio acquisition module 110 is used to acquire each initial audio signal to obtain an initial audio signal list Y=(Y 1 , Y 2 , …, Y i , …, Y n ), i=1, 2, ..., n, where n is the number of initial audio signals collected; Y i is the i-th initial audio signal collected; each initial audio signal has a unique corresponding sound receiving device.

[0019] Specifically, in this embodiment, for a scene where multiple people make sounds at the same time, each sound-making body receives sound through a corresponding sound receiving device (microphone, etc.), that is, each initial audio signal has a unique corresponding sound receiving device.

[0020] The AES module 120 is used to transmit each initial audio signal in Y to a scoring processor corresponding to the audio scoring module.

[0021] Specifically, the step of transmitting each initial audio signal in Y to a scoring processor corresponding to a corresponding audio scoring module includes:

[0022] Step S1, converting each original audio signal in Y into a corresponding digital audio signal.

[0023] Here, the original audio signal is converted into a digital audio signal using an analog-to-digital converter (ADC).

[0024] Step S2, encoding each digital audio signal according to the AES / EBU standard to obtain each encoded digital audio signal.

[0025] The AES / EBU standard (Audio Engineering Society / European Broadcast Union) defines a high-quality dual-channel digital audio signal transmission method, which uses an analog XLR audio cable for transmission, breaking the limitations of traditional analog transmission and achieving high-fidelity transmission of digital audio. Step S2 also includes the following steps:

[0026] Step S21, according to Y, obtain the synchronization information corresponding to each initial audio signal to obtain the corresponding synchronization information list T=(T 1 , T 2 ,…,T i ,…,T n ), where T i Y i Corresponding synchronization information; T i =(TJ i , TC i , TX i );TJ i Y i Corresponding timestamp information; TC i Y i Corresponding sampling rate information; TX i Y i Corresponding phase information; each synchronization information has a fixed format.

[0027] Step S22, embed each synchronization information in T into the corresponding digital audio signal in a preset encoding method to obtain each encoded digital audio signal; wherein the preset encoding method is to embed each synchronization information into the auxiliary data bit of each corresponding digital audio signal.

[0028] Here, the timestamp, sampling rate and phase information are embedded into the auxiliary data bits of each corresponding digital audio signal as synchronization information of the original audio signal, and each synchronization information has a fixed data format to avoid bit errors and interference during transmission.

[0029] In an exemplary embodiment of the present application, each synchronization information further includes a parity bit.

[0030] Specifically, adding a parity bit to the synchronization information can be used for simple error detection and improve the accuracy of audio transmission.

[0031] In this embodiment, by embedding the synchronization information in the audio signal and transmitting it together with the audio signal, the risk of synchronization failure caused by synchronization signal loss or interference is reduced. In addition, it does not rely on an external synchronization signal source, thereby improving the flexibility and scalability of the system. In addition, this method can be upgraded and modified based on the existing AES audio processing system without replacing a large number of hardware devices. This embodiment can improve the channel synchronization of subsequent sound transmission.

[0032] Step S3, transmitting each encoded digital audio signal to a scoring processor corresponding to the audio scoring module according to a preset transmission medium.

[0033] Here, the preset transmission medium is a coaxial cable or an optical fiber.

[0034] AES / EBU audio signals can be transmitted over a variety of media, including coaxial cable (such as BNC connectors), optical fiber, and Ethernet (in network audio systems). In local sound reinforcement systems, coaxial cable and optical fiber are widely used due to their long-distance transmission capabilities and anti-interference performance.

[0035] The audio scoring module 130 is used to obtain a corresponding initial audio difficulty score list set F=(F 1 , F 2 , …, F i , …, F n ), where F i Y i Corresponding initial audio difficulty rating list; F i =(FS i , FZ i ,FH i ,FD i );FS i Y i The processing difficulty score of the corresponding preprocessing; FZ i Y i Corresponding environmental noise processing difficulty score; FH i Y i The processing difficulty score corresponding to the echo interference; FD i Rate the difficulty of processing the automatic gain.

[0036] Specifically, here, each initial audio signal can be scored according to a preset scoring model to obtain a difficulty score corresponding to each initial audio signal, wherein the preprocessing can be filtering, denoising and other processing; the processing difficulty score of the preprocessing indicates the intensity of the preprocessing, that is, the greater the corresponding difficulty score, the greater the intensity of the preprocessing, that is, the computing resources and time required to be consumed may be longer. The specific processing method of environmental noise can be to suppress environmental noise and improve the purity of sound. The processing difficulty score of environmental noise indicates the amount of computing resources and the length of time required to suppress environmental noise, that is, the greater the corresponding difficulty score, the more complex the environmental noise of the initial audio signal is, the more difficult it is to handle, the more computing resources may be consumed during processing, and the longer the time may be spent. The specific processing method of echo interference can be to eliminate echo interference, and the processing difficulty score of echo interference indicates the amount of computing resources and the length of time required to eliminate echo interference, that is, the greater the corresponding difficulty score, the more complex the echo of the initial audio signal is, the more difficult it is to handle, the more computing resources may be consumed during processing, and the longer the time may be spent. The specific processing method of automatic gain can be to adjust the gain of the sound signal. The greater the processing difficulty score of automatic gain, the greater the gain adjustment range of the initial audio signal needs to be, the more computing resources may be consumed during processing, and the longer the time may be spent.

[0037] In an exemplary embodiment of the present application, the audio scoring module 130 is also used to decode and digital-to-analog convert each received encoded digital audio signal to obtain an initial audio signal list Y and a corresponding synchronization information list T, and adjust the local clock and phase according to T and a preset adaptive algorithm.

[0038] Specifically, the receiving end (audio scoring module) uses an adaptive algorithm to adjust the local clock and phase according to the extracted synchronization information list T to ensure accurate synchronization with the sending end. The adaptive algorithm should be able to quickly respond to changes in synchronization information and make fine adjustments when necessary to maintain synchronization.

[0039] The audio processing module 140 is used to allocate each initial audio signal to a corresponding processor core for audio processing according to Y, F and the current computing resource surplus rate of each processor core in the preset multi-core audio processor, and obtain a corresponding target audio signal list M=(M 1 , M 2 , …, M i , …, M n ), where M i Y i The target audio signal is obtained after audio processing.

[0040] Specifically, the audio processing module 140 obtains the corresponding target audio signal list M=(M 1 , M 2 , …, M i , …, M n ):

[0041] Step A1, obtaining the current computing resource remaining rate of each processor core in the multi-core audio processor to obtain a corresponding computing resource remaining rate list L=(L 1 , L 2 , …, L j , …, L m ), j = 1, 2, ..., m, m is the number of processor cores included in the multi-core audio processor, L j is the current computing resource surplus rate corresponding to the jth processor core.

[0042] Here, each processor core may currently be processing work. In this embodiment, the current computing resource remaining rate of each processor core in the multi-core audio processor is obtained to obtain a corresponding computing resource remaining rate list. The current computing resource remaining rate represents the processable computing resource occupancy rate of the corresponding processor core.

[0043] Step A2: According to F, obtain the corresponding predicted computing resource occupancy rate list Z=(Z 1 , Z 2 , …, Z i , …, Z n ), where Z i F i The corresponding predicted computing resource occupancy rate.

[0044] Wherein, step A2 further comprises the following steps:

[0045] Step A21, based on F, obtain the comprehensive score list P=(P 1 , P 2 ,…,P i ,…,P n ), where P i Y i The corresponding comprehensive score; P i Meet the following conditions.

[0046] P i =α 1 *FS i +α 2 *FZ i +α 3 *FH i +α 4 *FD i ;

[0047] Among them, α 1 is the time weight corresponding to preprocessing; α 2 is the time weight corresponding to the environmental noise; α 3 is the time weight corresponding to the echo interference; α 4 is the time weight corresponding to the automatic gain.

[0048] Here, for each processing method, the computing resources and time required are also different. The larger the time weight corresponding to each processing method, the more computing resources and time required for the processing method itself. Then, according to the weight corresponding to each processing method itself and the processing difficulty score of each processing method corresponding to each initial audio signal, the comprehensive score corresponding to each initial audio signal is obtained. The larger the comprehensive score, the more computing resources are required to process the corresponding initial audio signal.

[0049] Step A22, determining the predicted computing resource occupancy rate corresponding to each initial audio signal according to P and a preset occupancy rate mapping table; wherein the preset occupancy rate mapping table includes a mapping relationship between each predicted computing resource occupancy rate and each comprehensive score.

[0050] Here, the predicted computing resource occupancy rate corresponding to each initial audio signal is obtained according to a preset occupancy rate mapping table.

[0051] Step A3, if m≥n, Z i +L j ≤avg(L)+avg(Z)+RC, and Z i +L j >Z i +L x , then Y i Assign to L j The corresponding processor core performs audio processing; among them, Z i +L x +RC≤1; x=1, 2, …, j-1, j+1, …, m; RC is the reserved computing resource occupancy rate; avg() is the preset average value determination function.

[0052] Specifically, if the number of processor cores in the multi-core audio processor is greater than the number of initial audio signals to be processed, in order to ensure that the computing resources occupied by each processor core are balanced as much as possible, Z i +L j≤avg(L)+avg(Z)+RC, where avg(L)+avg(Z)+RC is the average computing resource occupancy rate of each processor core after receiving the initial audio signal, obtained based on the average computing resource surplus rate of the processor core and the average computing resource occupancy rate of the initial audio signal. In actual allocation, since the data is not evenly distributed, in order to ensure that each initial audio signal can be reasonably allocated, a reserved computing resource occupancy rate is set. Furthermore, Z i +L j ≤avg(L)+avg(Z)+RC, and Z i +L j >Z i +L x . Even if Z i +L j The average occupancy rate is smaller than the preset average occupancy rate, but is as close to the average occupancy rate as possible, so that suitable processor cores can be reserved as much as possible for other initial audio signals that require more computing resources. This makes the average computing resource occupancy rate of each processor core as balanced as possible after receiving the initial audio signal. Multiple processor cores are processed in parallel, and the corresponding data volume is as consistent as possible, which improves the overall processing efficiency of audio processing in multi-audio scenarios and saves processing time.

[0053] Step A4: according to each processed initial audio signal, obtain the corresponding target audio signal M=(M 1 , M 2 , …, M i , …, M n ).

[0054] Specifically, according to each processed initial audio signal, the corresponding target audio signal M=(M 1 , M 2 , …, M i , …, M n )

[0055] The local amplification module 150 is used to perform local amplification on each target audio signal according to M.

[0056] Specifically, before amplification, the processing of each initial audio signal is completed, and the local amplification can be directly performed using a loudspeaker or other equipment.

[0057] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0058] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0059] Those skilled in the art will appreciate that various aspects of the present application may be implemented as a system, method or program product. Therefore, various aspects of the present application may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to as "circuit", "module" or "system" herein.

[0060] The electronic device according to this embodiment of the present application is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0061] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: the at least one processor mentioned above, the at least one storage device mentioned above, and a bus connecting different system components (including storage devices and processors).

[0062] The storage device stores program codes, which can be executed by the processor, so that the processor executes the steps described in the “exemplary method” section of the specification according to various exemplary embodiments of the present application.

[0063] The memory may include readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read only memory (ROM).

[0064] The storage may also include a program / utility having a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0065] The bus may represent one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0066] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may communicate with one or more devices that enable a user to interact with the electronic device, and / or may communicate with any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface. In addition, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter. The network adapter communicates with other modules of the electronic device through a bus. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0067] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0068] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present application can also be implemented in the form of a program product, which includes a program code. When the above program product is run on a terminal device, the above program code is used to enable the above terminal device to execute the steps according to various exemplary implementations of the present application described in the above "Exemplary Method" section of the present specification.

[0069] The above-mentioned program product can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0070] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0071] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0072] Program code for performing the operations of the present application may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0073] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0074] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0075] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A local sound reinforcement system based on AES audio processing, characterized in that: The system includes: an audio acquisition module, an AES module, an audio scoring module, an audio processing module and a local amplification module; wherein, The audio acquisition module is used to acquire each initial audio signal to obtain an initial audio signal list Y=(Y1, Y2, ..., Y i , …, Y n ), i=1, 2, ..., n, where n is the number of initial audio signals collected; Y i is the i-th initial audio signal collected; each initial audio signal has a unique corresponding sound receiving device; The AES module is used to transmit each initial audio signal in Y to the scoring processor corresponding to the audio scoring module; The audio scoring module is used to obtain a corresponding initial audio difficulty score list set F=(F1, F2, ..., F i , …, F n ), where F i Y i Corresponding initial audio difficulty rating list; F i =(FS i , FZ i ,FH i ,FD i );FS i Y i The processing difficulty score of the corresponding preprocessing; FZ i Y i Corresponding environmental noise processing difficulty score; FH i Y i The processing difficulty score corresponding to the echo interference; FD i Rate the processing difficulty of the automatic gain; The audio processing module is used to allocate each initial audio signal to the corresponding processor core for audio processing according to Y, F and the current computing resource surplus rate of each processor core in the preset multi-core audio processor, and obtain the corresponding target audio signal list M=(M1, M2, ..., M i , …, M n ), where M i Y i A target audio signal obtained through audio processing; The local amplification module is used to locally amplify each target audio signal according to M; According to Y, F and the current computing resource surplus rate of each processor core in the preset multi-core audio processor, each initial audio signal is assigned to the corresponding processor core for audio processing, and a corresponding target audio signal list M=(M1, M2, ..., M i , …, M n ),include: Obtain the current computing resource surplus rate of each processor core in the multi-core audio processor to obtain the corresponding computing resource surplus rate list L=(L1, L2, ..., L j , …, L m ), j = 1, 2, ..., m, m is the number of processor cores included in the multi-core audio processor, L j is the current computing resource surplus rate corresponding to the jth processor core; According to F, we get the corresponding predicted computing resource occupancy list Z=(Z1, Z2, …, Z i , …, Z n ), where Z i F i The corresponding predicted computing resource occupancy rate; If m ≥ n, Z i +L j ≤avg(L)+avg(Z)+RC, and Z i +L j >Z i +L x , then Y i Assign to L j The corresponding processor core performs audio processing; among them, Z i +L x +RC≤1; x=1, 2, ..., j-1, j+1, ..., m; RC is the reserved computing resource occupancy rate; avg() is the preset average value determination function; According to each processed initial audio signal, the corresponding target audio signal M=(M1, M2, ..., M i , …, M n ).

2. The local sound reinforcement system based on AES audio processing according to claim 1, characterized in that: The step of transmitting each initial audio signal in Y to a scoring processor corresponding to a corresponding audio scoring module includes: Convert each initial audio signal in Y into a corresponding digital audio signal; Encoding each digital audio signal according to the AES / EBU standard to obtain each encoded digital audio signal; Each encoded digital audio signal is transmitted to a scoring processor corresponding to the audio scoring module according to a preset transmission medium.

3. The local sound reinforcement system based on AES audio processing according to claim 2, characterized in that: The preset transmission medium is a coaxial cable or an optical fiber.

4. The local sound reinforcement system based on AES audio processing according to claim 2, characterized in that: The step of encoding each of the digital audio signals according to the AES / EBU standard to obtain each encoded digital audio signal comprises: According to Y, the synchronization information corresponding to each initial audio signal is obtained to obtain the corresponding synchronization information list T=(T1, T2, ..., T i ,…,T n ), where T i Y i Corresponding synchronization information; T i =(TJ i , TC i , TX i );TJ i Y i Corresponding timestamp information; TC i Y i Corresponding sampling rate information; TX i Y i Corresponding phase information; each synchronization information has a fixed format; Each synchronization information in T is embedded into the corresponding digital audio signal in a preset coding method to obtain each encoded digital audio signal; wherein the preset coding method is to embed each synchronization information into the auxiliary data bit of each corresponding digital audio signal.

5. The local sound reinforcement system based on AES audio processing according to claim 4, characterized in that: Each synchronization message also includes a parity bit.

6. The local sound reinforcement system based on AES audio processing according to claim 4, characterized in that: The audio scoring module is also used to decode and convert each received encoded digital audio signal to obtain an initial audio signal list Y and a corresponding synchronization information list T, and adjust the local clock and phase according to T and a preset adaptive algorithm.

7. The local sound reinforcement system based on AES audio processing according to claim 1, characterized in that: According to F, we get the corresponding predicted computing resource occupancy list Z=(Z1, Z2, …, Z i , …, Z n ),include: According to F, we get the comprehensive score list P=(P1, P2, ..., P i ,…,P n ), where P i Y i The corresponding comprehensive score; P i Meet the following conditions: P i =α1*FS i +α2*FZ i +α3*FH i +α4*FD i ; Among them, α1 is the time weight corresponding to preprocessing; α2 is the time weight corresponding to environmental noise; α3 is the time weight corresponding to echo interference; α4 is the time weight corresponding to automatic gain; According to P and a preset occupancy rate mapping table, the predicted computing resource occupancy rate corresponding to each initial audio signal is determined; wherein the preset occupancy rate mapping table includes a mapping relationship between each predicted computing resource occupancy rate and each comprehensive score.

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