Microphone flexible noise reduction method and system

Abstract

The invention relates to the technical field of noise reduction calculation control, in particular to a microphone flexible noise reduction method and system. According to the scheme, the method comprises the steps of setting a microphone array, performing sound collection on each microphone in the microphone array, and generating an independent microphone input signal; noise reduction is carried out on the independent microphone input signal according to a preset noise filtering filter, and the independent microphone input signal serves as a noise reduction signal; comparing and analyzing the noise reduction signal, carrying out noise analysis, and determining a noise frequency band; the average sound pressure of each noise frequency band under the environment noise is extracted; after recording is started, the sound of the noise frequency band is automatically read, comparison is carried out, and the noise filtering range of starting of each microphone is judged; when the environment changes, the environmental noise is automatically collected, the filtering frequency band is set again, and the updating of the automatic filtering noise is completed. According to the scheme, the change of the noise environment is collected, the frequency band of the noise is automatically tracked, the filtering effect is further achieved, and flexible microphone noise reduction based on noise tracking is achieved.

Description

Technical Field

[0001] The present invention relates to the field of noise reduction calculation control technology, and more specifically, to a microphone flexible noise reduction method and system. Background Art

[0002] In the field of noise reduction computing and control, the research on the methods, significance and importance of flexible noise reduction of microphones is reflected in improving the quality of audio signals through innovative algorithms and technologies, and reducing the interference of environmental noise on applications such as speech recognition, communication and recording. This kind of research can not only significantly improve the user experience, but also play a key role in many fields such as medical, security, automobile and consumer electronics, and promote the advancement of related technologies and the popularization of applications.

[0003] Prior to the technology of the present invention, the existing microphone flexible noise reduction methods mainly adopted active noise reduction (ANC) technology, including feedforward, feedback and composite ANC. Feedforward ANC collects noise through an external microphone and generates an anti-noise signal, but is easily affected by wind noise; feedback ANC uses an internal microphone to collect noise, which is more suitable for high-frequency noise processing, but there is a risk of uncontrolled amplification; composite ANC combines the advantages of the first two, but the cost is higher. The difficulty of these technologies lies in how to accurately collect background sounds to provide maximum attenuation, and how to deal with the problem of incomplete phase matching. The key points include selecting the appropriate microphone position, optimizing the algorithm to improve the noise reduction effect, and ensuring the stability and reliability of the system. Summary of the invention

[0004] In view of the above problems, the present invention proposes a microphone flexible noise reduction method and system, which collects changes in the noise environment, automatically tracks the frequency band of the noise, and then achieves a filtering effect, thereby realizing flexible microphone noise reduction based on noise tracking.

[0005] According to a first aspect of an embodiment of the present invention, a microphone flexible noise reduction method is provided.

[0006] In one or more embodiments, preferably, the microphone flexible noise reduction method includes:

[0007] Set up a microphone array, collect sound from each microphone in the microphone array, and generate an independent microphone input signal;

[0008] Denoising the independent microphone input signal according to a preset noise removal filter to obtain a denoised signal;

[0009] Comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band;

[0010] According to the noise frequency band, extracting the average sound pressure of each noise frequency band under the ambient noise;

[0011] After starting recording, the sound of the noise frequency band is automatically read and compared to determine the noise filtering range started by each microphone;

[0012] When the environment changes, the ambient noise is automatically collected, the filtered frequency band is re-set, and the noise is automatically filtered out and updated.

[0013] In one or more embodiments, preferably, the step of setting a microphone array, collecting sound from each microphone in the microphone array, and generating an independent microphone input signal specifically includes:

[0014] According to a predetermined geometric configuration and positional relationship, a plurality of microphones are fixed at specific positions in a certain arrangement to form a microphone array;

[0015] Make sure the distance and angle between each microphone meet the design requirements;

[0016] Each microphone in the microphone array is started to work and collect sound signals in the surrounding environment, and each microphone is used to collect sound to generate an independent microphone input signal.

[0017] In one or more embodiments, preferably, the step of reducing the noise of the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal specifically includes:

[0018] Design noise filtering filters based on the expected noise reduction effect and environmental noise characteristics;

[0019] The sound signal collected by each microphone is input into a preset noise removal filter for processing, and the processed signal is used as a noise reduction signal.

[0020] In one or more embodiments, preferably, the comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band specifically includes:

[0021] The main noise frequency band of the environment is pre-set, and the environmental noise is acquired in the case of actual microphone signal input, wherein the actual microphone signal input is in the case where a person or object does not actively generate the signal and no sound-generating device is enabled;

[0022] Obtaining a noise signal from each microphone, wherein the noise signal is environmental noise;

[0023] Performing frequency analysis on the noise signal and extracting frequency distribution of the noise frequency;

[0024] Obtaining all frequency values ​​corresponding to the sound pressure levels that satisfy the first calculation formula, and then calculating the upper limit and lower limit of the noise frequency band according to the second calculation formula for all frequency values ​​that satisfy the first calculation formula, to generate the noise frequency band;

[0025] The first calculation formula is:

[0026] ZM≥30dB

[0027] Where ZM is the sound pressure level,

[0028] The second calculation formula is:

[0029] SX=ZM+5

[0030] XX=ZM-5

[0031] Wherein, SX is the upper limit of the noise frequency band, ZMf is the frequency value that satisfies the first calculation formula, ZMf is an integer, and XX is the lower limit of the noise frequency band.

[0032] In one or more embodiments, preferably, extracting the average sound pressure of each noise frequency band under the ambient noise according to the noise frequency band specifically includes:

[0033] Obtain each noise frequency band, and then extract the corresponding sounds one by one under the ambient noise;

[0034] The average sound pressure of the sound in each noise frequency band is extracted.

[0035] In one or more embodiments, preferably, after starting recording, automatically reading the sound in the noise frequency band, performing comparison, and determining the noise filtering range started by each microphone specifically includes:

[0036] Extract sound from each microphone separately to obtain the sound in each noise frequency band;

[0037] Calculate the average sound pressure of the sound in each noise frequency band;

[0038] Determine whether the third calculation formula is satisfied. If so, it is considered that the noise can be filtered out. Otherwise, continue to determine the sounds in other noise frequency bands until all noise frequency bands are determined, thus forming all allowable noise frequency bands of the current microphone.

[0039] Using the fourth calculation formula to obtain the current noise filtering range of the microphone;

[0040] Determine the noise filtering range of each microphone one by one to form the noise filtering range activated by each microphone;

[0041] The third calculation formula is:

[0042] S1<1.2×S2

[0043] Among them, S1 is the average sound pressure recorded by the microphone, and S2 is the average sound pressure of the ambient noise;

[0044] The fourth calculation formula is:

[0045] M=U1∪…∪Ui∪…∪Un

[0046] Wherein, M is the noise filtering range of the current microphone, N is the total number of i, and U1, Ui, and Un are the 1st, i, and Nth allowed noise frequency bands.

[0047] In one or more embodiments, preferably, when the environment changes, automatically collecting environmental noise, resetting the filtering frequency band, and completely automatically filtering out the noise update specifically include:

[0048] The sound pressure of several key frequencies of the frequency band of the ambient noise is collected in real time, and if it is determined that the fifth calculation formula is satisfied, the ambient noise update is started;

[0049] If active environmental noise extraction is required, re-extraction is performed;

[0050] After the environmental noise is re-extracted, the noise filtering range of each microphone is recalculated, and the microphone is controlled to perform noise filtering;

[0051] The fifth calculation formula is:

[0052] |L1-L2|>30dB

[0053] Wherein, L1 is the average value of the sound pressure within 1 minute above the key frequency, and L2 is the average value of the sound pressure within 1 minute of the key frequency.

[0054] According to a second aspect of an embodiment of the present invention, a microphone flexible noise reduction system is provided.

[0055] In one or more embodiments, preferably, the microphone flexible noise reduction system includes:

[0056] A microphone positioning module is used to set up a microphone array, collect sound from each microphone in the microphone array, and generate an independent microphone input signal;

[0057] A primary noise reduction module, configured to reduce the noise of the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal;

[0058] A noise frequency band analysis module, used to compare and analyze the noise reduction signal, perform noise analysis, and determine the noise frequency band;

[0059] An environmental sound pressure analysis module, used to extract the average sound pressure of each noise frequency band under environmental noise according to the noise frequency band;

[0060] A flexible filtering control module is used to automatically read the sound of the noise frequency band after starting recording, compare it, and determine the noise filtering range started by each microphone;

[0061] The environment flexible adjustment module is used to automatically collect environmental noise when the environment changes, re-set the filtering frequency band, and completely and automatically filter out the noise update.

[0062] According to a third aspect of an embodiment of the present invention, there is provided a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method as described in any one of the first aspect of the embodiment of the present invention is implemented.

[0063] According to a fourth aspect of an embodiment of the present invention, there is provided an electronic device, comprising a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement any one of the methods described in the first aspect of the embodiment of the present invention.

[0064] The technical solution provided by the embodiments of the present invention may have the following beneficial effects:

[0065] In the solution of the present invention, a method for extracting the optimal solution for online noise reduction based on dynamic optimization is designed to achieve the effect of dynamically filtering out noise.

[0066] In the solution of the present invention, when the noise frequency band that is being tracked changes, it can be quickly filtered out to achieve optimal noise control.

[0067] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0068] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, 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 invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0070] Figure 1 The present invention is a flowchart of a flexible noise reduction method for a microphone according to an embodiment of the present invention.

[0071] Figure 2The present invention is a flowchart of setting a microphone array in a microphone flexible noise reduction method according to an embodiment of the present invention, collecting sound from each microphone in the microphone array, and generating an independent microphone input signal.

[0072] Figure 3 The invention is a flowchart of a method for flexible noise reduction of a microphone according to an embodiment of the present invention, in which the independent microphone input signal is subjected to noise reduction according to a preset noise removal filter to obtain a noise reduction signal.

[0073] Figure 4 The present invention is a flowchart of comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band in a microphone flexible noise reduction method according to an embodiment of the present invention.

[0074] Figure 5 The present invention is a flowchart of extracting the average sound pressure of each noise frequency band under environmental noise according to the noise frequency band in a microphone flexible noise reduction method according to an embodiment of the present invention.

[0075] Figure 6 It is a flowchart of a microphone flexible noise reduction method in one embodiment of the present invention, which automatically reads the sound of the noise frequency band after starting recording, compares it, and determines the noise filtering range started by each microphone.

[0076] Figure 7 The present invention is a flowchart of a flexible microphone noise reduction method in which, when the environment changes, environmental noise is automatically collected, a frequency band is re-set for filtering, and noise is completely and automatically filtered out.

[0077] Figure 8 It is a structural diagram of a microphone flexible noise reduction system according to an embodiment of the present invention.

[0078] Fig. 9 It is a structural diagram of an electronic device in one embodiment of the present invention. DETAILED DESCRIPTION

[0079] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0080] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0081] In the field of noise reduction computing and control, the research on the methods, significance and importance of flexible noise reduction of microphones is reflected in improving the quality of audio signals through innovative algorithms and technologies, and reducing the interference of environmental noise on applications such as speech recognition, communication and recording. This kind of research can not only significantly improve the user experience, but also play a key role in many fields such as medical, security, automobile and consumer electronics, and promote the advancement of related technologies and the popularization of applications.

[0082] Prior to the technology of the present invention, the existing microphone flexible noise reduction methods mainly adopted active noise reduction (ANC) technology, including feedforward, feedback and composite ANC. Feedforward ANC collects noise through an external microphone and generates an anti-noise signal, but is easily affected by wind noise; feedback ANC uses an internal microphone to collect noise, which is more suitable for high-frequency noise processing, but there is a risk of uncontrolled amplification; composite ANC combines the advantages of the first two, but the cost is higher. The difficulty of these technologies lies in how to accurately collect background sounds to provide maximum attenuation, and how to deal with the problem of incomplete phase matching. The key points include selecting the appropriate microphone position, optimizing the algorithm to improve the noise reduction effect, and ensuring the stability and reliability of the system.

[0083] In an embodiment of the present invention, a flexible microphone noise reduction method and system are provided. The solution collects changes in the noise environment, automatically tracks the frequency band of the noise, and then achieves a filtering effect, thereby realizing flexible microphone noise reduction based on noise tracking.

[0084] According to a first aspect of an embodiment of the present invention, a microphone flexible noise reduction method is provided.

[0085] Figure 1 The present invention is a flowchart of a flexible noise reduction method for a microphone according to an embodiment of the present invention.

[0086] In one or more embodiments, preferably, the microphone flexible noise reduction method includes:

[0087] S101, setting a microphone array, collecting sound from each microphone in the microphone array, and generating an independent microphone input signal;

[0088] S102, performing noise reduction on the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal;

[0089] S103, comparing and analyzing the noise reduction signal, performing noise analysis, and determining a noise frequency band;

[0090] S104, extracting the average sound pressure of each noise frequency band under the ambient noise according to the noise frequency band;

[0091] S105, after starting recording, automatically reading the sound of the noise frequency band, performing comparison, and determining the noise filtering range started by each microphone;

[0092] S106. When the environment changes, the environmental noise is automatically collected, the filtering frequency band is re-set, and the complete automatic filtering noise is updated.

[0093] In the embodiment of the present invention, the flexibility involved uses dynamic online data to collect changes in the noise environment and automatically track the frequency band of the noise, thereby achieving a filtering effect. This method is designed to be injected into the microphone to achieve a flexible design of debugging first and then tracking.

[0094] Figure 2 The present invention is a flowchart of setting a microphone array in a microphone flexible noise reduction method according to an embodiment of the present invention, collecting sound from each microphone in the microphone array, and generating an independent microphone input signal.

[0095] like Figure 2 As shown, in one or more embodiments, preferably, the setting of the microphone array, collecting sound from each microphone in the microphone array, and generating an independent microphone input signal specifically includes:

[0096] S201, according to a predetermined geometric configuration and position relationship, a plurality of microphones are fixed at specific positions in a certain arrangement to form a microphone array;

[0097] S202, ensuring that the distance and angle between each microphone meet the design requirements;

[0098] S203: Start each microphone in the microphone array to start working and collect sound signals in the surrounding environment, collect sound from each microphone, and generate an independent microphone input signal.

[0099] In an embodiment of the present invention, an implementation method and system of a microphone flexible noise reduction method are described. First, according to a predetermined geometric configuration and positional relationship, multiple microphones are fixed at specific positions in a certain arrangement to form a microphone array. Specifically, the microphones can be arranged in a linear, circular or other specific shape to ensure that the distance and angle between each microphone meet the design requirements, thereby optimizing the sound collection effect. Next, each microphone in the microphone array is started to start working and collect sound signals in the surrounding environment. Each microphone operates independently to collect the surrounding sounds in real time. These collected sound signals are independent microphone input signals. To illustrate this more clearly, it is assumed that the microphone array system is used in a conference room, and each microphone is placed at different positions of the conference table, such as the chairman's seat, both sides and the back, to cover the sound environment of the entire conference room. When the meeting is in progress, each microphone independently collects the sound signals in its vicinity and generates an independent microphone input signal. These independent microphone input signals are then transmitted to the central processing unit for further signal processing and analysis. In this way, the system can effectively capture and process sound signals from different directions and positions, providing basic data for subsequent noise reduction processing.

[0100] Figure 3 The invention is a flowchart of a method for flexible noise reduction of a microphone according to an embodiment of the present invention, in which the independent microphone input signal is subjected to noise reduction according to a preset noise removal filter to obtain a noise reduction signal.

[0101] like Figure 3 As shown, in one or more embodiments, preferably, the step of reducing the noise of the independent microphone input signal according to a preset noise removal filter as a noise reduction signal specifically includes:

[0102] S301, designing a noise filtering filter according to the expected noise reduction effect and environmental noise characteristics;

[0103] S302: Input the sound signal collected by each microphone into a preset noise removal filter for processing, and use the processed signal as a noise reduction signal.

[0104] In an embodiment of the present invention, the independent microphone input signal is subjected to noise reduction processing according to a preset noise removal filter. First, a suitable noise removal filter is designed according to the expected noise reduction effect and the characteristics of the ambient noise. The design of the filter takes into account a variety of factors, including the frequency characteristics of the ambient noise, the configuration of the microphone array, and the desired noise reduction effect. In actual operation, the sound signal collected by each microphone is independently input into the preset noise removal filter. For example, in a noisy office environment, multiple microphones are distributed in different positions in the room, and each microphone collects sound signals independently. These signals contain components such as speech sounds and background noise. The signals collected by each microphone are independently transmitted to the central processing unit. In the central processing unit, each independent sound signal is processed by the noise removal filter. The filter identifies and removes background noise according to preset parameters and algorithms, and retains useful sound components. The processed signals are noise reduction signals, which can be used for further analysis or transmission. For example, in a conference scene, the sound signal processed in this way can capture the speaker's voice more clearly without being disturbed by surrounding noise.

[0105] Figure 4 The present invention is a flowchart of comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band in a microphone flexible noise reduction method according to an embodiment of the present invention.

[0106] like Figure 4 As shown, in one or more embodiments, preferably, the comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band specifically includes:

[0107] S401, presetting the main noise frequency band of the environment, and acquiring the environmental noise in the case of actual microphone signal input, wherein the actual microphone signal input is in the case where a person or object does not actively generate the signal and does not activate any sound-generating device;

[0108] S402, obtaining a noise signal of each microphone, wherein the noise signal is environmental noise;

[0109] S403, performing frequency analysis on the noise signal, and extracting frequency distribution of the noise frequency;

[0110] S404, obtaining all frequency values ​​corresponding to the sound pressure levels that satisfy the first calculation formula, and then calculating the upper limit and lower limit of the noise frequency band according to the second calculation formula for all the frequency values ​​that satisfy the first calculation formula, to generate the noise frequency band;

[0111] The first calculation formula is:

[0112] ZM≥30dB

[0113] Where ZM is the sound pressure level,

[0114] The second calculation formula is:

[0115] SX=ZM+5

[0116] XX=ZM-5

[0117] Wherein, SX is the upper limit of the noise frequency band, ZMf is the frequency value that satisfies the first calculation formula, ZMf is an integer, and XX is the lower limit of the noise frequency band.

[0118] In an embodiment of the present invention, the noise reduction signal is subjected to noise analysis, and the noise frequency band is determined. First, the main noise frequency band of the environment needs to be pre-set. This step is usually based on the investigation and measurement of the actual environment to identify the frequency range of the main noise source. Next, the environmental noise is acquired under the condition of the actual signal input of the microphone. The "actual signal input of the microphone" here refers to the case where no person or object actively makes a sound and no sound-generating device is enabled. For example, in an office environment, when all personnel remain quiet and turn off all devices that may generate noise (such as air conditioners, fans, etc.), the signal collected by the microphone array is the environmental noise signal. After obtaining the noise signal of each microphone, these noise signals are frequency analyzed, and the frequency distribution of the noise frequency is extracted. This process can be achieved by signal processing techniques such as fast Fourier transform (FFT). By performing spectral analysis on the noise signal, the distribution of noise at different frequencies can be obtained. Then, the frequency value corresponding to the sound pressure level that meets the conditions is determined according to the first calculation formula. The first calculation formula is: ZM≥30dB, where ZM is the sound pressure level. Through this formula, the frequency value with a sound pressure level greater than or equal to 30dB can be screened out. Next, use the second calculation formula to calculate the upper and lower limits of the noise frequency band. The second calculation formula is: SX=ZM+5, XX=ZM-5, where SX is the upper limit of the noise frequency band, ZMf is the frequency value that satisfies the first calculation formula, ZMf is an integer, and XX is the lower limit of the noise frequency band. Through this formula, the frequency values ​​that meet the conditions can be expanded into a frequency band, thereby more accurately describing the frequency range of the noise. For example, assuming that after frequency analysis, it is found that the sound pressure level of a certain frequency value f1 is 32dB, then this frequency value meets the requirements of the first calculation formula. According to the second calculation formula, it can be calculated that the noise frequency band corresponding to this frequency value is [f1-5, f1+5]. In this way, a complete noise frequency band description can be obtained for subsequent noise reduction processing.

[0119] Figure 5 The present invention is a flowchart of extracting the average sound pressure of each noise frequency band under environmental noise according to the noise frequency band in a microphone flexible noise reduction method according to an embodiment of the present invention.

[0120] like Figure 5 As shown, in one or more embodiments, preferably, extracting the average sound pressure of each noise frequency band under the ambient noise according to the noise frequency band specifically includes:

[0121] S501, obtaining each noise frequency band, and then extracting corresponding sounds one by one under the environmental noise;

[0122] S502: extracting the average sound pressure of the sound in each noise frequency band.

[0123] In an embodiment of the present invention, according to the noise frequency band, the average sound pressure of each noise frequency band under ambient noise is extracted. First, each noise frequency band needs to be obtained. This can be obtained by the aforementioned frequency analysis and calculation, that is, the noise frequency band determined by the first calculation formula and the second calculation formula. For example, it is assumed that a certain noise frequency band has been determined to be [f1-5, f1+5]. Next, under ambient noise, the corresponding sounds are extracted one by one. Specifically, for each noise frequency band, the sound components in the frequency band are extracted from the sound signal collected by the microphone array. This process can be implemented by a bandpass filter, which only retains the sound signal in a specific frequency band and filters out the signals of other frequencies. Then, the average sound pressure of the sound in each noise frequency band is extracted. The average sound pressure refers to the energy average value of the sound signal within a certain period of time. By calculating the energy of the sound signal in each noise frequency band, the average sound pressure value of the frequency band can be obtained. This process can be implemented by the following steps: time segmentation: divide the continuous sound signal into several short time segments, for example, each segment is 20 milliseconds. Energy calculation: square and sum the sound signal in each time segment to obtain the total energy of the segment. Average sound pressure calculation: Divide the total energy by the length of the time segment to get the average sound pressure of the time segment. Band average sound pressure: Average the average sound pressure values ​​of all time segments to get the average sound pressure of the noise frequency band. For example, assuming that in a certain noise frequency band [f1-5, f1+5], the average sound pressure values ​​of multiple time segments calculated by the above steps are A1, A2, ..., An. Then the average sound pressure ZM_avg of the noise frequency band can be calculated by the following formula: ZMavg = (∑i = ni = 1A_i) ÷ n; where n is the number of time segments, and A_i is the average sound pressure value of the i-th time segment.

[0124] Figure 6 It is a flowchart of a microphone flexible noise reduction method in one embodiment of the present invention, which automatically reads the sound of the noise frequency band after starting recording, compares it, and determines the noise filtering range started by each microphone.

[0125] like Figure 6As shown, in one or more embodiments, preferably, after starting the recording, automatically reading the sound of the noise frequency band, performing comparison, and determining the noise filtering range started by each microphone specifically includes:

[0126] S601, extracting sound from each microphone separately to obtain sound in each noise frequency band;

[0127] S602, calculating the average sound pressure of the sound in each noise frequency band;

[0128] S603, judging whether the third calculation formula is satisfied, if so, it is considered that the noise can be filtered out, otherwise, the sound in other noise frequency bands is judged continuously until all noise frequency bands are judged, thus forming all the noise frequency bands that can be allowed by the current microphone;

[0129] S604, using a fourth calculation formula to obtain a current noise filtering range of the microphone;

[0130] S605, determining the noise filtering range of each microphone one by one, and forming a noise filtering range activated by each microphone;

[0131] The third calculation formula is:

[0132] S1<1.2×S2

[0133] Among them, S1 is the average sound pressure recorded by the microphone, and S2 is the average sound pressure of the ambient noise;

[0134] The fourth calculation formula is:

[0135] M=U1∪…∪Ui∪…∪Un

[0136] Wherein, M is the noise filtering range of the current microphone, N is the total number of i, and U1, Ui, and Un are the 1st, i, and Nth allowed noise frequency bands.

[0137] In an embodiment of the present invention, after starting recording, the sound of the noise frequency band is automatically read, compared, and the noise filtering range started by each microphone is determined. First, the sound is extracted separately for each microphone to obtain the sound in each noise frequency band. This can be achieved by the aforementioned bandpass filter, and only the sound signal in a specific frequency band is retained. Next, the average sound pressure of the sound in each noise frequency band is calculated. This process can be achieved by the following steps: Time segmentation: Divide the continuous sound signal into several short time segments, for example, each segment is 20 milliseconds. Energy calculation: Square and sum the sound signal in each time segment to obtain the total energy of the segment. Average sound pressure calculation: Divide the total energy by the length of the time segment to obtain the average sound pressure of the time segment. Band average sound pressure: Average the average sound pressure values ​​of all time segments to obtain the average sound pressure of the noise frequency band. Then, it is determined whether the third calculation formula is satisfied. If it is satisfied, it is considered that the noise can be filtered. Otherwise, the sound in other noise frequency bands is continued to be judged until all noise frequency bands are judged, and all noise frequency bands that can be allowed by the current microphone are formed. Determine the noise filtering range of each microphone one by one to form the noise filtering range activated by each microphone. The third calculation formula is: S1<1.2×S2; wherein S1 is the average sound pressure recorded by the microphone, and S2 is the average sound pressure of the ambient noise. The fourth calculation formula is: M=U1∪…∪Ui∪…∪Un; wherein M is the noise filtering range of the current microphone, N is the total number of i, and U1, Ui, and Un are the 1st, i, and Nth allowed noise frequency bands. Next, determine whether the third calculation formula is satisfied: S1<1.2×S2; if satisfied, it is considered that the noise can be filtered; if not satisfied, continue to judge the sounds in other noise frequency bands until all noise frequency bands are judged. Finally, the fourth calculation formula is used to obtain the current noise filtering range of the microphone: M = U1∪…∪Ui∪…∪Un; where M is the current noise filtering range of the microphone, N is the total number of i, and U1, Ui, and Un are the 1st, i, and Nth allowed noise frequency bands. In this way, the noise filtering range of each microphone can be accurately determined, thereby achieving a more accurate noise reduction effect.

[0138] Figure 7 The present invention is a flowchart of a flexible microphone noise reduction method in which, when the environment changes, environmental noise is automatically collected, a frequency band is re-set for filtering, and noise is completely and automatically filtered out.

[0139] like Figure 7 As shown, in one or more embodiments, preferably, when the environment changes, the environmental noise is automatically collected, the frequency band is re-filtered, and the complete automatic noise filtering is updated, specifically including:

[0140] S701, collecting sound pressures of several key frequencies of the frequency band of ambient noise in real time, and starting ambient noise update if it is determined that the fifth calculation formula is satisfied;

[0141] S702: if it is necessary to actively extract the environmental noise, then re-extract it;

[0142] S703, after the environmental noise is re-extracted, the noise filtering range of each microphone is recalculated, and the microphone is controlled to perform noise filtering;

[0143] The fifth calculation formula is:

[0144] |L1-L2|>30dB

[0145] Wherein, L1 is the average value of the sound pressure within 1 minute above the key frequency, and L2 is the average value of the sound pressure within 1 minute of the key frequency.

[0146] In an embodiment of the present invention, when there is a change in the environment, the environmental noise is automatically collected, the filtering frequency band is re-set, and the complete automatic filtering noise update. First, the sound pressure of several key frequencies of the frequency band of the environmental noise is collected in real time. This can be achieved by the aforementioned bandpass filter, and only the sound signal in a specific frequency band is retained. Then, it is determined whether the fifth calculation formula is satisfied. If it is satisfied, the environmental noise update is started; if it is not satisfied, the change of the environmental noise is continued to be monitored. The fifth calculation formula is: |L1-L2|>30dB; wherein L1 is the average value of the sound pressure within the last 1 minute of the key frequency, and L2 is the average value of the sound pressure within the current 1 minute of the key frequency. If it is necessary to actively extract the environmental noise, it is re-extracted. This can be achieved by the aforementioned method, that is, extracting sound for each microphone separately, obtaining the sound in each noise frequency band, and calculating the average sound pressure. After the environmental noise is re-extracted, the noise filtering range of each microphone is recalculated, and the microphone is controlled to perform noise filtering. Determine whether the third calculation formula is satisfied. If it is satisfied, it is considered that the noise can be filtered out. Otherwise, continue to judge the sounds in other noise frequency bands until all noise frequency bands are judged, and then all the noise frequency bands that can be allowed by the current microphone are formed. Determine the noise filtering range of each microphone one by one to form the noise filtering range started by each microphone. In this way, when the environment changes, it can be realized that the environmental noise is automatically collected, the filtering frequency band is re-set, and the complete automatic filtering noise is updated.

[0147] According to a second aspect of an embodiment of the present invention, a microphone flexible noise reduction system is provided.

[0148] Figure 8 It is a structural diagram of a microphone flexible noise reduction system according to an embodiment of the present invention.

[0149] In one or more embodiments, preferably, the microphone flexible noise reduction system includes:

[0150] The microphone positioning module 801 is used to set up a microphone array, collect sound from each microphone in the microphone array, and generate an independent microphone input signal;

[0151] A primary noise reduction module 802, configured to reduce the noise of the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal;

[0152] A noise frequency band analysis module 803 is used to compare and analyze the noise reduction signal, perform noise analysis, and determine the noise frequency band;

[0153] The environmental sound pressure analysis module 804 is used to extract the average sound pressure of each noise frequency band under the environmental noise according to the noise frequency band;

[0154] The flexible filtering control module 805 is used to automatically read the sound of the noise frequency band after starting the recording, compare it, and determine the noise filtering range started by each microphone;

[0155] The environment flexible adjustment module 806 is used to automatically collect environmental noise when the environment changes, re-set the filtering frequency band, and completely and automatically filter out the update of noise.

[0156] In the embodiment of the present invention, a system suitable for different structures is realized through a series of modular designs. The system can achieve closed-loop, reliable and efficient execution through collection, analysis and control.

[0157] According to a third aspect of an embodiment of the present invention, there is provided a computer-readable storage medium on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method as described in any one of the first aspect of the embodiment of the present invention is implemented.

[0158] According to a fourth aspect of an embodiment of the present invention, an electronic device is provided. Fig. 9 It is a structural diagram of an electronic device in one embodiment of the present invention. Fig. 9 The electronic device shown is a universal microphone flexible noise reduction device. Fig. 9 The electronic device 900 includes one or more (only one is shown in the figure) processors 902, a memory 904 and a wireless module 906 coupled to each other. The memory 904 stores a program that can execute the content of the above-mentioned embodiment, and the processor 902 can execute the program stored in the memory 904.

[0159] The processor 902 may include one or more processing cores. The processor 902 uses various interfaces and lines to connect various parts of the entire electronic device 900, and executes various functions and processes data of the electronic device 900 by running or executing instructions, programs, code sets or instruction sets stored in the memory 904, and calling data stored in the memory 904. Optionally, the processor 902 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), and programmable logic array (PLA). The processor 902 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU mainly processes the operating system, the user interface, and the target application; the GPU is responsible for rendering and drawing the display content; and the modem is used to process wireless communications. It is understandable that the above-mentioned modem may not be integrated into the processor 902, but may be implemented separately through a communication chip.

[0160] The memory 904 may include a random access memory (RAM) or a read-only memory (ROM). The memory 904 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 904 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the following various method embodiments, etc. The data storage area may also store data (such as the aforementioned text document) created by the electronic device 900 during use, etc.

[0161] The wireless module 906 is used to receive and send electromagnetic waves, realize the mutual conversion between electromagnetic waves and electrical signals, and thus communicate with a communication network or other equipment, for example, communicate with a base station based on a mobile communication protocol. The wireless module 906 may include various existing circuit elements for performing these functions, for example, an antenna, a radio frequency transceiver, a digital signal processor, an encryption / decryption chip, a user identity module (SIM) card, a memory, etc. The wireless module 906 may communicate with various networks such as the Internet, an intranet, a wireless network, or communicate with other electronic devices through a wireless network. The above-mentioned wireless network may include a cellular telephone network, a wireless local area network, or a metropolitan area network. The above-mentioned wireless network may use various communication standards, protocols, and technologies, including but not limited to WLAN protocols and Bluetooth protocols, and may even include those protocols that have not yet been developed.

[0162] The technical solution provided by the embodiments of the present invention may have the following beneficial effects:

[0163] In the solution of the present invention, a method for extracting the optimal solution for online noise reduction based on dynamic optimization is designed to achieve the effect of dynamically filtering out noise.

[0164] In the solution of the present invention, when the noise frequency band that is being tracked changes, it can be quickly filtered out to achieve optimal noise control.

[0165] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0166] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0167] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0168] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0169] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A microphone flexible noise reduction method, characterized in that: The method includes: Set up a microphone array, collect sound from each microphone in the microphone array, and generate an independent microphone input signal; Denoising the independent microphone input signal according to a preset noise removal filter to obtain a denoised signal; Comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band; According to the noise frequency band, extracting the average sound pressure of each noise frequency band under the ambient noise; After starting recording, the sound of the noise frequency band is automatically read and compared to determine the noise filtering range started by each microphone; When the environment changes, the ambient noise is automatically collected, the filtered frequency band is re-set, and the noise is automatically filtered out and updated.

2. A microphone flexible noise reduction method as claimed in claim 1, characterized in that: The step of setting up a microphone array, collecting sound from each microphone in the microphone array, and generating an independent microphone input signal specifically includes: According to a predetermined geometric configuration and positional relationship, a plurality of microphones are fixed at specific positions in a certain arrangement to form a microphone array; Make sure the distance and angle between each microphone meet the design requirements; Each microphone in the microphone array is started to work and collect sound signals in the surrounding environment, and each microphone is used to collect sound to generate an independent microphone input signal.

3. A microphone flexible noise reduction method as claimed in claim 1, characterized in that: The step of reducing the noise of the independent microphone input signal according to the preset noise removal filter to obtain the noise reduction signal specifically includes: Design noise filtering filters based on the expected noise reduction effect and environmental noise characteristics; The sound signal collected by each microphone is input into a preset noise removal filter for processing, and the processed signal is used as a noise reduction signal.

4. A microphone flexible noise reduction method as claimed in claim 1, characterized in that: The comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band specifically includes: The main noise frequency band of the environment is pre-set, and the environmental noise is acquired in the case of actual microphone signal input, wherein the actual microphone signal input is in the case where a person or object does not actively generate the signal and no sound-generating device is enabled; Obtaining a noise signal from each microphone, wherein the noise signal is environmental noise; Performing frequency analysis on the noise signal and extracting frequency distribution of the noise frequency; Obtaining all frequency values ​​corresponding to the sound pressure levels that satisfy the first calculation formula, and then calculating the upper limit and lower limit of the noise frequency band according to the second calculation formula for all frequency values ​​that satisfy the first calculation formula, to generate the noise frequency band; The first calculation formula is: ZM≥30dB Where ZM is the sound pressure level, The second calculation formula is: SX=ZM+5 XX=ZM-5 Wherein, SX is the upper limit of the noise frequency band, ZMf is the frequency value that satisfies the first calculation formula, ZMf is an integer, and XX is the lower limit of the noise frequency band.

5. A microphone flexible noise reduction method as claimed in claim 1, characterized in that: The step of extracting the average sound pressure of each noise frequency band under the ambient noise according to the noise frequency band specifically includes: Obtain each noise frequency band, and then extract the corresponding sounds one by one under the ambient noise; The average sound pressure of the sound in each noise frequency band is extracted.

6. A microphone flexible noise reduction method as claimed in claim 1, characterized in that: After the recording is started, the sound of the noise frequency band is automatically read and compared to determine the noise filtering range started by each microphone, specifically including: Extract sound from each microphone separately to obtain the sound in each noise frequency band; Calculate the average sound pressure of the sound in each noise frequency band; Determine whether the third calculation formula is satisfied. If so, it is considered that the noise can be filtered out. Otherwise, continue to determine the sounds in other noise frequency bands until all noise frequency bands are determined, thus forming all allowable noise frequency bands of the current microphone. Using the fourth calculation formula to obtain the current noise filtering range of the microphone; Determine the noise filtering range of each microphone one by one to form the noise filtering range activated by each microphone; The third calculation formula is: S1<1.2×S2 Among them, S1 is the average sound pressure recorded by the microphone, and S2 is the average sound pressure of the ambient noise; The fourth calculation formula is: M=U1∪…∪Ui∪…∪Un Wherein, M is the noise filtering range of the current microphone, N is the total number of i, and U1, Ui, and Un are the 1st, i, and Nth allowed noise frequency bands.

7. A microphone flexible noise reduction method as claimed in claim 1, characterized in that: When the environment changes, the environmental noise is automatically collected, the frequency band is re-set to filter out the noise, and the complete automatic noise filtering is updated, specifically including: The sound pressure of several key frequencies of the frequency band of the ambient noise is collected in real time, and if it is determined that the fifth calculation formula is satisfied, the ambient noise update is started; If active environmental noise extraction is required, re-extraction is performed; After the environmental noise is re-extracted, the noise filtering range of each microphone is recalculated, and the microphone is controlled to perform noise filtering; The fifth calculation formula is: |L1-L2|>30dB Wherein, L1 is the average value of the sound pressure within 1 minute above the key frequency, and L2 is the average value of the sound pressure within 1 minute of the key frequency.

8. A microphone flexible noise reduction system, characterized in that: The system is used to implement the method according to any one of claims 1 to 7, and the system comprises: A microphone positioning module is used to set up a microphone array, collect sound from each microphone in the microphone array, and generate an independent microphone input signal; A primary noise reduction module, configured to reduce the noise of the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal; A noise frequency band analysis module, used to compare and analyze the noise reduction signal, perform noise analysis, and determine the noise frequency band; An environmental sound pressure analysis module, used to extract the average sound pressure of each noise frequency band under environmental noise according to the noise frequency band; A flexible filtering control module is used to automatically read the sound of the noise frequency band after starting recording, compare it, and determine the noise filtering range started by each microphone; The environment flexible adjustment module is used to automatically collect environmental noise when the environment changes, re-set the filtering frequency band, and completely and automatically filter out the noise update.

9. A computer-readable storage medium storing computer program instructions, characterized in that: The computer program instructions implement the method according to any one of claims 1 to 7 when executed by a processor.

10. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of claims 1-7.

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