A flexible noise reduction method and system for microphone

Abstract

The present invention relates to the field of noise reduction calculation and control technology, and more specifically, to a flexible noise reduction method and system for microphones. The solution includes setting up a microphone array, collecting sound from each microphone in the microphone array, and generating an independent microphone input signal; reducing the noise of the independent microphone input signal according to a preset noise filtering filter as a noise reduction signal; comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band; extracting the average sound pressure of each noise frequency band under ambient noise; after starting recording, automatically reading the sound of the noise frequency band, comparing, and judging the noise filtering range started by each microphone; when the environment changes, automatically collecting ambient noise, resetting the filtering frequency band, and completely and automatically filtering out the noise. The solution collects changes in the noise environment, automatically tracks the frequency band of the noise, and then achieves the filtering effect, realizing flexible microphone noise reduction based on noise tracking.

Description

Technical Field

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

[0002] In the field of noise reduction computing and control, the research on flexible microphone noise reduction methods, significance, and importance lies in improving audio signal quality through innovative algorithms and technologies, reducing the interference of ambient noise on applications such as speech recognition, communications, and recording. This research not only significantly improves the user experience but also plays a key role in various fields such as healthcare, security, automotive, and consumer electronics, promoting the advancement of related technologies and the popularization of their 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 flexible microphone 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, realizing flexible microphone noise reduction based on noise tracking.

[0005] According to a first aspect of an embodiment of the present invention, a method for flexible noise reduction of a microphone 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] performing noise reduction on the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal;

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

[0010] Extracting the average sound pressure of each noise frequency band under the ambient noise according to the noise frequency band;

[0011] After starting the recording, the sound of the noise frequency band is automatically read and compared to determine the noise filtering range activated 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.

[0013] In one or more embodiments, preferably, 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:

[0014] 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;

[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 and generate an independent microphone input signal.

[0017] In one or more embodiments, preferably, the step of performing noise reduction on the independent microphone input signal according to a preset noise removal filter to obtain the 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 the 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] Presetting the main noise frequency band of the environment, and acquiring the environmental noise when the microphone actually inputs the signal, wherein the actual microphone signal input is not actively generated by a person or object and no sound-generating device is activated;

[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 and lower limits 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 sound 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 activated 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, the noise is considered to be filterable. Otherwise, continue to determine the sounds in other noise frequency bands until all noise frequency bands are determined, thus forming the total allowable noise frequency bands for 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] Where 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 filtered frequency band, and completely updating the automatically filtered noise specifically include:

[0048] The sound pressure of several key frequencies in 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 sound pressure value within the previous minute of the key frequency, and L2 is the average sound pressure value within the current minute of the key frequency.

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

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

[0056] The microphone positioning module is used to set up the 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, configured to extract the average sound pressure of each noise frequency band under the 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 activated 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 update the filtered noise.

[0062] According to a third aspect of an embodiment of the present invention, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method according to 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, an electronic device is provided, 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 solutions 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 online noise reduction solution based on dynamic optimization is designed to achieve the effect of dynamic noise filtering.

[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 in part will become apparent from the description, or will be understood by practicing the present invention. The purposes 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 following briefly introduces the drawings required for use in the description of the embodiments. 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 This is a flow chart 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 flexible microphone 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 present 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 flexible noise reduction method for a microphone 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 ambient noise according to the noise frequency band in a flexible noise reduction method for a microphone according to an embodiment of the present invention.

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

[0076] Figure 7 This is a flowchart of a flexible microphone noise reduction method according to an embodiment of the present invention, which automatically collects environmental noise, re-sets the filtering frequency band, and completely and automatically filters out noise when the environment changes.

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

[0078] Figure 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 may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between 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., and do not represent the order of precedence, nor do they limit "first" and "second" to be different types.

[0080] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0081] In the field of noise reduction computing and control, the research on flexible microphone noise reduction methods, significance, and importance lies in improving audio signal quality through innovative algorithms and technologies, reducing the interference of ambient noise on applications such as speech recognition, communications, and recording. This research not only significantly improves the user experience but also plays a key role in various fields such as healthcare, security, automotive, and consumer electronics, promoting the advancement of related technologies and the popularization of their 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. This 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 method for flexible noise reduction of a microphone is provided.

[0085] Figure 1 This is a flow chart 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 the 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 activated 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 update is completed.

[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 first debugging and then tracking.

[0094] Figure 2 The present invention is a flowchart of setting a microphone array in a flexible microphone 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 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:

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

[0097] S202. Ensure 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 for each microphone, and generate an independent microphone input signal.

[0099] In an embodiment of the present invention, a flexible microphone noise reduction method and system are described. First, multiple microphones are fixed in a specific arrangement based on a predetermined geometric configuration and positional relationship 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 design requirements, thereby optimizing sound collection. Next, each microphone in the microphone array is activated to begin collecting sound signals from the surrounding environment. Each microphone operates independently, collecting surrounding sound in real time. These collected sound signals are independent microphone input signals. To illustrate this more clearly, assume that the microphone array system is used in a conference room, with each microphone placed at a different location on the conference table, such as the chairperson's seat, on the sides, and behind, to cover the entire conference room's acoustic environment. During the meeting, each microphone independently collects sound signals from its surrounding area, generating independent microphone input signals. These independent microphone input signals are then transmitted to a 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 locations, providing basic data for subsequent noise reduction.

[0100] Figure 3 The present 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 performing noise reduction on the independent microphone input signal according to a preset noise removal filter to obtain the noise reduction signal specifically includes:

[0102] S301. Design a noise filtering filter based on 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, noise reduction is performed on individual microphone input signals using a preset noise removal filter. First, a suitable noise removal filter is designed based on the desired noise reduction effect and the characteristics of the ambient noise. The design of this filter takes into account various factors, including the frequency characteristics of the ambient noise, the configuration of the microphone array, and the desired noise reduction effect. In practice, the sound signal collected by each microphone is independently input into this preset noise removal filter. For example, in a noisy office environment, multiple microphones are distributed in different locations in the room, each independently collecting sound signals. These signals contain components such as speech and background noise. The signals collected by each microphone are independently transmitted to a central processing unit (CPU). Within the CPU, each individual sound signal is processed by a noise removal filter. Based on preset parameters and algorithms, the filter identifies and removes background noise, retaining the useful sound components. The resulting signal is the noise-reduced signal, which can be used for further analysis or transmission. For example, in a conference setting, the sound signal processed in this way can more clearly capture the speaker's voice without interference from 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 flexible noise reduction method for a microphone 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: Preset a main noise frequency band of the environment, and acquire the environmental noise when a microphone actually inputs a signal, wherein the actual microphone signal input is not actively generated by a person or object and no sound-generating device is activated;

[0108] S402: Obtain a noise signal from 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: Obtain all frequency values ​​corresponding to the sound pressure levels that satisfy the first calculation formula, and then calculate the upper and lower limits 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;

[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, noise analysis is performed on the noise reduction signal to determine the noise frequency band. First, the dominant noise frequency band of the environment needs to be pre-set. This step is typically based on surveys and measurements of the actual environment to identify the frequency range of the main noise sources. Next, ambient noise is acquired while the microphone is actually inputting a signal. "Actual microphone input" here refers to the situation where no one or any object is actively making any sound, and no sound-generating devices are enabled. For example, in an office environment, when all personnel remain silent and all potentially noise-generating devices (such as air conditioners and fans) are turned off, the signal collected by the microphone array is the ambient noise signal. After obtaining the noise signal from each microphone, these noise signals are subjected to frequency analysis, and the frequency distribution of the noise frequencies is extracted. This process can be achieved using 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 determined. Then, the frequency value corresponding to the sound pressure level that meets the conditions is determined according to a first calculation formula. The first calculation formula is: ZM ≥ 30dB, where ZM is the sound pressure level. This formula can be used to filter out frequency values ​​with a sound pressure level greater than or equal to 30dB. 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. This formula can expand the frequency values ​​that meet the conditions into a frequency band, thereby more accurately describing the frequency range of the noise. For example, suppose 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, the noise frequency band corresponding to this frequency value can be calculated as [f1-5, f1+5]. In this way, a complete description of the noise frequency band 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 ambient noise according to the noise frequency band in a flexible noise reduction method for a microphone 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 the corresponding sounds one by one under the ambient noise;

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

[0123] In this embodiment of the present invention, the average sound pressure of each noise frequency band under ambient noise is extracted based on the noise frequency band. First, each noise frequency band needs to be obtained. This can be obtained through the aforementioned frequency analysis and calculation, namely, the noise frequency band determined by the first and second calculation formulas. For example, assume that a noise frequency band has been determined to be [f1-5, f1+5]. Next, the corresponding sound is extracted one by one under ambient noise. Specifically, for each noise frequency band, the sound components within that frequency band are extracted from the sound signal collected by the microphone array. This process can be achieved using a bandpass filter, which retains only the sound signals within a specific frequency band and filters out signals of other frequencies. Then, the average sound pressure of the sound in each noise frequency band is extracted. Average sound pressure refers to the average energy of the sound signal over a certain period of time. By calculating the energy of the sound signal within each noise frequency band, the average sound pressure value of that frequency band can be obtained. This process can be achieved through the following steps: Time segmentation: The continuous sound signal is divided into several short time segments, for example, each segment is 20 milliseconds. Energy calculation: The squares of the sound signals within each time segment are summed 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 for that 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 segment. For example, assume that within a noise frequency band [f1-5, f1+5], the average sound pressure values ​​of multiple time segments calculated using the above steps are A1, A2, ..., An. The average sound pressure ZM_avg of the noise frequency band can then be calculated using 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 This is a flowchart of a microphone flexible noise reduction method in one embodiment of the present invention, which automatically reads the sound in 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 recording, automatically reading the sound of the noise frequency band, performing comparison, and determining the noise filtering range activated 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: Determine whether the third calculation formula is satisfied. If so, the noise is considered to be filterable. Otherwise, continue to determine sounds in other noise frequency bands until all noise frequency bands are determined, thereby forming the total allowable noise frequency bands for the current microphone.

[0129] S604: Obtain the current noise filtering range of the microphone using a fourth calculation formula;

[0130] S605: Determine the noise filtering range of each microphone one by one to form the 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] Where 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 recording is initiated, the sound within the noise frequency band is automatically read and compared to determine the noise filtering range enabled for each microphone. First, sound is extracted from each microphone individually to obtain the sound within each noise frequency band. This can be achieved using the aforementioned bandpass filter, which only retains the sound signal within a specific frequency band. Next, the average sound pressure of the sound within each noise frequency band is calculated. This process can be achieved through the following steps: Time segmentation: The continuous sound signal is divided into several short time segments, for example, each segment is 20 milliseconds. Energy calculation: The squares of the sound signals within each time segment are summed to obtain the total energy of the segment. Average sound pressure calculation: The total energy is divided by the length of the time segment to obtain the average sound pressure of the time segment. Band average sound pressure: The average sound pressure values ​​of all time segments are averaged to obtain the average sound pressure of the noise frequency band. Then, a determination is made as to whether the third calculation formula is satisfied. If so, the noise is considered to be filterable. Otherwise, the sound within other noise frequency bands is continuously evaluated until all noise frequency bands have been evaluated, thereby determining the total allowable noise frequency bands for the current 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; 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 determine the current microphone's noise filtering range: M = U1∪…∪Ui∪…∪Un; where M is the current microphone's noise filtering range, N is the total number of i, and U1, Ui, and Un are the first, i, and Nth allowed noise frequency bands. This method accurately determines the noise filtering range of each microphone, achieving more precise noise reduction.

[0138] Figure 7 This is a flowchart of a flexible microphone noise reduction method according to an embodiment of the present invention, which automatically collects environmental noise, re-sets the filtering frequency band, and completely and automatically filters out noise when the environment changes.

[0139] like Figure 7 As shown, in one or more embodiments, preferably, when the environment changes, automatically collecting environmental noise, resetting the filtered frequency band, and completely updating the automatic noise filtering specifically include:

[0140] S701: Collect the sound pressure of several key frequencies of the frequency band of the ambient noise in real time, and if it is determined that the fifth calculation formula is satisfied, start updating the ambient noise;

[0141] S702: If active environmental noise extraction is required, re-extraction is performed;

[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 sound pressure value within the previous minute of the key frequency, and L2 is the average sound pressure value within the current minute of the key frequency.

[0146] In an embodiment of the present invention, when the environment changes, ambient noise is automatically collected, the filtered frequency band is re-set, and the fully automatic noise filtering is updated. First, the sound pressure of several key frequencies in the ambient noise frequency band is collected in real time. This can be achieved using the aforementioned bandpass filter, retaining only the sound signals within the specific frequency band. Next, a determination is made as to whether the fifth calculation formula is satisfied. If so, the ambient noise update is initiated; if not, the ambient noise changes are continuously monitored. The fifth calculation formula is: |L1-L2|>30dB; where L1 is the average sound pressure of the key frequency within the previous minute, and L2 is the average sound pressure of the key frequency within the current minute. If active ambient noise extraction is required, re-extraction is performed. This can be achieved using the aforementioned method, namely, extracting sound from each microphone individually, obtaining sound within each noise frequency band, and calculating the average sound pressure. After the ambient noise is re-extracted, the noise filtering range for each microphone is recalculated, and the microphone is controlled to perform noise filtering. The system then determines whether the third calculation formula is satisfied. If so, the noise is considered filterable. Otherwise, the system continues evaluating sounds in other noise frequency bands until all noise frequency bands have been evaluated, forming the total allowable noise frequency band for the current microphone. The noise filtering range of each microphone is determined individually to form the activated noise filtering range for each microphone. This approach allows for automatic noise collection and resetting of the filter frequency bands as the environment changes, completely updating the noise filtering.

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

[0148] Figure 8 This 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 for performing noise reduction on the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal;

[0152] The 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] An environmental sound pressure analysis module 804 is configured 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 activated 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 update the filtered noise.

[0156] In the embodiment of the present invention, a system applicable to 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, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method according to any one of the first aspect of the embodiment of the present invention is implemented.

[0158] According to a fourth aspect of the embodiments of the present invention, an electronic device is provided. Figure 9 It is a structural diagram of an electronic device in one embodiment of the present invention. Figure 9 The electronic device shown is a universal microphone flexible noise reduction device. Figure 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 aforementioned embodiments, 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 utilizes various interfaces and circuits to connect various components within the electronic device 900. It executes various functions and processes data for the electronic device 900 by running or executing instructions, programs, code sets, or instruction sets stored in the memory 904, and by accessing data stored in the memory 904. Optionally, the processor 902 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a 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 primarily processes the operating system, user interface, and target applications; the GPU is responsible for rendering and drawing display content; and the modem handles 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 documents) created by the electronic device 900 during use.

[0161] The wireless module 906 is used to receive and transmit electromagnetic waves, realize the mutual conversion between electromagnetic waves and electrical signals, and thus communicate with a communication network or other devices, for example, communicate with a base station based on a mobile communication protocol. The wireless module 906 may include various existing circuit components 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 can communicate with various networks such as the Internet, an enterprise intranet, a wireless network, or communicate with other electronic devices via 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 protocols that have not yet been developed.

[0162] The technical solutions 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 online noise reduction solution based on dynamic optimization is designed to achieve the effect of dynamic noise filtering.

[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. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, 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 magnetic 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 flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, 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 flowcharts and / or block diagrams. 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 that can direct a computer or other programmable data processing device to work 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 The 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 operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

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

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; performing noise reduction on the independent microphone input signal according to a preset noise removal filter to obtain a noise reduction signal; Comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band; Extracting the average sound pressure of each noise frequency band under the ambient noise according to the noise frequency band; After starting the recording, the sound of the noise frequency band is automatically read and compared to determine the noise filtering range activated by each microphone; When the environment changes, it automatically collects environmental noise, re-sets the filtering frequency band, and automatically updates the noise filtering. The comparing and analyzing the noise reduction signal, performing noise analysis, and determining the noise frequency band specifically includes: Presetting the main noise frequency band of the environment, and acquiring the environmental noise when the microphone actually inputs the signal, wherein the actual microphone signal input is not actively generated by a person or object and no sound-generating device is activated; 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 and lower limits 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.

2. A microphone flexible noise reduction method according to 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, multiple 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 and generate an independent microphone input signal.

3. The flexible noise reduction method for a microphone according to claim 1, wherein: The step of performing noise reduction on the independent microphone input signal according to a 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 the noise reduction signal.

4. The flexible noise reduction method for a microphone according to claim 1, wherein: 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 sound one by one under the ambient noise; The average sound pressure of the sound in each noise frequency band is extracted.

5. The flexible noise reduction method for a microphone according to claim 1, wherein: After starting the recording, the sound of the noise frequency band is automatically read and compared to determine the noise filtering range activated 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, the noise is considered to be filterable. Otherwise, continue to determine the sounds in other noise frequency bands until all noise frequency bands are determined, thus forming the total allowable noise frequency bands for 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 Where 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.

6. The flexible noise reduction method for a microphone according to claim 1, wherein: When the environment changes, the ambient noise is automatically collected, the frequency band to be filtered out is re-set, and the complete automatic noise filtering is updated, specifically including: The sound pressure of several key frequencies in 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 sound pressure value within the previous minute of the key frequency, and L2 is the average sound pressure value within the current minute of the key frequency.

7. 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 6, and the system comprises: The microphone positioning module is used to set up the 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, configured to extract the average sound pressure of each noise frequency band under the 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 activated 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 update the filtered noise.

8. 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 6 when executed by a processor.

9. An electronic device comprising a memory and a processor, characterized in that: The memory is configured 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 to 6.

Images