Active noise reduction method for OWS earphone, electronic equipment and readable storage medium

Abstract

The invention relates to an OWS earphone active noise reduction method, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a noise signal through a microphone; analyzing the noise signal, and when the volume of the noise signal is greater than a preset volume threshold value, generating a noise reduction sound wave opposite to the phase of the noise signal through an electroacoustic transducer to eliminate noise; analyzing the noise signal to determine an environmental scene; when the OWS earphone is in a commuting scene, determining the phase and frequency of a noise reduction sound wave according to a noise signal collected by the microphone; calculating a noise reduction evaluation index in the commuting scene, and adjusting the phase and frequency of a noise reduction sound wave according to the noise reduction evaluation index to maintain an optimal noise reduction effect; different noise reduction modes are set according to common application scenes of the earphone, feedback can be made according to noise reduction requirements of different application scenes, the use experience of a user is not affected while the noise reduction effect is generated, and meanwhile the optimal noise reduction effect is kept through the noise reduction evaluation index.

Description

Technical Field

[0001] The present invention relates to the field of active noise reduction technology for OWS headphones, and in particular to an active noise reduction method for OWS headphones, an electronic device and a readable storage medium. Background Art

[0002] OWS headphones stand for "Open Wearable Stereo", which means fully open wearable headphones, and it can be said to be an innovative form based on TWS headphones.

[0003] The biggest difference between it and TWS earphones is that they are "fully open" and "not in the ear". Due to the different design concepts, OWS earphones also use a novel air conduction method, which uses the outer eardrum, eardrum, tympanic cavity and other air conduction transmission media to directly transmit the sound wave vibration signal converted from the electrical signal to the auditory nerve through the temporal bone.

[0004] However, most OWS earphones have poor noise reduction due to their open design, which may not provide an immersive listening experience like traditional TWS earphones in noisy environments.

[0005] Moreover, the noise characteristics are different in different environments. If the noise reduction mode of the headphones is single and cannot be adjusted according to environmental changes, it will further affect the audio effect of the headphones.

[0006] For example, when the usage scenario is in an office, the noise characteristics are mainly white noise and low-level conversations. In an office environment, users may need a certain degree of noise reduction to concentrate, but they also need to hear colleagues' conversations or phone ringing. Therefore, it is necessary to design a mild noise reduction mode to focus on suppressing low-frequency noise, such as air conditioning. Therefore, for the usage scenario in the office, a transparent mode is set to allow users to quickly switch on the noise reduction state when needed to facilitate communication with others.

[0007] For example, the noise in commuting scenarios mainly comes from the engine sound of vehicles, wind noise during driving, and the noise of people. In this environment, users may need a stronger noise reduction effect to block interference. Therefore, it is necessary to design a medium to high noise reduction mode that covers a wide frequency range and effectively reduces the noise of vehicles.

[0008] For example, the noise in outdoor sports scenes mainly comes from wind, traffic, natural environment sounds, etc. Users may want to hear certain environmental sounds to ensure safety when exercising outdoors. Therefore, it is necessary to design a selective noise reduction mode that focuses on suppressing interfering noise, such as traffic sounds, while allowing safety-related sounds to pass.

[0009] In summary, in the patent application of the present invention, the applicant has carefully studied an OWS headset active noise reduction method to solve the above problems. Summary of the invention

[0010] In view of the deficiencies in the above-mentioned prior art, the present invention mainly aims to provide an OWS headset active noise reduction method, an electronic device and a readable storage medium, which can provide feedback according to the noise reduction requirements of different application scenarios, so that it can produce a noise reduction effect without affecting the user's experience. Moreover, coupling the feedforward microphone and the feedback microphone with the electroacoustic transducer can speed up the noise reduction reaction, and then make accurate responses to different noise scenarios.

[0011] To achieve the above-mentioned purpose, the present invention adopts the following technical scheme: An OWS headset active noise reduction method comprises the following steps: Acquire noise signal through microphone; The noise signal is analyzed, and when the volume of the noise signal is greater than a preset volume threshold, a noise reduction wave having a phase opposite to that of the noise signal is generated by an electroacoustic transducer to eliminate the noise; Analyze the noise signal to determine the environment scene where the OWS headset is located; the environment scene includes an office scene, a commuting scene, and an outdoor sports scene; When the OWS headset is in an office scene, the electroacoustic transducer is kept generating a noise reduction wave with a phase opposite to that of the noise signal to eliminate the noise; When the OWS headset is in a commuting scenario, the phase and frequency of the noise reduction wave used to offset the noise are determined according to the noise signal collected by the microphone; the noise reduction evaluation index in the commuting scenario is calculated, and the phase and frequency of the noise reduction wave are adjusted according to the noise reduction evaluation index to maintain the best noise reduction effect; When the OWS headset is in an outdoor sports scene, the noise signal is classified to obtain a target signal and a signal to be processed, the target signal is transmitted to the human ear through a microphone, and noise reduction processing is performed on the signal to be processed at the same time.

[0012] As a preferred solution, analyzing the noise signal to determine the environmental scene in which the OWS headset is located includes: First, by analyzing the frequency and loudness of the noise signal collected by the microphone, and then analyzing the user's behavior pattern through the built-in sensor of the OWS headset, and then combining the user's behavior pattern with the characteristics of the sound signal collected by the feedforward microphone, the current environmental scene of the OWS headset can be determined.

[0013] As a preferred solution, the noise reduction evaluation index is T, and its calculation formula is as follows: ; Among them, SNR 1 and SNR2 Respectively represent the signal-to-noise ratio (SNR) of the left and right OWS headphones in commuting scenarios. 0 is the signal-to-noise ratio evaluation index for the set standard commuting scenario, is the probability of normal noise reduction of the set headphones, x is the number of headphones with normal noise reduction, which can be 1 or 2. Indicates the set noise reduction effect evaluation index. The proportion of normal noise-cancelling headphones corresponds to the weight of the comprehensive noise-cancelling effect evaluation.

[0014] As a preferred solution, the SNR 1 or the SNR 2 The calculation steps include: A noisy signal is obtained through a microphone, and the calculation formula of the noisy signal is y(t)= s(t)+ n(t), where y(t) is the noisy signal, s(t) is the useful signal, and n(t) is the noise signal; Perform frequency domain analysis on the noisy signal, that is, perform Fourier transform on the noisy signal y(t) to obtain Y(f); The spectrum of the useful signal and the noise signal is obtained according to the result Y(f) in the frequency domain. The calculation formula is as follows: Y(f)=S(f)+ N(f), where S(f) is the spectrum of the useful signal and N(f) is the spectrum of the noise. The useful signal power Ps is obtained by integrating the square of the amplitude of the spectrum S(f) of the useful signal over the entire frequency range. The calculation formula is as follows: ; And the noise power Pn is obtained by integrating the square of the amplitude of the noise spectrum N(f) over the entire frequency range. The calculation formula is as follows: ; The corresponding signal-to-noise ratio is calculated according to the following formula: .

[0015] As a preferred solution, determining the phase and frequency of the noise reduction wave for canceling the noise according to the noise signal collected by the microphone includes: Perform spectrum analysis on the noise signal collected by the microphone to determine the main frequency components of the noise signal; The frequency of the noise reduction wave used to cancel the noise signal is determined according to the main frequency component, and the phase of the noise reduction wave is determined according to the shape and peak position of the autocorrelation function.

[0016] As a preferred solution, adjusting the phase and frequency of the noise reduction wave according to the noise reduction evaluation index includes: Gradually adjust the phase of the noise reduction wave in a certain direction, and observe the change of the noise reduction evaluation index in real time during the adjustment of the noise reduction wave; If the noise reduction evaluation index gradually increases, continue to adjust the phase of the noise reduction wave in the same direction until the noise reduction evaluation index is adjusted to the maximum value; if the noise reduction evaluation index gradually decreases, adjust the phase of the noise reduction wave in the opposite direction until the noise reduction evaluation index is adjusted to the maximum value.

[0017] As a preferred solution, the microphone includes a first external microphone, a second external microphone and an internal microphone, the first external microphone and the second external microphone are both feedforward microphones, and the internal microphone is a feedback microphone.

[0018] As a preferred solution, the first external microphone and the second external microphone are coupled to the rear frame of the electroacoustic transducer so that the electroacoustic transducer can capture external noise in real time and generate reverse sound waves to cancel the noise in time; The internal microphone is coupled to the front frame of the electroacoustic transducer to monitor the sound inside the earphone through the electroacoustic transducer and activate the active noise reduction function when the sound inside the earphone meets the preset noise reduction scenario.

[0019] A computer-readable storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the steps of the above-mentioned OWS headset active noise reduction method.

[0020] An electronic device comprises a memory, a processor and program instructions stored in the memory and executable on the processor, wherein the program instructions implement the above-mentioned OWS headset active noise reduction method when executed by the processor.

[0021] Compared with the prior art, the present invention has obvious advantages and beneficial effects. Specifically, it mainly sets different noise reduction modes according to the common application scenarios of OWS headphones, and can provide feedback for the noise reduction requirements of different application scenarios, so that the noise reduction effect is produced without affecting the user's experience. Moreover, the feedforward microphone and the feedback microphone are coupled with the electroacoustic transducer, which can speed up the noise reduction reaction, and then accurately respond to different noise scenarios. Secondly, through the noise reduction evaluation index T, the noise reduction effect of the OWS headphones in the current noise environment can be evaluated in real time, that is, whether the current noise reduction signal is optimal. If not, the phase and frequency of the noise reduction wave will continue to be adjusted to ensure that the noise reduction wave maintains the best noise reduction effect.

[0022] In order to more clearly illustrate the structural features and effects of the present invention, it is described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0025] like Figure 1 As shown, an OWS headset active noise reduction method includes the following steps: Acquire noise signal through microphone; The noise signal is analyzed, and when the volume of the noise signal is greater than a preset volume threshold, a noise reduction wave having a phase opposite to that of the noise signal is generated by an electroacoustic transducer to eliminate the noise; Analyze the noise signal to determine the environment scene where the OWS headset is located; the environment scene includes an office scene, a commuting scene, and an outdoor sports scene; When the OWS headset is in an office scene, the electroacoustic transducer is kept generating a noise reduction wave with a phase opposite to that of the noise signal to eliminate the noise; When the OWS headset is in a commuting scenario, the phase and frequency of the noise reduction wave used to offset the noise are determined according to the noise signal collected by the microphone; the noise reduction evaluation index in the commuting scenario is calculated, and the phase and frequency of the noise reduction wave are adjusted according to the noise reduction evaluation index to maintain the best noise reduction effect; When the OWS headset is in an outdoor sports scene, the noise signal is classified to obtain a target signal and a signal to be processed, the target signal is transmitted to the human ear through a microphone, and noise reduction processing is performed on the signal to be processed at the same time.

[0026] Specifically, the microphone includes a first external microphone, a second external microphone and an internal microphone, the first external microphone and the second external microphone are both feedforward microphones, and the internal microphone is a feedback microphone; wherein the first external microphone is used to obtain the noise signal in front of the earphone, the second external microphone is used to obtain the noise signal behind the earphone, and the internal microphone is arranged to monitor the sound passing therethrough and the sound played through the speaker; at the same time, the two feedforward microphones are coupled to the rear frame of the electroacoustic transducer so that the electroacoustic transducer can capture the external noise in real time and generate a reverse noise reduction wave in time to cancel the noise; and the feedback microphone is coupled to the front frame of the electroacoustic transducer to monitor the sound inside the earphone through the electroacoustic transducer and activate the active noise reduction function when the sound inside the earphone meets the preset noise reduction scenario.

[0027] When the active noise reduction method is executed, a noise signal is first obtained through a microphone; then the noise signal is analyzed, and when the volume of the noise signal is greater than a preset volume threshold, a noise reduction wave with a phase opposite to that of the noise signal is generated through an electroacoustic transducer to eliminate the noise; The noise signal is then analyzed to determine the environmental scene in which the OWS headset is located. In this embodiment, the environmental scenes include office scenes, commuting scenes, and outdoor sports scenes. Specifically, the following steps can be used to determine the environmental scene: first, the frequency and loudness of the noise signal collected by the microphone are analyzed, and the user's behavior pattern is analyzed through the built-in sensor of the OWS headset. Then, the user's behavior pattern is combined with the characteristics of the sound signal collected by the feedforward microphone to determine the current environmental scene in which the OWS headset is located.

[0028] Next, we will briefly explain the office scene, commuting scene, and outdoor sports scene: 1. Typical noises in office scenes include: Keyboard tapping sound: the crisp sound of keystrokes, with a certain rhythm and frequency.

[0029] Mouse clicking sound: A relatively mild clicking sound, and there may be continuous operation sounds.

[0030] Operation sounds of equipment such as printers and copiers: Regular mechanical operation sounds, which may be accompanied by the sound of paper transmission.

[0031] Conversation: Usually low and slow, mainly discussing work content, with short intervals of silence and communication.

[0032] Keyboard tapping and mouse clicking sounds are usually within a specific frequency range and can be identified through spectrum analysis. For example, keyboard tapping sounds may have obvious energy distribution in the mid- and high-frequency bands. The operating sounds of equipment such as printers usually have a fixed rhythm and pattern, which can be judged through pattern recognition algorithms. By detecting work-related words or specific office terms, it can assist in judging it as an office scene.

[0033] 2. Typical noises in commuting scenarios include: Noise from vehicles: such as the sound of car engines, the sound of buses, the friction sound of subway tracks, etc. These sounds usually have a loud volume and specific frequency characteristics.

[0034] Crowd noise: On public transportation or in stations, there will be sounds of people talking and walking around, which is quite messy.

[0035] Broadcast notification sound: There will be broadcast announcements of train numbers, flights and other information at stations, airports and other places.

[0036] There are three ways to judge the commuting scene: a. Extract the specific frequency components and time domain characteristics of traffic noise, such as the low-frequency roar of car alarms and the high-frequency vibration of subway track friction.

[0037] b. Sound classification: Use machine learning algorithms to classify different types of transportation noise to determine the commuting scenario.

[0038] c. Voice recognition broadcast content: If specific words in the broadcast can be recognized, such as "station", "train number", "flight", etc., it can be determined as a commuting scene.

[0039] 3. Noise in outdoor sports scenes includes: The friction sound between sports shoes and the ground: a regular friction sound that changes with the rhythm of movement.

[0040] Breathing sound: When exercising, a person's breathing will become rapid and the breathing sound will be more obvious, especially during strenuous exercise.

[0041] Sounds such as conversation, wind or insects: have different pitches, loudness and timbre.

[0042] When the noise reduction scenario currently required to be used in the OWS headset is an office noise reduction scenario, the electroacoustic transducer is maintained to generate a noise reduction wave with a phase opposite to that of the noise signal to eliminate the noise.

[0043] When the OWS headset is in a commuting scenario, the phase and frequency of the noise reduction wave used to offset the noise are determined according to the noise signal collected by the microphone; the noise reduction evaluation index in the commuting scenario is calculated, and the phase and frequency of the noise reduction wave are adjusted according to the noise reduction evaluation index to maintain the best noise reduction effect.

[0044] In this embodiment, the formula for calculating the noise reduction evaluation index T is: ; Among them, SNR 1 and SNR 2 Respectively represent the signal-to-noise ratio (SNR) of the left and right OWS headphones in commuting scenarios. 0 is the signal-to-noise ratio evaluation index for the set standard commuting scenario, is the probability of the set earphones to achieve normal noise reduction (which can be obtained through testing before leaving the factory), x is the number of earphones with normal noise reduction, which can be 1 or 2. Indicates the set noise reduction effect evaluation index. The proportion of normal noise-cancelling headphones corresponds to the weight of the comprehensive noise-cancelling effect evaluation (which can be obtained through testing before leaving the factory).

[0045] It should be noted that when the OWS headphones are reducing noise, they generally first analyze the noise characteristics of the current environment to obtain its phase and frequency, and then generate opposite noise reduction waves to offset the noise. However, the noise signal will change, which may easily lead to the generated noise reduction waves (noise reduction signals) not being able to perform noise reduction well. Therefore, in this embodiment, a noise reduction evaluation index T is introduced. The noise reduction evaluation index T is used to evaluate the noise reduction effect of the OWS headphones in the current noise environment in real time, that is, to evaluate whether the current noise reduction wave is optimal. If not, the phase and frequency of the noise reduction wave are continuously adjusted to ensure that the noise reduction signal maintains the best noise reduction effect. Among them, the larger the noise reduction evaluation index T, the better the noise reduction effect.

[0046] In this embodiment, the definition of signal-to-noise ratio (SNR) refers to the ratio of signal power to noise power in an electronic device or electronic system. To obtain the signal-to-noise ratio based on phase and frequency, it is necessary to first separate the useful signal and noise components from the noisy signal, and then calculate their power.

[0047] Specifically, in this embodiment, the signal-to-noise ratio SNR in the commuting scenario is obtained. 1 Or signal-to-noise ratio SNR 2 , including the following steps: The noisy signal is picked up by the feedforward microphone. The noisy signal includes the useful signal and the noise signal. Assuming a useful signal , where A is the amplitude, is the angular frequency, is the phase, and the noise is n(t). Then, the noisy signal is y(t) = s(t) + n(t).

[0048] Perform frequency domain analysis on the noisy signal, that is, perform Fourier transform on the noisy signal y(t) to obtain Y(f); The spectrum of the useful signal and the noise signal is obtained according to the result Y(f) in the frequency domain. The calculation formula is as follows: Y(f)=S(f)+ N(f), where S(f) is the spectrum of the useful signal and N(f) is the spectrum of the noise. The useful signal power Ps is obtained by integrating the square of the amplitude of the spectrum S(f) of the useful signal over the entire frequency range. The calculation formula is as follows: At the same time, the noise power Pn is obtained by integrating the square of the amplitude of the noise spectrum N(f) over the entire frequency range. The calculation formula is as follows: ; Finally, the corresponding signal-to-noise ratio is calculated according to the following formula: ; Substituting the sound signals collected by the left and right OWS headphones into the above signal-to-noise ratio formula, the signal-to-noise ratio of the left and right headphones in the commuting scenario can be obtained. .

[0049] In this embodiment, the phase and frequency of the noise reduction wave are adjusted according to the noise reduction evaluation index, including: gradually adjusting the phase of the noise reduction wave in a certain direction, and observing the changes of the noise reduction evaluation index during the noise reduction wave adjustment process in real time; if the noise reduction evaluation index gradually increases, continue to adjust the phase of the noise reduction wave in the same direction until the noise reduction evaluation index is adjusted to the maximum value; if the noise reduction evaluation index gradually decreases, adjust the phase of the noise reduction wave in the opposite direction until the noise reduction evaluation index is adjusted to the maximum value.

[0050] Specifically, the noise reduction evaluation index can evaluate whether the noise reduction effect of the current headset has reached the best. In this embodiment, the specific judgment method is as follows: when reducing noise, the phase of the noise reduction signal can be gradually adjusted, such as gradually changing the phase of the noise reduction wave in a certain direction with a preset step length (distance), and observing the changes in the noise reduction evaluation index during the adjustment of the noise reduction wave in real time. If the value of the noise reduction evaluation index becomes larger, it means that the noise reduction effect has improved, then the phase can continue to be adjusted in the same direction (at least one step length) until the maximum noise reduction evaluation index is obtained, which is the best effect; if the noise reduction evaluation index becomes smaller during the adjustment of the noise reduction wave, it means that the noise reduction effect is reduced, and the phase needs to be adjusted in the opposite direction.

[0051] In this embodiment, by introducing the noise reduction evaluation index T, the noise characteristics and the performance of the noise reduction headphones in the actual usage environment are taken into consideration, and the opposite sound waves used to offset the noise are adjusted so that the noise reduction effect changes with the characteristics of the ambient noise, ensuring that the headphones maintain the best noise reduction effect as much as possible.

[0052] It should be noted that the method for determining the maximum noise reduction evaluation index is: during the index increase process, after reaching a peak, it will decrease. Then the peak value is the maximum noise reduction evaluation index, representing the best noise reduction effect. Therefore, by comparison, when the index has been in an upward state, at a certain moment, the index decreases and continues to decrease, then the previous peak should be the maximum noise reduction evaluation index.

[0053] In this embodiment, determining the phase and frequency of the noise reduction wave for canceling the noise according to the noise signal collected by the microphone includes: Perform spectrum analysis on the noise signal collected by the feedforward microphone to determine the main frequency components of the noise; Then the noise reduction wave frequency used to cancel the noise is determined according to the main frequency component, and then the noise reduction wave phase is determined according to the shape and peak position of the autocorrelation function.

[0054] When the OWS headset is in an outdoor sports scene, the noise signal is classified to obtain the target signal and the signal to be processed, the target signal is transmitted to the human ear through the microphone, and the signal to be processed is subjected to noise reduction processing at the same time. Specifically, the target signal is basically the useful signal mentioned above, and the signal to be processed is the noise signal mentioned above. Among them, the noise captured by the feedforward microphone is first classified, and the classification is based on the reference "Sound Environment Quality Standard" (GB3096-2008), which can be adjusted according to the specific scene, and then the unnecessary noise after classification is subjected to noise reduction processing (the noise reduction function is performed according to the mechanism of the existing general noise reduction headset), the required sound is retained, and it is transmitted to the human ear through the feedback microphone.

[0055] The key point of the design of the present invention is that it mainly sets different noise reduction modes according to the common application scenarios of OWS headphones, and can make feedback according to the noise reduction requirements of different application scenarios, so that it can produce noise reduction effects without affecting the user's experience. In addition, the feedforward microphone and the feedback microphone are coupled with the electroacoustic transducer, which can speed up the noise reduction reaction, and then accurately respond to different noise scenarios. Secondly, through the noise reduction evaluation index T, the noise reduction effect of the OWS headphones in the current noise environment can be evaluated in real time, that is, whether the current noise reduction signal is optimal. If not, the phase and frequency of the noise reduction wave will continue to be adjusted to ensure that the noise reduction wave maintains the best noise reduction effect.

[0056] The present application also provides a computer-readable storage medium storing a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the steps of the above-mentioned OWS headset active noise reduction method.

[0057] The present application also provides an electronic device, including a memory, a processor, and program instructions stored in the memory and executable on the processor, wherein the program instructions implement the above-mentioned OWS headset active noise reduction method when executed by the processor.

[0058] In one embodiment, the processor may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor is generally used to control the overall operation of the electronic device. In this embodiment, the processor is used to run the program code stored in the readable storage medium or process data.

[0059] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a readable storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0060] The above description is only a preferred embodiment of the present invention and does not limit the technical scope of the present invention. Therefore, any slight modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. An OWS headset active noise reduction method, characterized in that: The following steps are involved: Acquire noise signal through microphone; The noise signal is analyzed, and when the volume of the noise signal is greater than a preset volume threshold, a noise reduction wave having a phase opposite to that of the noise signal is generated by an electroacoustic transducer to eliminate the noise; Analyze the noise signal to determine the environment scene where the OWS headset is located; the environment scene includes an office scene, a commuting scene, and an outdoor sports scene; When the OWS headset is in an office scene, the electroacoustic transducer is kept generating a noise reduction wave with a phase opposite to that of the noise signal to eliminate the noise; When the OWS headset is in a commuting scenario, the phase and frequency of the noise reduction wave used to offset the noise are determined according to the noise signal collected by the microphone; the noise reduction evaluation index in the commuting scenario is calculated, and the phase and frequency of the noise reduction wave are adjusted according to the noise reduction evaluation index to maintain the best noise reduction effect; When the OWS headset is in an outdoor sports scene, the noise signal is classified to obtain a target signal and a signal to be processed, the target signal is transmitted to the human ear through a microphone, and noise reduction processing is performed on the signal to be processed at the same time.

2. The OWS headset active noise reduction method according to claim 1, characterized in that: The analyzing the noise signal to determine the environment scene where the OWS headset is located includes: First, by analyzing the frequency and loudness of the noise signal collected by the microphone, and then analyzing the user's behavior pattern through the built-in sensor of the OWS headset, and then combining the user's behavior pattern with the characteristics of the sound signal collected by the feedforward microphone, the current environmental scene of the OWS headset can be determined.

3. The OWS headset active noise reduction method according to claim 1, characterized in that: The noise reduction evaluation index is T, and its calculation formula is as follows: ； Among them, SNR1 and SNR2 represent the signal-to-noise ratio of the left and right OWS headphones in the commuting scene, respectively, and SNR0 is the signal-to-noise ratio evaluation index of the set standard commuting scene. is the probability of normal noise reduction of the set headphones, x is the number of headphones with normal noise reduction, which can be 1 or 2. Indicates the set noise reduction effect evaluation index. The proportion of normal noise-cancelling headphones corresponds to the weight of the comprehensive noise-cancelling effect evaluation.

4. The OWS headset active noise reduction method according to claim 3, characterized in that: The step of calculating the SNR1 or the SNR2 comprises: A noisy signal is obtained through a microphone, and the calculation formula of the noisy signal is y(t)= s(t)+ n(t), where y(t) is the noisy signal, s(t) is the useful signal, and n(t) is the noise signal; Perform frequency domain analysis on the noisy signal, that is, perform Fourier transform on the noisy signal y(t) to obtain Y(f); The spectrum of the useful signal and the noise signal is obtained according to the result Y(f) in the frequency domain. The calculation formula is as follows: Y(f)=S(f)+N(f), where S(f) is the spectrum of the useful signal and N(f) is the spectrum of the noise. The useful signal power Ps is obtained by integrating the square of the amplitude of the spectrum S(f) of the useful signal over the entire frequency range. The calculation formula is as follows: ; And the noise power Pn is obtained by integrating the square of the amplitude of the noise spectrum N(f) over the entire frequency range. The calculation formula is as follows: ; The corresponding signal-to-noise ratio is calculated according to the following formula: 。 5. The OWS headset active noise reduction method according to claim 1, characterized in that: The determining of the phase and frequency of the noise reduction wave for canceling the noise according to the noise signal collected by the microphone comprises: Perform spectrum analysis on the noise signal collected by the microphone to determine the main frequency components of the noise signal; The frequency of the noise reduction wave used to cancel the noise signal is determined according to the main frequency component, and the phase of the noise reduction wave is determined according to the shape and peak position of the autocorrelation function.

6. The OWS headset active noise reduction method according to claim 1, characterized in that: The adjusting the phase and frequency of the noise reduction wave according to the noise reduction evaluation index comprises: Gradually adjust the phase of the noise reduction wave in a certain direction, and observe the change of the noise reduction evaluation index in real time during the adjustment of the noise reduction wave; If the noise reduction evaluation index gradually increases, continue to adjust the phase of the noise reduction wave in the same direction until the noise reduction evaluation index is adjusted to the maximum value; if the noise reduction evaluation index gradually decreases, adjust the phase of the noise reduction wave in the opposite direction until the noise reduction evaluation index is adjusted to the maximum value.

7. The OWS headset active noise reduction method according to claim 1, characterized in that: The microphone includes a first external microphone, a second external microphone and an internal microphone. The first external microphone and the second external microphone are both feedforward microphones, and the internal microphone is a feedback microphone.

8. The OWS headset active noise reduction method according to claim 7, characterized in that: The first external microphone and the second external microphone are coupled to the rear frame of the electroacoustic transducer so that the electroacoustic transducer can capture external noise in real time and generate reverse sound waves in time to cancel the noise; The internal microphone is coupled to the front frame of the electroacoustic transducer to monitor the sound inside the earphone through the electroacoustic transducer and activate the active noise reduction function when the sound inside the earphone meets the preset noise reduction scenario.

9. A computer-readable storage medium, characterized in that: A plurality of instructions are stored, and the instructions are suitable for being loaded by a processor and executing the steps of the OWS headset active noise reduction method according to any one of claims 1 to 8.

10. An electronic device, characterized in that: The invention comprises a memory, a processor and program instructions stored in the memory and executable on the processor, wherein the program instructions are executed by the processor to implement the OWS headset active noise reduction method as claimed in any one of claims 1 to 8.

Images