Sound noise reduction processing method and system in complex environment, terminal and storage medium

Abstract

The application relates to a sound noise reduction processing method and system in a complex environment, a terminal and a storage medium. The method comprises the following steps: acquiring multiple sound signals collected by multiple microphones in the same target environment, each sound signal comprising sound information of multiple sounds, and the sound information of one sound in the multiple sounds comprising signal energy; acquiring microphone position information of the multiple microphones; determining a first weight of each sound signal according to the microphone position information based on a preset first weight distribution rule; determining a second weight of each sound according to the signal energy based on a preset second weight distribution rule; determining a comprehensive weight according to the first weight and the second weight, wherein the comprehensive weight is the weight of each sound in all sounds; sorting each sound according to the comprehensive weight to obtain a sorting result; and reducing the signal energy according to the sorting result and a preset threshold. The application has the effect of improving the applicability of the noise reduction mode.

Description

Technical Field

[0001] This application relates to the field of sound noise reduction, and in particular to a sound noise reduction processing method, system, terminal and storage medium in complex environments. Background Technology

[0002] When audio acquisition devices collect sound signals, they are easily affected by surrounding environmental factors, causing the collected sound signals to contain noise and affecting sound quality. These noise sources are numerous, including equipment interference and electromagnetic interference, such as noise generated by motor rotation and noise generated by electromagnetic signal interference.

[0003] Existing noise cancellation methods include passive and active noise cancellation. Passive noise cancellation primarily reduces noise by blocking sound transmission between the sound-producing device and the ear; therefore, its application scenarios are limited, and its noise reduction effect is not ideal. Active noise cancellation mainly works by capturing noise sound waves and then emitting opposing sound waves to cancel the noise; therefore, active noise cancellation has a better noise reduction effect. However, current devices using active noise cancellation are mainly headphones, and their application scenarios are also very limited, only suitable for specific situations, such as playing music, and not applicable to most scenarios in daily life and work. Therefore, improving the applicability of noise cancellation methods has become an urgent problem to be solved. Summary of the Invention

[0004] To improve the applicability of noise reduction methods, this application provides a sound noise reduction processing method, system, terminal, and storage medium in complex environments.

[0005] The purpose of this application is to provide a method for sound noise reduction in complex environments.

[0006] The aforementioned objective of this application is achieved through the following technical solution:

[0007] A method for sound noise reduction in complex environments includes:

[0008] Acquire multiple audio signals collected by multiple microphones in the same target environment. Each audio signal includes audio information of multiple sounds, and the audio information of one of the multiple sounds includes signal energy.

[0009] Obtain the microphone position information of the multiple microphones;

[0010] Based on a preset first weight allocation rule, the first weight of each audio path is determined according to the microphone position information;

[0011] Based on a preset second weighting allocation rule, the second weight of each sound is determined according to the signal energy;

[0012] A comprehensive weight is determined based on the first weight and the second weight, wherein the comprehensive weight is the weight of each sound among all sounds;

[0013] Each sound is sorted according to the comprehensive weight, and the sorting result is obtained;

[0014] The signal energy is denoised based on the sorting results and a preset threshold.

[0015] By adopting the above technical solution, the comprehensive weight of each sound is determined by the preset first weight allocation rule and the preset second weight allocation rule, and then the signal energy is denoised according to the comprehensive weight and the preset threshold. The collected sound can be the sound of any environment, thereby improving the applicability of the noise reduction method.

[0016] In a preferred embodiment, this application can be further configured such that: obtaining microphone location information of the plurality of microphones includes;

[0017] Establish a spatial rectangular coordinate system;

[0018] The microphone's position is marked on the spatial rectangular coordinate system to obtain spatial coordinate points, which represent the microphone's position information.

[0019] In a preferred embodiment, this application can be further configured such that: the determination of the first weight of each audio path based on the microphone position information according to the preset first weight allocation rule includes;

[0020] Retrieve the spatial center point of the target environment;

[0021] Calculate the line segment distance between the spatial coordinate point and the spatial center point;

[0022] Calculate the sum of the distances of all line segments;

[0023] Calculate the weight of the line segment distance relative to the total distance, and determine the weight as the first weight for each audio path.

[0024] In a preferred embodiment, this application can be further configured such that: determining the second weight of each sound based on the signal energy according to a preset second weight allocation rule includes:

[0025] Calculate the total energy of each sound path;

[0026] Calculate the weight of the signal energy relative to the total energy, and determine the weight as the second weight for each sound.

[0027] In a preferred embodiment, this application may be further configured such that: determining the comprehensive weight based on the first weight and the second weight includes;

[0028] Calculate the product of the first weight and the second weight to obtain the comprehensive weight.

[0029] In a preferred embodiment, this application can be further configured such that: the sorting of each sound according to the comprehensive weight to obtain a sorting result includes;

[0030] Calculate the sum of the combined weights of each sound in the multiple sound paths to obtain the total weight;

[0031] The results are obtained by sorting the data according to the total weights.

[0032] In a preferred embodiment, this application can be further configured such that: the noise reduction of signal energy based on the sorting result and a preset threshold includes;

[0033] Retrieve preset thresholds;

[0034] Compare the summed weight of each sound with a preset threshold;

[0035] If the total weight is less than the preset threshold, the signal energy of the sound will be amplified;

[0036] If the total weight is greater than a preset threshold, the signal energy of the sound will be suppressed.

[0037] The second objective of this application is to provide a sound noise reduction system for complex environments.

[0038] The second objective of this application is achieved through the following technical solution:

[0039] A sound noise reduction system for complex environments includes;

[0040] The first acquisition module is used to acquire multiple sounds collected by multiple microphones in the same target environment. Each sound includes sound information of multiple sounds, and the sound information of one of the multiple sounds includes signal energy.

[0041] The second acquisition module is used to acquire microphone position information of the multiple microphones;

[0042] The first determining module is used to determine the first weight of each sound channel based on the microphone position information according to a preset first weight allocation rule.

[0043] The second determining module is used to determine the second weight of each sound based on the signal energy according to a preset second weight allocation rule.

[0044] The third determining module is used to determine a comprehensive weight based on the first weight and the second weight, wherein the comprehensive weight is the weight of each sound among all sounds;

[0045] The sorting module is used to sort each sound according to the comprehensive weight to obtain the sorting result;

[0046] The noise reduction module is used to reduce the noise of the signal energy based on the sorting result and a preset threshold.

[0047] The third objective of this application is to provide a terminal.

[0048] The aforementioned objective three of this application is achieved through the following technical solution:

[0049] A terminal includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the program to implement the sound noise reduction processing method in any of the above-described complex environments.

[0050] The fourth objective of this application is to provide a computer-readable storage medium capable of storing a corresponding program.

[0051] The fourth objective of this application is achieved through the following technical solution:

[0052] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the sound noise reduction processing method in any of the above-described complex environments.

[0053] In summary, this application includes the following beneficial technical effects:

[0054] The comprehensive weight of each sound is determined by pre-setting the first weight allocation rule and the second weight allocation rule. Then, the signal energy is denoised according to the comprehensive weight and the preset threshold. The collected sound can be the sound of any environment, thereby improving the applicability of the noise reduction method. Attached Figure Description

[0055] Figure 1 This is a schematic flowchart of a sound noise reduction processing method in a complex environment according to an embodiment of this application.

[0056] Figure 2 This is a schematic diagram of a sound noise reduction system in a complex environment according to an embodiment of this application.

[0057] Figure 3 This is a schematic diagram of the terminal structure according to an embodiment of this application.

[0058] Explanation of reference numerals in the attached drawings: 21, First acquisition module; 22, Second acquisition module; 23, First determination module; 24, Second determination module; 25, Third determination module; 26, Sorting module; 27, Noise reduction module; 301, CPU; 302, ROM; 303, RAM; 304, Bus; 305, I / O interface; 306, Input section; 307, Output section; 308, Storage section; 309, Communication section; 310, Driver; 311, Removable medium. Detailed Implementation

[0059] The present application will be further described in detail below with reference to the accompanying drawings.

[0060] This specific embodiment is merely an explanation of this application and is not intended to limit it. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0061] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0062] This application provides a method, system, terminal, and storage medium for sound noise reduction in complex environments, which can improve the applicability of noise reduction methods.

[0063] Reference Figure 1 A flowchart illustrating a sound noise reduction method for complex environments.

[0064] Step S100: Acquire multiple audio signals collected by multiple microphones in the same target environment.

[0065] Specifically, in this application, the target environment can be the internal environment of any enclosed device that needs to collect sound, such as the internal environment of a closed transformer. Multiple microphones are randomly placed inside the transformer. The microphones are used to collect the sound of the equipment inside the transformer working. All the sounds collected by each microphone are one sound path. Therefore, multiple sound paths will be obtained. Each sound path includes the sound information of the equipment working in the internal environment of the transformer. Each sound path includes the sound information of multiple sounds, and the sound information includes the signal energy of each sound.

[0066] Step S200: Obtain microphone position information for multiple microphones.

[0067] Specifically, a spatial rectangular coordinate system is established, with the center point of the spatial rectangular coordinate system being the center point inside the transformer. When the target environment is a non-enclosed space, an enclosed space capable of accommodating the sound of all generating devices is constructed. Subsequently, the positions of the microphones are marked on the spatial rectangular coordinate system to obtain spatial coordinate points. Each spatial coordinate point represents the position of a microphone, and the spatial coordinate points provide microphone position information.

[0068] Step S300: Based on the preset first weight allocation rule, determine the first weight of each audio path according to the microphone position information.

[0069] Specifically, the spatial coordinates of the known center point inside the transformer are retrieved; then, based on a preset point-line formula, the line segment distance between the spatial coordinates and the center point is calculated, with each spatial coordinate point having a line segment distance to the center point; then, all line segment distances are summed to obtain the total distance; finally, the weight of each line segment distance in the total distance is calculated, and this weight is the first weight of each sound channel, which is the weight of each microphone in the total microphones.

[0070] For example, if the microphones are located at points A, B, and C, and the center point of the space is point O, then the distance from point A to point O is the line segment distance A, the distance from point B to point O is the line segment distance B, and the distance from point C to point O is the line segment distance C. The total distance is line segment distance A + line segment distance B + line segment distance C. The weight of line segment distance A is line segment distance A / (line segment distance A + line segment distance B + line segment distance C). That is, the first weight of the sound channel collected by the microphone at point A is line segment distance A / (line segment distance A + line segment distance B + line segment distance C).

[0071] Step S400: Based on the preset second weight allocation rule, determine the second weight of each sound according to the signal energy.

[0072] Specifically, given the signal energy of each sound in each channel, calculate the total energy of that channel, which is the sum of all signal energies in that channel; then calculate the weight of the signal energy in the total energy, which is the second weight of each sound.

[0073] For example, one sound path includes the signal energy A of sound A and the signal energy B of sound B. The total energy of this sound path is signal energy A + signal energy B. The weight of signal energy A is signal energy A / (signal energy A + signal energy), that is, the second weight of sound A in this sound path is signal energy A / (signal energy A + signal energy).

[0074] Step S500: Determine the comprehensive weight based on the first weight and the second weight.

[0075] Specifically, the first weight of one known sound in the total number of sounds, and the second weight of each sound within that sound in the total number of sounds, are multiplied to obtain the comprehensive weight, which is the weight of each sound in the total number of sounds.

[0076] Step S600: Sort each sound according to the comprehensive weight to obtain the sorting result.

[0077] Specifically, the above-mentioned method uses multiple microphones to collect the sound of the equipment working in the internal environment of the transformer. That is, one sound will exist in multiple sound channels. The sum of the comprehensive weights of one sound in multiple sound channels is calculated to obtain the total weight. The results are then sorted according to the total weights to obtain the sorting results.

[0078] For example, if the overall weight of sound A in line A is 0.1, the overall weight in line B is 0.2, and the overall weight in line C is 0.1, then the total weight of sound A is 0.4.

[0079] Step S700: Reduce the noise of the signal energy according to the sorting results and the preset threshold.

[0080] Specifically, a preset threshold is retrieved, and the total weight of each sound is compared with the preset threshold. If the total weight is less than the preset threshold, the signal energy of that sound is amplified; if the total weight is greater than the preset threshold, the signal energy of that sound is suppressed.

[0081] Of course, only one implementation method is disclosed in this application for reference, but the order of all steps is not limited.

[0082] In summary, by setting a first weight allocation rule and a second weight allocation rule to determine the comprehensive weight of each sound, and then reducing the noise of the signal energy according to the comprehensive weight and a preset threshold, the collected sound can be any environmental sound, thereby improving the applicability of the noise reduction method.

[0083] Reference Figure 2 A sound noise reduction processing system for complex environments includes a first acquisition module 21, a second acquisition module 22, a first determination module 23, a second determination module 24, a third determination module 25, a sorting module 26, and a noise reduction module 27, wherein:

[0084] The first acquisition module is used to acquire multiple sounds collected by multiple microphones in the same target environment. Each sound includes sound information of multiple sounds, and the sound information of one of the multiple sounds includes signal energy.

[0085] The second acquisition module is used to acquire microphone position information of multiple microphones;

[0086] The first determining module is used to determine the first weight of each audio path based on the microphone position information according to the preset first weight allocation rule.

[0087] The second determining module is used to determine the second weight of each sound based on the signal energy according to a preset second weight allocation rule.

[0088] The third determining module is used to determine the comprehensive weight based on the first weight and the second weight, wherein the comprehensive weight is the weight of each sound among all sounds;

[0089] The sorting module is used to sort each sound according to a comprehensive weight and obtain the sorting result;

[0090] The noise reduction module is used to reduce the noise of the signal energy based on the sorting results and preset thresholds.

[0091] Reference Figure 3 A schematic diagram of the structure of a terminal.

[0092] The terminal includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 302 or programs loaded from storage into random access memory (RAM) 303. RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via bus 304. Input / output (I / O) interface 305 is also connected to bus 304.

[0093] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to I / O interface 305 as needed. A removable medium 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 310 as needed so that computer programs read from it can be installed into storage section 308 as needed.

[0094] Specifically, according to embodiments of this application, the flowchart above refers to... Figure 1The described process can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a machine-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the functions defined in the system of this application.

[0095] It should be noted that the computer-readable medium shown in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, or any suitable combination thereof.

[0096] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0097] The units or modules described in the embodiments of this application can be implemented in software or hardware. The described units or modules can also be housed in a processor, for example, and can be described as: a processor connecting a first acquisition module 21, a second acquisition module 22, a first determination module 23, a second determination module 24, a third determination module 25, a sorting module 26, and a noise reduction module 27. The names of these units or modules do not necessarily limit the specific unit or module itself; for example, the second acquisition module 22 can also be described as "a module for acquiring microphone position information of multiple microphones".

[0098] In another aspect, this application also provides a computer-readable storage medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable storage medium stores one or more programs that, when used by one or more processors, execute the data encryption transmission method described in this application.

[0099] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A method for sound noise reduction processing in a complex environment, the complex environment being a closed environment, the method comprising: Comprising; ​ acquiring multiple sound collected by multiple microphones in the same target environment, each sound including sound information of multiple sounds, the sound information of one sound including signal energy; acquiring microphone position information of the multiple microphones; determining a first weight of each sound based on a preset first weight distribution rule according to the microphone position information; determining a second weight of each sound based on a preset second weight distribution rule according to the signal energy; determining a comprehensive weight according to the first weight and the second weight, the comprehensive weight being the weight of each sound in all sounds; sorting each sound according to the comprehensive weight to obtain a sorting result; the sorting according to the comprehensive weight to obtain a sorting result, comprising; calculating the sum of the comprehensive weight of each sound in multiple sounds to obtain a total weight; sorting according to the total weight to obtain a sorting result; determining the signal energy according to the sorting result and a preset threshold value; the determination of the signal energy according to the sorting result and a preset threshold value, comprising; calling a preset threshold value; comparing the total weight of each sound with the preset threshold value; if the total weight is less than the preset threshold value, amplifying the signal energy of the sound; if the total weight is greater than the preset threshold value, suppressing the signal energy of the sound.

2. The method of claim 1, wherein: the acquisition of the microphone position information of the multiple microphones, comprising; establishing a space rectangular coordinate system; marking the position of the microphone on the space rectangular coordinate system to obtain a space coordinate point, the space coordinate point being the microphone position information.

3. The method of claim 2, wherein: the determination of the first weight of each sound based on the preset first weight distribution rule according to the microphone position information, comprising; calling a space center point of the target environment; calculating the distance of the line segment between the space coordinate point and the space center point; calculating the distance sum of all line segment distances; calculating the weight of the line segment distance in the distance sum, and determining the weight as the first weight of each sound.

4. The method of claim 1, wherein: the determination of the second weight of each sound based on the preset second weight distribution rule according to the signal energy, comprising; calculating the energy sum of each sound; calculating the weight of the signal energy in the energy sum, and determining the weight as the second weight of each sound.

5. The method of claim 1, wherein: the determination of the comprehensive weight according to the first weight and the second weight, comprising; calculating the product of the first weight and the second weight to obtain the comprehensive weight.

6. A sound noise reduction processing system in a complex environment, the complex environment being an enclosed environment, characterized by: Comprising; a first acquisition module (21) for acquiring multiple sound collected by multiple microphones in the same target environment, each sound including sound information of multiple sounds, the sound information of one sound including signal energy; a second acquisition module (22) for acquiring microphone position information of the multiple microphones; a first determination module (23) for determining a first weight of each sound based on a preset first weight distribution rule according to the microphone position information; a second determination module (24) for determining a second weight of each sound based on a preset second weight distribution rule according to the signal energy; a third determining module (25) configured to determine a comprehensive weight of each sound according to the first weight and the second weight, the comprehensive weight being a weight of each sound in all sounds; a ranking module (26) configured to rank each sound according to the comprehensive weight to obtain a ranking result; the ranking each sound according to the comprehensive weight to obtain the ranking result comprises: calculating a sum of the comprehensive weights of each sound in the multi-path sound to obtain a sum weight; ranking according to the sum weight to obtain the ranking result; a noise reduction module (27) configured to reduce signal energy according to the ranking result and a preset threshold; the reducing signal energy according to the ranking result and the preset threshold comprises: calling the preset threshold; comparing the sum weight of each sound with the preset threshold; if the sum weight is less than the preset threshold, amplifying the signal energy of the sound; if the sum weight is greater than the preset threshold, suppressing the signal energy of the sound.

7. A terminal, characterized by: a memory and a processor, the memory having a computer program stored thereon, and the processor implementing the method of any one of claims 1-5 when executing the program.

8. A computer-readable storage medium, characterized in that: a computer program stored thereon, the program being executed by a processor to implement the method of any one of claims 1-5.

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