Earphone noise reduction method and device

Abstract

The invention provides an earphone noise reduction method and device. The method comprises the following steps: carrying out discrete transformation processing on a variable control filter bank; calculating the weight of each sub-filter based on the earphone noise signal, and determining a new filter based on the weights of the sub-filters and the time domain representation; calculating a first filtered output and a second filtered output based on the filter coefficients; updating the filter coefficient of the new filter based on the first filtering output and the second filtering output to obtain an updated filter coefficient; and calculating a noise elimination signal based on the earphone noise signal and the update filter coefficient, and controlling the update filter to output the noise elimination signal to eliminate the earphone noise signal, thereby reducing the error between the offset signal and the earphone noise signal, improving the accuracy of the offset signal, and improving the corresponding noise reduction effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of headphone noise reduction, and in particular relates to a headphone noise reduction method and device. Background Art

[0002] In recent years, with the rapid development of artificial intelligence and mobile communication technology, the research of wireless Bluetooth headsets has become a hot field. People can use wireless Bluetooth headsets to achieve human-computer interaction and interpersonal communication. Usually, the sound field environment where the wearer is located has a lot of noise, human voice and other interference, which will seriously affect the wearer's voice experience.

[0003] As for the noise reduction in the prior art, it usually performs noise reduction processing by outputting a reverse cancellation signal which is the same as the noise through a built-in filter. However, the reverse cancellation signal is not accurately determined, that is, the error between the reverse cancellation signal and the actual noise signal is large, and the noise reduction process cannot be effectively implemented. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a headphone noise reduction method and device, which are used to solve the technical problems in the prior art.

[0005] On the one hand, the present invention provides the following technical solution, a headphone noise reduction method, comprising: A variable control filter group is set inside the earphone and an earphone noise signal is obtained, and a discrete transformation process is performed on the variable control filter group to obtain time domain representations of a plurality of sub-filters; Calculating a weight of each of the sub-filters based on the headphone noise signal, and determining a new filter based on the weight of the sub-filter and the time domain representation; Determining filter coefficients of the new filter, and calculating a first filter output and a second filter output based on the filter coefficients; updating the filter coefficients of the new filter based on the first filter output and the second filter output to obtain updated filter coefficients; A noise cancellation signal is calculated based on the headphone noise signal and the update filter coefficient, and the update filter is controlled to output the noise cancellation signal to cancel the headphone noise signal.

[0006] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention first sets a variable control filter group inside the earphone and obtains the earphone noise signal, and performs discrete transformation processing on the variable control filter group to obtain time domain representations of several sub-filters; then calculates the weight of each sub-filter based on the earphone noise signal, and determines a new filter based on the weight and time domain representation of the sub-filter; then determines the filter coefficient of the new filter, and calculates the first filter output and the second filter output based on the filter coefficient; then updates the filter coefficient of the new filter based on the first filter output and the second filter output to obtain updated filter coefficients; finally, calculates the noise cancellation signal based on the earphone noise signal and the updated filter coefficient, and controls the updated filter to output the noise cancellation signal to eliminate the earphone noise signal. The present invention determines a new filter, which can effectively identify the earphone noise signal and generate a more accurate cancellation signal, thereby improving the effect of earphone noise reduction. At the same time, the present invention performs a corresponding updating process on the coefficient of the new filter, thereby reducing the error between the cancellation signal and the earphone noise signal, improving the accuracy of the cancellation signal and also improving the corresponding noise reduction effect.

[0007] Preferably, the step of performing discrete transformation processing on the variable control filter group to obtain a plurality of sub-filters, and calculating output signals of all the sub-filters based on the headphone noise signal comprises: The variable filter bank is subjected to discrete Fourier transform processing to obtain a plurality of sub-filters: ; In the formula, represents the discrete Fourier transform matrix, represents the spectrum of the variable filter bank, Indicates The spectrum of the sub-filters, represents the number of sub-filters; Calculate the The spectrum of the sub-filter : , ; ; ; ; ; In the formula, Respectively represent Sub-filter Stage Order spectrum, , The first interval and the second interval are respectively represents the variable filter bank Order spectrum, represents the order of the variable filter bank; Based on The spectrum of the sub-filter Determine Time domain representation of the sub-filters : .

[0008] Preferably, the step of calculating the weight of each sub-filter based on the headphone noise signal comprises: Calculate the output signals of all the sub-filters based on the headphone noise signal : ; ; ; ; In the formula, represents the secondary signal vector level, represents the set of combined weight vectors, Indicates The secondary signal vector of the sub-filters, Indicates The combined weight vector of sub-filters, represents the number of sub-filters, represents the headphone noise signal, Indicates Time domain representation of sub-filters; Based on the output signal Calculate the error function : ; In the formula, represents the minimum mean square error calculation, , represents the error desired signal, the pulse signal of the secondary path, Represents convolution calculation; For the error function Minimize and combine the weight vector set The combined weight vector in is updated to obtain the updated weight vector : ; In the formula, represents the update coefficient; Based on updating the weight vector Error function Perform update processing until the update conditions are met and output the optimal update weight vector , based on the optimal update weight vector The weight of each sub-filter : ; In the formula, Indicates the judgment threshold.

[0009] Preferably, in the step of determining a new filter based on the weights of the sub-filters and the time domain representation, the new filter for: ; In the formula, , Respectively represent The weights and time domain representation of the sub-filters, Indicates the number of sub-filters.

[0010] Preferably, the step of determining the filter coefficients of the new filter and calculating the first filter output and the second filter output based on the filter coefficients comprises: Calculate the filter coefficients of the new filter : ; In the formula, represents the steering vector of the earphone, is the conjugate transpose symbol, represents the identity matrix, Represents the angle from the headphone noise signal to the microphone array; Calculate a first filter output based on the filter coefficients : ; In the formula, represents the headphone noise signal; Calculate a second filtered output based on the filter coefficients : .

[0011] Preferably, in the step of updating the filter coefficients of the new filter based on the first filter output and the second filter output to obtain updated filter coefficients, the updated filter coefficients for: ; In the formula, represents the filter coefficients, , Respectively represent the update factor and the allocation weight, , Respectively represent the first filter output and the second filter output, is the conjugate transpose symbol.

[0012] Preferably, in the step of calculating the noise cancellation signal based on the headphone noise signal and the updated filter coefficient, the noise cancellation signal for: ; In the formula, , represents the error desired signal, the pulse signal of the secondary path, represents the convolution calculation, represents the update filter coefficients, represents the headphone noise signal, Indicates a new filter.

[0013] In a second aspect, the present invention provides the following technical solution: a headphone noise reduction device, the device comprising: A transformation module, used to set a variable control filter group inside the earphone and obtain an earphone noise signal, and perform discrete transformation processing on the variable control filter group to obtain time domain representations of a plurality of sub-filters; A weight module, configured to calculate a weight of each of the sub-filters based on the headphone noise signal, and determine a new filter based on the weight of the sub-filter and the time domain representation; A coefficient module, configured to determine filter coefficients of the new filter and calculate a first filter output and a second filter output based on the filter coefficients; An updating module, configured to update the filter coefficients of the new filter based on the first filtering output and the second filtering output to obtain updated filter coefficients; The noise reduction module is used to calculate a noise cancellation signal based on the headphone noise signal and the update filter coefficient, and control the update filter to output the noise cancellation signal to cancel the headphone noise signal.

[0014] In a third aspect, the present invention provides the following technical solution: a computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the headphone noise reduction method as described above when executing the computer program.

[0015] In a fourth aspect, the present invention provides the following technical solution: a storage medium having a computer program stored thereon, wherein the computer program implements the headphone noise reduction method as described above when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A flowchart of a headphone noise reduction method provided in Embodiment 1 of the present invention; Figure 2 A structural block diagram of a headphone noise reduction device provided in Embodiment 2 of the present invention; Figure 3 A schematic diagram of the hardware structure of a computer provided in another embodiment of the present invention.

[0018] The embodiments of the present invention will be further described below with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the embodiments of the present invention, and should not be construed as limiting the present invention.

[0020] Embodiment 1 In the first embodiment of the present invention, Figure 1 As shown, a headphone noise reduction method includes: S1, setting a variable control filter group inside the earphone and obtaining an earphone noise signal, and performing discrete transformation processing on the variable control filter group to obtain time domain representations of a plurality of sub-filters; Specifically, a variable control filter group is set inside the earphone, which includes several filters and are initial filters. A new filter is generated through subsequent operation processing. The new filter can be generated according to different sizes and types of shapes, and can therefore be suitable for noise reduction processes of different noises.

[0021] Wherein, the step S1 comprises: S11, performing discrete Fourier transform processing on the variable filter bank to obtain a plurality of sub-filters: ; In the formula, represents the discrete Fourier transform matrix, represents the spectrum of the variable filter bank, Indicates The spectrum of the sub-filters, Indicates the number of sub-filters.

[0022] S12, calculate the The spectrum of the sub-filter : , ; ; ; ; ; In the formula, Respectively represent Sub-filter Stage Order spectrum, , The first interval and the second interval are respectively represents the variable filter bank Order spectrum, Indicates the order of the variable filter bank.

[0023] S13, based on The spectrum of the sub-filter Determine Time domain representation of the sub-filters : ; Specifically, represents the inverse discrete Fourier transform matrix.

[0024] S2. Calculating a weight of each of the sub-filters based on the headphone noise signal, and determining a new filter based on the weight of the sub-filter and the time domain representation; Wherein, the step S2 comprises: S21, calculating the output signals of all the sub-filters based on the headphone noise signal : ; ; ; ; In the formula, represents the secondary signal vector level, represents the set of combined weight vectors, Indicates The secondary signal vector of the sub-filters, Indicates The combined weight vector of sub-filters, represents the number of sub-filters, represents the headphone noise signal, Indicates The time domain representation of the sub-filters.

[0025] S22, based on the output signal Calculate the error function : ; In the formula, represents the minimum mean square error calculation, , represents the error desired signal, the pulse signal of the secondary path, Represents convolution calculation; Specifically, the error expected signal can be pre-specified according to the size of the headphone noise signal, and the smaller the value, the better.

[0026] S23, the error function Minimize and combine the weight vector set The combined weight vector in is updated to obtain the updated weight vector : ; In the formula, represents the update coefficient.

[0027] S24, based on updating weight vector Error function Perform update processing until the update conditions are met and output the optimal update weight vector , based on the optimal update weight vector The weight of each sub-filter : ; In the formula, Indicates the judgment threshold; Specifically, in this embodiment, the judgment threshold is 0.5.

[0028] Among them, the new filter for: ; In the formula, , Respectively represent The weights and time domain representation of the sub-filters, Indicates the number of sub-filters.

[0029] S3, determining filter coefficients of the new filter, and calculating a first filter output and a second filter output based on the filter coefficients; Wherein, step S3 comprises: S31, calculating the filter coefficients of the new filter : ; In the formula, represents the steering vector of the earphone, is the conjugate transpose symbol, represents the identity matrix, Represents the angle from the headphone noise signal to the microphone array.

[0030] S32, calculating the first filter output based on the filter coefficient : ; In the formula, Indicates the headphone noise signal.

[0031] S33, calculating the second filter output based on the filter coefficient : ; Specifically, the first filter output is specifically the output of the fixed beamformer, the second filter output is specifically the output of the ABM module, and the second filter output basically only contains noise.

[0032] S4, updating the filter coefficients of the new filter based on the first filter output and the second filter output to obtain updated filter coefficients; Among them, update the filter coefficients for: ; In the formula, represents the filter coefficients, , They represent the update factor and the allocation weight respectively. , Respectively represent the first filter output and the second filter output, is the conjugate transpose symbol.

[0033] S5. Calculate a noise cancellation signal based on the headphone noise signal and the update filter coefficient, and control the update filter to output the noise cancellation signal to cancel the headphone noise signal.

[0034] The noise elimination signal for: ; In the formula, , represents the error desired signal, the pulse signal of the secondary path, represents the convolution calculation, represents the update filter coefficients, represents the headphone noise signal, represents a new filter; Specifically, after the noise cancellation signal is obtained by calculation, the filter can be controlled to output the noise cancellation signal in reverse, thereby canceling out the noise signal of the headphone, thereby realizing the headphone noise reduction process.

[0035] The headphone noise reduction method provided in the first embodiment of the present invention first sets a variable control filter group inside the headphone and obtains the headphone noise signal, and performs discrete transformation processing on the variable control filter group to obtain time domain representations of several sub-filters; then calculates the weight of each sub-filter based on the headphone noise signal, and determines a new filter based on the weight and time domain representation of the sub-filter; then determines the filter coefficient of the new filter, and calculates the first filter output and the second filter output based on the filter coefficient; then updates the filter coefficient of the new filter based on the first filter output and the second filter output to obtain updated filter coefficients; finally, calculates the noise cancellation signal based on the headphone noise signal and the updated filter coefficient, and controls the updated filter to output the noise cancellation signal to eliminate the headphone noise signal. The present invention determines a new filter, which can effectively identify the headphone noise signal and generate a relatively accurate cancellation signal, thereby improving the effect of the headphone noise reduction. At the same time, the present invention performs a corresponding updating process on the coefficient of the new filter, thereby reducing the error between the cancellation signal and the headphone noise signal, improving the accuracy of the cancellation signal and also improving the corresponding noise reduction effect.

[0036] Embodiment 2 like Figure 2 As shown, in the second embodiment of the present invention, a headphone noise reduction device is provided, and the device includes: Transformation module 1, used for setting a variable control filter group inside the earphone and obtaining an earphone noise signal, and performing discrete transformation processing on the variable control filter group to obtain time domain representations of a plurality of sub-filters; A weight module 2, configured to calculate a weight of each of the sub-filters based on the headphone noise signal, and determine a new filter based on the weight of the sub-filters and the time domain representation; A coefficient module 3, used for determining filter coefficients of the new filter, and calculating a first filter output and a second filter output based on the filter coefficients; An updating module 4, configured to update the filter coefficients of the new filter based on the first filtering output and the second filtering output to obtain updated filter coefficients; The noise reduction module 5 is used to calculate a noise cancellation signal based on the headphone noise signal and the update filter coefficient, and control the update filter to output the noise cancellation signal to cancel the headphone noise signal.

[0037] Wherein, the transformation module 1 comprises: The transform submodule is used to perform discrete Fourier transform processing on the variable filter bank to obtain a plurality of sub-filters: ; In the formula, represents the discrete Fourier transform matrix, represents the spectrum of the variable filter bank, Indicates The spectrum of the sub-filters, represents the number of sub-filters; The spectrum submodule is used to calculate the The spectrum of the sub-filter : , ; ; ; ; ; In the formula, Respectively represent Sub-filter Stage Order spectrum, , The first interval and the second interval are respectively represents the variable filter bank Order spectrum, represents the order of the variable filter bank; The time domain submodule is used to The spectrum of the sub-filter Determine Time domain representation of the sub-filters : .

[0038] The weight module 2 comprises: A signal calculation submodule, used to calculate the output signals of all the sub-filters based on the headphone noise signal : ; ; ; ; In the formula, represents the secondary signal vector level, represents the set of combined weight vectors, Indicates The secondary signal vector of the sub-filters, Indicates The combined weight vector of sub-filters, represents the number of sub-filters, represents the headphone noise signal, Indicates Time domain representation of sub-filters; A function submodule is used to generate a signal based on the output signal Calculate the error function : ; In the formula, represents the minimum mean square error calculation, , represents the error desired signal, the pulse signal of the secondary path, Represents convolution calculation; Update submodule, used to update the error function Minimize and combine the weight vector set The combined weight vector in is updated to obtain the updated weight vector : ; In the formula, represents the update coefficient; The weight submodule is used to update the weight vector based on Error function Perform update processing until the update conditions are met and output the optimal update weight vector , based on the optimal update weight vector The weight of each sub-filter : ; In the formula, Indicates the judgment threshold.

[0039] The coefficient module 3 comprises: A coefficient submodule for calculating the filter coefficients of the new filter : ; In the formula, represents the steering vector of the earphone, is the conjugate transpose symbol, represents the identity matrix, Represents the angle from the headphone noise signal to the microphone array; A first output submodule is used to calculate a first filtered output based on the filter coefficients : ; In the formula, represents the headphone noise signal; A second output submodule is used to calculate a second filtered output based on the filter coefficients : .

[0040] In some other embodiments of the present invention, the embodiments of the present invention provide the following technical solutions: a computer, comprising a memory 102, a processor 101, and a computer program stored in the memory 102 and executable on the processor 101; the processor 101 implements the headphone noise reduction method as described above when executing the computer program.

[0041] Specifically, the processor 101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.

[0042] Among them, the memory 102 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 102 may include a hard disk drive (HDD), a floppy disk drive, a solid state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 102 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 102 may be inside or outside the data processing device. In a specific embodiment, the memory 102 is a non-volatile memory. In a specific embodiment, the memory 102 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically alterable ROM (EAROM) or a flash memory (FLASH), or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0043] The memory 102 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 101 .

[0044] The processor 101 implements the above-mentioned headphone noise reduction method by reading and executing the computer program instructions stored in the memory 102 .

[0045] In some embodiments, the computer may further include a communication interface 103 and a bus 100. Figure 3 As shown, the processor 101, the memory 102, and the communication interface 103 are connected via a bus 100 and communicate with each other.

[0046] The communication interface 103 is used to implement communication between the modules, devices, units and / or equipment in the embodiment of the present invention. The communication interface 103 can also implement data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage, and image / data processing workstations.

[0047] The bus 100 includes hardware, software or both, and couples the components of the computer device to each other. The bus 100 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 100 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, bus 100 may include one or more buses. Although embodiments of the present invention describe and illustrate a particular bus, the present invention contemplates any suitable bus or interconnect.

[0048] The computer can execute the headphone noise reduction method of the present invention based on acquiring the headphone noise reduction device, thereby realizing the headphone noise reduction method.

[0049] In some further embodiments of the present invention, in combination with the above-mentioned headphone noise reduction method, the embodiments of the present invention provide the following technical solutions: a storage medium having a computer program stored thereon, and the computer program implements the above-mentioned headphone noise reduction method when executed by a processor.

[0050] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0051] More specific examples of readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0052] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0053] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0054] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for reducing noise in headphones, characterized in that: include: A variable control filter group is set inside the earphone and an earphone noise signal is obtained, and a discrete transformation process is performed on the variable control filter group to obtain time domain representations of a plurality of sub-filters; Calculating a weight of each of the sub-filters based on the headphone noise signal, and determining a new filter based on the weight of the sub-filter and the time domain representation; Determining filter coefficients of the new filter, and calculating a first filter output and a second filter output based on the filter coefficients; updating the filter coefficients of the new filter based on the first filter output and the second filter output to obtain updated filter coefficients; A noise cancellation signal is calculated based on the headphone noise signal and the update filter coefficient, and the update filter is controlled to output the noise cancellation signal to cancel the headphone noise signal.

2. The headphone noise reduction method according to claim 1, characterized in that: The step of performing discrete transformation processing on the variable control filter group to obtain a plurality of sub-filters, and calculating output signals of all the sub-filters based on the headphone noise signal comprises: The variable filter bank is subjected to discrete Fourier transform processing to obtain a plurality of sub-filters: ； In the formula, represents the discrete Fourier transform matrix, represents the spectrum of the variable filter bank, Indicates The spectrum of the sub-filters, represents the number of sub-filters; Calculate the The spectrum of the sub-filter : ， ； ； ； ； ； In the formula, Respectively represent Sub-filter Stage Order spectrum, , The first interval and the second interval are respectively represents the variable filter bank Order spectrum, represents the order of the variable filter bank; Based on The spectrum of the sub-filter Determine The time domain representation of the sub-filters : 。 3. The headphone noise reduction method according to claim 1, characterized in that: The step of calculating the weight of each sub-filter based on the headphone noise signal comprises: Calculate the output signals of all the sub-filters based on the headphone noise signal : ； ； ； ； In the formula, represents the secondary signal vector level, represents the set of combined weight vectors, Indicates The secondary signal vector of the sub-filters, Indicates The combined weight vector of sub-filters, represents the number of sub-filters, represents the headphone noise signal, Indicates Time domain representation of sub-filters; Based on the output signal Calculate the error function : ； In the formula, represents the minimum mean square error calculation, , represents the error desired signal, the pulse signal of the secondary path, Represents convolution calculation; For the error function Minimize and combine the weight vector set The combined weight vector in is updated to obtain the updated weight vector : ； In the formula, represents the update coefficient; Based on updating the weight vector Error function Perform update processing until the update conditions are met and output the optimal update weight vector , based on the optimal update weight vector The weight of each sub-filter : ； In the formula, Indicates the judgment threshold.

4. The headphone noise reduction method according to claim 1, characterized in that: In the step of determining a new filter based on the weights of the sub-filters and the time domain representation, the new filter for: ； In the formula, , Respectively represent The weights and time domain representation of the sub-filters, Indicates the number of sub-filters.

5. The headphone noise reduction method according to claim 1, characterized in that: The step of determining the filter coefficients of the new filter and calculating the first filter output and the second filter output based on the filter coefficients comprises: Calculate the filter coefficients of the new filter : ； In the formula, represents the steering vector of the earphone, is the conjugate transpose symbol, represents the identity matrix, Represents the angle from the headphone noise signal to the microphone array; Calculate a first filter output based on the filter coefficients : ； In the formula, represents the headphone noise signal; Calculate a second filtered output based on the filter coefficients : 。 6. The headphone noise reduction method according to claim 1, characterized in that: In the step of updating the filter coefficients of the new filter based on the first filter output and the second filter output to obtain updated filter coefficients, the updated filter coefficients for: ； In the formula, represents the filter coefficients, , They represent the update factor and the allocation weight respectively. , Respectively represent the first filter output and the second filter output, is the conjugate transpose symbol.

7. The headphone noise reduction method according to claim 1, characterized in that: In the step of calculating the noise cancellation signal based on the headphone noise signal and the updated filter coefficient, the noise cancellation signal for: ； In the formula, , represents the error desired signal, the pulse signal of the secondary path, represents the convolution calculation, represents the update filter coefficients, represents the headphone noise signal, Indicates a new filter.

8. An earphone noise reduction device, characterized in that: The system comprises: A transformation module, used to set a variable control filter group inside the earphone and obtain an earphone noise signal, and perform discrete transformation processing on the variable control filter group to obtain time domain representations of a plurality of sub-filters; A weight module, configured to calculate a weight of each of the sub-filters based on the headphone noise signal, and determine a new filter based on the weight of the sub-filter and the time domain representation; A coefficient module, configured to determine filter coefficients of the new filter and calculate a first filter output and a second filter output based on the filter coefficients; An updating module, configured to update the filter coefficients of the new filter based on the first filtering output and the second filtering output to obtain updated filter coefficients; The noise reduction module is used to calculate a noise cancellation signal based on the headphone noise signal and the update filter coefficient, and control the update filter to output the noise cancellation signal to cancel the headphone noise signal.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the headphone noise reduction method according to any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the headphone noise reduction method according to any one of claims 1 to 7 is implemented.

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