Headset noise reduction method and apparatus, headset, and computer-readable storage medium

Abstract

The application discloses a helmet noise reduction method and device, a helmet and a computer readable storage medium. The helmet noise reduction method is applied to a helmet. At least two first microphones are arranged on the outer side of a helmet body. The helmet noise reduction method comprises the following steps: collecting a voice signal through a talk microphone of the helmet, and collecting first environmental noise signals through the first microphones; obtaining a noise reduction reference value, and performing noise suppression processing on the first environmental noise signals respectively, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value; and mixing the processed noise signals and the voice signal and then outputting the mixed signal to a talk opposite end. The helmet noise reduction effect is improved.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to a helmet noise reduction method, device, helmet, and computer-readable storage medium. Background Technology

[0002] In recent years, smart devices have swept the globe. Smart helmets, as an emerging device, not only bring a sense of technology to users but also provide convenience for their daily lives. For example, users can wear smart helmets to listen to music, watch videos, exercise, and engage in other daily activities, no longer limited by the traditional method of using a handheld device or headphones. However, in various complex noise environments, such as airports, subways, tunnels, or cycling on windy roads, when using a cycling helmet to make a call, both the ambient noise and the user's voice need to be output to the other party. This can lead to problems where wind noise from various directions makes it difficult for the other party to hear the user clearly. Improving the helmet's noise reduction effect during calls, enhancing call clarity, and improving the overall user experience are urgent issues that need to be addressed. Summary of the Invention

[0003] The main objective of this invention is to provide a helmet noise reduction method, device, helmet, and computer-readable storage medium, aiming to propose a helmet noise reduction solution to improve the noise reduction effect during helmet calls, enhance call clarity, and improve the subjective experience of calls.

[0004] To achieve the above objectives, the present invention provides a helmet noise reduction method, wherein the helmet noise reduction method is applied to a helmet, and at least two first microphones are disposed on the outer side of the helmet body, and the helmet noise reduction method includes:

[0005] Voice signals are collected through the helmet's microphone, and first ambient noise signals are collected through each of the first microphones.

[0006] Obtain a noise reduction reference value, and perform noise suppression processing on each of the first environmental noise signals respectively, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value;

[0007] The processed noise signals are mixed with the voice signals and then output to the other end of the call.

[0008] Optionally, the helmet body is further provided with at least one second microphone on the outer side of the helmet body. The second microphone is located in the forehead area, which is a region defined on the outer side of the helmet body according to the position of the user's forehead when wearing the helmet. The first microphone is located in the region on the outer side of the helmet body other than the forehead area.

[0009] The step of obtaining the noise reduction reference value includes:

[0010] The second ambient noise signal is acquired through the second microphone;

[0011] Calculate the second noise value of the second environmental noise signal, and subtract the first preset threshold from the second noise value to obtain the noise reduction reference value.

[0012] Optionally, the step of obtaining the noise reduction reference value further includes:

[0013] Detect whether the helmet's posture is a preset frontal riding posture;

[0014] If the helmet's posture is the preset frontal riding posture, then the step of subtracting the first preset threshold from the second noise value to obtain the noise reduction reference value is performed.

[0015] If the helmet's posture is not the preset frontal riding posture, then a second preset threshold is obtained as the noise reduction benchmark value.

[0016] Optionally, the step of performing noise suppression processing on each of the first environmental noise signals includes:

[0017] Calculate the first noise value for each of the first environmental noise signals;

[0018] If the first noise value is greater than the noise reduction reference value, then noise suppression processing is performed on the first environmental noise signal corresponding to the first noise value;

[0019] If the first noise value is less than or equal to the noise reduction reference value, then the first environmental noise signal corresponding to the first noise value is taken as the noise signal after noise suppression processing.

[0020] Optionally, the step of performing noise suppression processing on the first environmental noise signal corresponding to the first noise value if the first noise value is greater than the noise reduction reference value includes:

[0021] If the first noise value is greater than the noise reduction reference value, then the noise reduction reference value is divided by the first noise value to obtain the noise reduction ratio;

[0022] The noise signal after noise suppression is obtained by multiplying the first environmental noise signal corresponding to the first noise value by the noise reduction ratio.

[0023] Optionally, after the step of performing noise suppression processing on each of the first environmental noise signals, the method further includes:

[0024] Detect whether the helmet is in a call state;

[0025] If the helmet is in a call state, then the step of mixing the processed noise signals with the voice signal and outputting the mixture to the other end of the call is performed.

[0026] If the helmet is not in a call state, the processed noise signals are mixed and then output through the helmet's speaker.

[0027] Optionally, each of the first microphones is disposed in a respective directional region, and each directional region includes a left region, a right region, a left rear region, and a right rear region, which are divided on the outer side of the helmet according to the position of the user's left and right ears when wearing the helmet.

[0028] To achieve the above objectives, the present invention also provides a helmet noise reduction device, wherein the helmet noise reduction device is deployed on a helmet, and at least two first microphones are disposed on the outer side of the helmet body; the helmet noise reduction device includes:

[0029] A signal acquisition device is used to acquire voice signals through the helmet's microphone and to acquire first ambient noise signals through each of the first microphones.

[0030] The noise suppression module is used to obtain a noise reduction reference value and perform noise suppression processing on each of the first environmental noise signals respectively, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value.

[0031] The output module is used to mix the processed noise signals with the voice signals and output them to the other end of the call.

[0032] To achieve the above objectives, the present invention also provides a helmet, the helmet comprising: a memory, a processor, and a helmet noise reduction program stored in the memory and executable on the processor, wherein the helmet noise reduction program, when executed by the processor, implements the steps of the helmet noise reduction method described above.

[0033] In addition, to achieve the above objectives, the present invention also proposes a computer-readable storage medium storing a helmet noise reduction program, which, when executed by a processor, implements the steps of the helmet noise reduction method described above.

[0034] In this embodiment of the invention, at least two first microphones are installed on the outer side of the helmet to collect environmental noise signals from different directions. Voice signals are also collected through the helmet's communication microphone. A noise reduction benchmark value is obtained by collecting first environmental noise signals through each of the first microphones. Noise suppression processing is applied to each first environmental noise signal so that the noise value of the processed noise signal is less than the noise reduction benchmark value. This achieves targeted noise reduction for environmental noise from different directions, thereby improving the helmet's noise reduction effect. The processed noise signal is mixed with the voice signal and then output to the other end of the call, allowing the user on the other end to hear voice with real environmental noise, but without the voice clarity being affected by excessive environmental noise. In other words, this embodiment of the invention provides a helmet noise reduction solution that improves the noise reduction effect during helmet-based calls, enhances call clarity, and improves the subjective experience of making calls. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating the first embodiment of the helmet noise reduction method of the present invention;

[0036] Figure 2 This is a schematic diagram showing the placement of a microphone in a helmet according to an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the functional modules of a preferred embodiment of the helmet noise reduction device of the present invention.

[0038] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0039] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0040] Reference Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the helmet noise reduction method of the present invention.

[0041] This invention provides an embodiment of a helmet noise reduction method. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here. This invention's helmet noise reduction method is applied to a helmet. In this embodiment, the helmet noise reduction method includes:

[0042] Step S10: Acquire voice signals through the helmet's microphone and acquire first ambient noise signals through each of the first microphones.

[0043] In this embodiment, the helmet can be a helmet with voice call functionality, and a microphone is provided inside the helmet. The microphone is positioned to facilitate the pickup of the user's voice, for example, it can be positioned close to the user's mouth when the helmet is worn. The microphone can collect the user's voice signal. The helmet also includes a microphone for picking up ambient noise signals (hereinafter referred to as the first microphone for distinction). There are at least two first microphones, located on the outer side of the helmet shell (the side of the helmet shell closest to the external environment). The specific placement of these microphones is not limited. However, it is understood that because the first microphones are located on the outer side of the helmet shell, they can pick up ambient noise signals, and because there are at least two first microphones, they can pick up ambient noise signals from at least two directions.

[0044] The ambient noise signal collected by the first microphone is referred to as the first ambient noise signal for distinction.

[0045] In this embodiment, the triggering conditions for the helmet to execute step S10 are not limited. In specific implementations, they can be set as needed. For example, in one feasible implementation, step S10 and subsequent steps can be triggered in response to a user-triggered call noise reduction command. Alternatively, step S10 and subsequent steps can be executed after detecting that a voice call has started.

[0046] In one feasible embodiment, each first microphone can be located in a directional region. Each directional region can include a left-side region, a right-side region, a left-rear region, and a right-rear region on the outer side of the helmet, defined according to the position of the user's left and right ears when wearing the helmet. It is understood that the left-side region is the area on the outer side of the helmet near the left ear, the right-side region is the area on the outer side of the helmet near the right ear, the left-rear region is the area on the outer side of the helmet behind the left ear, and the right-rear region is the area on the outer side of the helmet behind the right ear. The specific location range of each directional region on the outer side of the helmet is not limited in this embodiment. At least one first microphone is provided in each directional region. It should be noted that the location of each directional region is not data related to its configuration within the helmet; the definition of the directional regions is only to help understand the location of the first microphones on the outer side of the helmet. In other embodiments, the number and method of dividing the directional regions can have other possibilities, which can be set according to the needs of the actual application scenario, and will not be listed here.

[0047] Step S20: Obtain the noise reduction reference value, and perform noise suppression processing on each of the first environmental noise signals respectively, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value.

[0048] The noise reduction baseline value is used to limit the degree of noise reduction. In this embodiment, the method of obtaining the noise reduction baseline value is not limited. For example, in one feasible embodiment, a threshold value can be preset and used as the noise reduction baseline value. In another feasible embodiment, a noise reduction baseline value customization function can be set up, allowing users to customize the noise reduction baseline value in the helmet based on this function. The helmet can then retrieve the saved user-defined noise reduction baseline value when needed.

[0049] The helmet performs noise suppression processing on each of the first environmental noise signals separately. There are many ways to perform noise suppression processing on the noise signals so that the noise value of the processed noise signal is less than or equal to the noise reduction reference value. In this embodiment, there is no limitation on which specific method is used. There are many ways to calculate the noise value of the noise signal. In this embodiment, there is no limitation. For example, the average decibel of the noise signal over a period of time can be calculated as the noise value of the noise signal over that period of time.

[0050] Understandably, since the ambient noise signals collected by each microphone come from different directions, the noise levels of each ambient noise signal are not the same. Therefore, noise suppression processing is performed separately for each ambient noise signal, thus achieving targeted noise reduction for different directions and improving the noise reduction experience for users wearing helmets. 。

[0051] Step S30: Mix the processed noise signals with the voice signals and output the mixture to the other end of the call.

[0052] After the helmet performs noise suppression processing on each of the first environmental noise signals, it can mix the processed noise signals with the speech signal and output them to the other end of the call. This allows the user on the other end of the call to hear speech with real environmental noise, but without the speech clarity being affected by excessive environmental noise.

[0053] In a specific implementation, the above steps S20 and S30 can be performed on the voice signal and environmental noise signal collected in the most recent period of time at regular intervals. The duration of this period can be set as needed and is not limited in this embodiment.

[0054] In this embodiment, at least two first microphones are installed on the outer side of the helmet to collect environmental noise signals from different directions. Voice signals are also collected through the helmet's communication microphone. A noise reduction benchmark value is obtained by collecting first environmental noise signals through each of the first microphones. Noise suppression processing is applied to each first environmental noise signal so that the noise value of the processed noise signal is less than the noise reduction benchmark value. This achieves targeted noise reduction for environmental noise from different directions, thereby improving the helmet's noise reduction effect. The processed noise signal is mixed with the voice signal and then output to the other end of the call, allowing the user on the other end to hear voice with real environmental noise, but without the voice clarity being affected by excessive environmental noise. In other words, this embodiment provides a helmet noise reduction solution that improves the noise reduction effect during helmet-based calls, enhances call clarity, and improves the subjective experience of making calls.

[0055] Based on the first embodiment described above, a second embodiment of the helmet noise reduction method of the present invention is proposed. In this embodiment, the step of obtaining the noise reduction reference value in step S20 includes:

[0056] Step S201: Acquire the second ambient noise signal through the second microphone.

[0057] In this embodiment, the outer side of the helmet is divided into a forehead area and other areas. At least one microphone is provided in the forehead area, and at least two microphones are provided in the other areas. The microphone provided in the forehead area is referred to as the second microphone for distinction, and the microphones provided in the other areas are the first microphones in the first embodiment described above.

[0058] The forehead area is a region defined on the outer side of the helmet based on the position of the user's forehead when the helmet is worn. This area is close to or near the user's forehead and can be defined by the designer as needed. It should be noted that the position of the forehead area is not data related to its placement within the helmet; the definition of the forehead area is only to help understand the placement of the first and second microphones on the outer side of the helmet.

[0059] In one feasible implementation, when the first microphone is located in a directional area on the outside of the helmet, the directional area can be obtained by dividing the area on the outside of the helmet other than the forehead area.

[0060] like Figure 2 As shown, the positions of the microphones in the helmet are given by way of example. 1 to 5 represent microphones located in the forehead area, left side area, right side area, left rear area and right rear area, respectively. 1 is the second microphone, 2 to 5 are the first microphones, and 6 represents the call microphone located near the user's chin.

[0061] The ambient noise signal collected by the first microphone is referred to as the second ambient noise signal for distinction.

[0062] Step S202: Calculate the second noise value of the second environmental noise signal, and subtract the first preset threshold from the second noise value to obtain the noise reduction reference value.

[0063] The helmet can calculate the noise value of a second ambient noise signal (referred to as the second noise value for distinction). There are many ways to calculate the noise value of a noise signal, and this embodiment is not limited to any one method. For example, the average decibel level of the noise signal over a period of time can be calculated as the noise value of the noise signal over that period. The result of subtracting a first preset threshold from the second noise value is used as the noise reduction reference value. This first preset threshold can be a threshold set in advance as needed, ensuring that the noise reduction reference value calculated based on the first preset threshold is within a noise value range that is comfortable for the user's hearing. This ensures that after noise suppression processing of the first ambient noise signal based on the noise reduction reference value, the noise does not affect the clarity of speech, thereby improving the noise reduction experience of the helmet. The specific first preset threshold is not limited in this embodiment; for example, it can be set to 40 decibels.

[0064] Understandably, the result of subtracting the first preset threshold from the second noise value is used as the noise reduction benchmark value. Then, noise suppression processing is performed on the first environmental noise signal based on the noise reduction benchmark value, so that the noise value of the processed noise signal is less than or equal to the noise reduction benchmark value. This processing is essentially equivalent to: subtracting the noise value of each first environmental noise signal from the second noise value of the second environmental noise signal to obtain the difference corresponding to each first environmental noise signal; if the difference corresponding to the first environmental noise signal is larger, it means that the noise value of the first environmental noise signal is smaller, and a smaller degree of noise suppression or even no noise suppression is required; if the difference corresponding to the first environmental noise signal is smaller, it means that the noise value of the first environmental noise signal is larger, and a larger degree of noise suppression is required. The purpose of performing noise suppression processing on the first environmental noise signal is to make the difference between the second noise value of the second environmental noise signal and the noise value of the processed first environmental noise signal greater than or equal to the aforementioned first preset threshold value.

[0065] It should be noted that wind noise is generally highest at the forehead area of ​​the helmet when a user is riding. The second ambient noise signal collected by the second microphone located in the forehead area reflects the most realistic level of wind noise during the user's helmet riding experience. By subtracting a first preset threshold from the second noise value of this ambient noise signal, a noise reduction benchmark value is obtained. This ensures that after noise suppression processing of the first ambient noise signal according to the noise reduction benchmark value, the resulting noise signal can reflect the true noise level without affecting the clarity of voice calls. In other words, the greater the forehead wind noise, the larger the calculated noise reduction benchmark value, and the greater the noise value of the noise signal after noise reduction processing. Conversely, the smaller the forehead wind noise, the smaller the calculated noise reduction benchmark value, and the smaller the noise value of the noise signal after noise reduction processing. This reflects the true noise level, and the user can perceive the difference in noise under different levels of wind noise, but because of the noise reduction processing, it will not affect the clarity of voice calls.

[0066] In one feasible implementation, the step of obtaining the noise reduction reference value in step S20 further includes:

[0067] Step S203: Detect whether the posture of the helmet is a preset frontal riding posture.

[0068] Considering that users may turn their heads while riding, resulting in their foreheads not facing the direction of riding, if the noise reduction baseline value is still calculated based on the second ambient noise signal collected by the second microphone located in the forehead area, the noise reduction baseline value will change too frequently and abruptly, which in turn will cause the noise value of the noise signal after noise suppression processing to change too frequently and abruptly.

[0069] In this embodiment, to solve the problem, it is proposed to detect whether the helmet posture is a preset frontal riding posture, and to obtain the noise reduction benchmark value by different methods according to the detection results.

[0070] The preset frontal riding posture can be set based on the posture when the helmet is facing the riding direction, and this is not limited in this embodiment. The helmet posture can be measured by a posture detection device installed on the helmet. The posture detection device can be an inertial measurement unit, accelerometer, etc., and this is not limited in this embodiment. For example, in one feasible embodiment, the helmet can be preset to a simulated riding state with the front of the helmet facing the riding direction. In this state, the triaxial accelerometer installed on the helmet collects acceleration data in various directions. Based on the collected acceleration data, a certain range of fluctuation is made to obtain the acceleration data range in each direction. The posture defined by the acceleration data range in each direction is taken as the preset frontal riding posture. When detecting whether the helmet posture is the preset frontal riding posture, the acceleration data in each direction collected by the triaxial accelerometer on the helmet is acquired and compared with the corresponding acceleration data range. If all fall within the corresponding acceleration data range, the helmet posture is determined to be the preset frontal riding posture; otherwise, the helmet posture is determined not to be the preset frontal riding posture.

[0071] Step S204: If the helmet posture is the preset frontal riding posture, then the step of subtracting the first preset threshold from the second noise value to obtain the noise reduction reference value is executed.

[0072] If the helmet posture is determined to be a preset frontal riding posture, a noise reduction reference value can be obtained by subtracting a first preset threshold from the second noise value corresponding to the second environmental noise signal. This ensures that the noise signal obtained by noise suppression processing based on the noise reduction reference value can reflect the true noise level without affecting the clarity of the voice call.

[0073] Step S205: If the helmet's posture is not the preset frontal riding posture, then obtain the second preset threshold as the noise reduction reference value.

[0074] The second preset threshold is a pre-set threshold that falls within a noise level range that is comfortable for the user's hearing. It can be set as needed and is not limited in this embodiment. If the helmet's posture is determined not to be the preset frontal riding posture, the second preset threshold can be used as the noise reduction reference value. That is, when the user's head is turned to the side, a pre-set fixed noise value is used as the noise reduction reference value to avoid the noise reduction reference value changing too frequently and abruptly, thereby preventing the noise signal after noise suppression processing from changing too frequently and abruptly.

[0075] Based on the first and / or second embodiments described above, a second embodiment of the helmet noise reduction method of the present invention is proposed. In this embodiment, the step of performing noise suppression processing on each of the first environmental noise signals in step S20 includes:

[0076] Step S206: Calculate the first noise value for each of the first environmental noise signals.

[0077] In this embodiment, a feasible implementation method for noise suppression processing of each first environmental noise signal based on a noise reduction reference value is proposed.

[0078] The noise value of each first environmental noise signal (hereinafter referred to as the first noise value for distinction) can be calculated separately. There are many ways to calculate the noise value of a noise signal, and this embodiment does not impose any restrictions. For example, the average decibel of the noise signal over a period of time can be calculated as the noise value of the noise signal over that period of time.

[0079] Step S207: If the first noise value is greater than the noise reduction reference value, then noise suppression processing is performed on the first environmental noise signal corresponding to the first noise value.

[0080] The first noise value of each first ambient noise signal can be compared with the noise reduction reference value. If a certain first noise value is greater than the noise reduction reference value, it means that the noise value of the first ambient noise signal corresponding to the first noise value exceeds the range that the user finds comfortable to hear. At this time, the first ambient noise signal corresponding to the first noise value can be subjected to noise suppression processing so that the noise value of the processed noise signal corresponding to the first ambient noise signal is less than the noise reduction reference value.

[0081] Step S208: If the first noise value is less than or equal to the noise reduction reference value, then the first environmental noise signal corresponding to the first noise value is used as the noise signal after noise suppression processing.

[0082] If a certain first noise value is less than or equal to the noise reduction reference value, it means that the noise value of the first ambient noise signal corresponding to the first noise value does not exceed the range that the user feels comfortable with hearing. In this case, the first ambient noise signal corresponding to the first noise value can be left unprocessed, that is, the first ambient noise signal can be directly used as the noise signal after noise suppression processing.

[0083] In one feasible implementation, step S207 includes:

[0084] Step S2071: If the first noise value is greater than the noise reduction reference value, then the noise reduction reference value is divided by the first noise value to obtain the noise reduction ratio.

[0085] In this embodiment, a feasible implementation method is proposed to perform noise suppression processing on a first environmental noise signal so that the noise value of the processed noise signal is less than the noise reduction reference value.

[0086] If a certain first noise value is greater than the noise reduction reference value, the noise reduction reference value can be divided by the first noise value to obtain a noise reduction ratio. For example, if the noise reduction reference value is 40 and the first noise value is 60, then the calculated noise reduction ratio is 2 / 3.

[0087] Step S2072: Multiply the first ambient noise signal corresponding to the first noise value by the noise reduction ratio to obtain the noise signal after noise suppression processing.

[0088] By multiplying the first ambient noise signal corresponding to the first noise value that is greater than the noise reduction reference value by the noise reduction ratio, the noise signal after noise suppression processing can be obtained.

[0089] In one feasible embodiment, after the step of performing noise suppression processing on each of the first environmental noise signals in step S20, the method further includes:

[0090] Step S40: Detect whether the helmet is in a call state.

[0091] In this embodiment, considering that when a user is using the helmet but not in a call state, call noise reduction is not required, but they may not be able to hear ambient noise clearly, affecting the user's helmet-using experience and safety. To solve this problem, this embodiment proposes to detect whether the helmet is in a call state.

[0092] Step S50: If the helmet is in a call state, then step S30 is executed;

[0093] If the helmet is in call mode, the noise signal obtained by performing noise suppression processing on each first environmental noise signal can be mixed with the voice signal collected by the call microphone and then output to the other end of the call to reduce the noise of the call voice.

[0094] Step S60: If the helmet is not in a call state, the processed noise signals are mixed and then output through the helmet's speaker.

[0095] If the helmet is not in a call state, the noise signals obtained after noise suppression processing of each first ambient noise signal can be directly mixed and output through the speaker set in the helmet to the user wearing the helmet. This allows the user to hear the external ambient noise clearly, avoiding the user's experience of using the helmet if they cannot hear the external ambient sounds, and also avoiding affecting the user's safety when using the helmet. Furthermore, because the first ambient noise signals collected by each first microphone have undergone noise suppression processing, the noise level of the ambient noise heard by the user is within a comfortable range, thereby improving the noise reduction effect.

[0096] Furthermore, this invention also proposes a helmet noise reduction device, which is deployed on a helmet, and at least two first microphones are provided on the outer side of the helmet body, referring to... Figure 3 The helmet noise reduction device includes:

[0097] The signal acquisition device 10 is used to acquire voice signals through the helmet's microphone and to acquire first ambient noise signals through each of the first microphones.

[0098] The noise suppression module 20 is used to obtain a noise reduction reference value and perform noise suppression processing on each of the first environmental noise signals respectively, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value.

[0099] The output module 30 is used to mix the processed noise signals with the voice signals and output them to the other end of the call.

[0100] In one feasible embodiment, at least one second microphone is also provided on the outer side of the helmet body. The second microphone is located in the forehead area, which is a region defined on the outer side of the helmet body according to the position of the user's forehead when wearing the helmet. The first microphone is located in the region on the outer side of the helmet body other than the forehead area.

[0101] The noise suppression module 20 is also used for:

[0102] The second ambient noise signal is acquired through the second microphone;

[0103] Calculate the second noise value of the second environmental noise signal, and subtract the first preset threshold from the second noise value to obtain the noise reduction reference value.

[0104] In one feasible embodiment, the noise suppression module 20 is further configured to:

[0105] Detect whether the helmet's posture is a preset frontal riding posture;

[0106] If the helmet's posture is the preset frontal riding posture, then the step of subtracting the first preset threshold from the second noise value to obtain the noise reduction reference value is performed.

[0107] If the helmet's posture is not the preset frontal riding posture, then a second preset threshold is obtained as the noise reduction benchmark value.

[0108] In one feasible embodiment, the noise suppression module 20 is further configured to:

[0109] Calculate the first noise value for each of the first environmental noise signals;

[0110] If the first noise value is greater than the noise reduction reference value, then noise suppression processing is performed on the first environmental noise signal corresponding to the first noise value;

[0111] If the first noise value is less than or equal to the noise reduction reference value, then the first environmental noise signal corresponding to the first noise value is taken as the noise signal after noise suppression processing.

[0112] In one feasible embodiment, the noise suppression module 20 is further configured to:

[0113] If the first noise value is greater than the noise reduction reference value, then the noise reduction reference value is divided by the first noise value to obtain the noise reduction ratio;

[0114] The noise signal after noise suppression is obtained by multiplying the first environmental noise signal corresponding to the first noise value by the noise reduction ratio.

[0115] In one feasible embodiment, the helmet noise reduction device further includes:

[0116] The detection module is used to detect whether the helmet is in a call state;

[0117] The output module 30 is also used for:

[0118] If the helmet is in a call state, then the step of mixing the processed noise signals with the voice signal and outputting the mixture to the other end of the call is performed.

[0119] If the helmet is not in a call state, the processed noise signals are mixed and then output through the helmet's speaker.

[0120] In one feasible embodiment, each of the first microphones is disposed in a respective directional region, and each directional region includes a left region, a right region, a left rear region, and a right rear region, which are divided on the outer side of the helmet according to the position of the user's left and right ears when the helmet is worn.

[0121] The extended content of the specific implementation of the helmet noise reduction device of the present invention is basically the same as the various embodiments of the helmet noise reduction method described above, and will not be repeated here.

[0122] The helmet of this invention comprises a structural shell, a communication module, a main control module (e.g., a microcontroller unit (MCU), a speaker, a microphone, and a memory. At least two first microphones are disposed on the outer side of the helmet body. The main control module may include a microprocessor, an audio decoding unit, a power supply and power management unit, sensors required by the system, and other active or passive components (which can be replaced, removed, or added according to actual functions) to realize the function of wireless audio reception and playback. The memory may store a helmet noise reduction program, which the microprocessor can call to perform the following operations:

[0123] Voice signals are collected through the helmet's microphone, and first ambient noise signals are collected through each of the first microphones.

[0124] Obtain a noise reduction reference value, and perform noise suppression processing on each of the first environmental noise signals respectively, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value;

[0125] The processed noise signals are mixed with the voice signals and then output to the other end of the call.

[0126] In one feasible embodiment, at least one second microphone is also provided on the outer side of the helmet body. The second microphone is located in the forehead area, which is a region defined on the outer side of the helmet body according to the position of the user's forehead when wearing the helmet. The first microphone is located in the region on the outer side of the helmet body other than the forehead area.

[0127] The operation of obtaining the noise reduction reference value includes:

[0128] The second ambient noise signal is acquired through the second microphone;

[0129] Calculate the second noise value of the second environmental noise signal, and subtract the first preset threshold from the second noise value to obtain the noise reduction reference value.

[0130] In one feasible implementation, the operation of obtaining the noise reduction reference value further includes:

[0131] Detect whether the helmet's posture is a preset frontal riding posture;

[0132] If the helmet's posture is the preset frontal riding posture, then the operation of subtracting the first preset threshold from the second noise value to obtain the noise reduction reference value is performed;

[0133] If the helmet's posture is not the preset frontal riding posture, then a second preset threshold is obtained as the noise reduction benchmark value.

[0134] In one feasible implementation, the operation of performing noise suppression processing on each of the first environmental noise signals includes:

[0135] Calculate the first noise value for each of the first environmental noise signals;

[0136] If the first noise value is greater than the noise reduction reference value, then noise suppression processing is performed on the first environmental noise signal corresponding to the first noise value;

[0137] If the first noise value is less than or equal to the noise reduction reference value, then the first environmental noise signal corresponding to the first noise value is taken as the noise signal after noise suppression processing.

[0138] In one feasible implementation, the step of performing noise suppression processing on the first environmental noise signal corresponding to the first noise value if the first noise value is greater than the noise reduction reference value includes:

[0139] If the first noise value is greater than the noise reduction reference value, then the noise reduction reference value is divided by the first noise value to obtain the noise reduction ratio;

[0140] The noise signal after noise suppression is obtained by multiplying the first environmental noise signal corresponding to the first noise value by the noise reduction ratio.

[0141] In one feasible implementation, after performing noise suppression processing on each of the first environmental noise signals, the microprocessor can further be used to call the helmet noise reduction program stored in the memory and perform the following operations:

[0142] Detect whether the helmet is in a call state;

[0143] If the helmet is in a call state, then the operation of mixing the processed noise signals with the voice signal and outputting the mixture to the other end of the call is performed.

[0144] If the helmet is not in a call state, the processed noise signals are mixed and then output through the helmet's speaker.

[0145] In one feasible embodiment, each of the first microphones is disposed in a respective directional region, and each directional region includes a left region, a right region, a left rear region, and a right rear region, which are divided on the outer side of the helmet according to the position of the user's left and right ears when the helmet is worn.

[0146] The various embodiments of the helmet and computer-readable storage medium of the present invention can be referred to the various embodiments of the helmet noise reduction method of the present invention, and will not be repeated here.

[0147] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0148] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0149] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this 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. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0150] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A helmet noise reduction method, characterized in that, The helmet noise reduction method is applied to a cycling helmet. At least two first microphones are provided on the outer side of the helmet body, and at least one second microphone is also provided on the outer side of the helmet body. The second microphone is located in the forehead area, which is a region defined on the outer side of the helmet body based on the position of the user's forehead when wearing the helmet. The first microphones are located in the area on the outer side of the helmet body excluding the forehead area. The helmet noise reduction method includes: Voice signals are collected through the helmet's microphone, and first ambient noise signals are collected through each of the first microphones. Obtain a noise reduction reference value, and perform noise suppression processing on each of the first environmental noise signals respectively, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value; The step of obtaining the noise reduction reference value includes: acquiring a second ambient noise signal through the second microphone; calculating a second noise value of the second ambient noise signal; and subtracting a first preset threshold from the second noise value to obtain the noise reduction reference value. The step of obtaining the noise reduction reference value further includes: detecting whether the helmet's posture is a preset frontal riding posture; if the helmet's posture is the preset frontal riding posture, then performing the step of subtracting the first preset threshold from the second noise value to obtain the noise reduction reference value; if the helmet's posture is not the preset frontal riding posture, then obtaining the second preset threshold as the noise reduction reference value. The processed noise signals are mixed with the voice signals and then output to the other end of the call.

2. The helmet noise reduction method as described in claim 1, characterized in that, The step of performing noise suppression processing on each of the first environmental noise signals includes: Calculate the first noise value for each of the first environmental noise signals; If the first noise value is greater than the noise reduction reference value, then noise suppression processing is performed on the first environmental noise signal corresponding to the first noise value; If the first noise value is less than or equal to the noise reduction reference value, then the first environmental noise signal corresponding to the first noise value is taken as the noise signal after noise suppression processing.

3. The helmet noise reduction method as described in claim 2, characterized in that, The step of performing noise suppression processing on the first environmental noise signal corresponding to the first noise value if the first noise value is greater than the noise reduction reference value includes: If the first noise value is greater than the noise reduction reference value, then the noise reduction reference value is divided by the first noise value to obtain the noise reduction ratio; The noise signal after noise suppression is obtained by multiplying the first environmental noise signal corresponding to the first noise value by the noise reduction ratio.

4. The helmet noise reduction method as described in claim 1, characterized in that, After the step of performing noise suppression processing on each of the first environmental noise signals, the method further includes: Detect whether the helmet is in a call state; If the helmet is in a call state, then the step of mixing the processed noise signals with the voice signal and outputting the mixture to the other end of the call is performed. If the helmet is not in a call state, the processed noise signals are mixed and then output through the helmet's speaker.

5. The helmet noise reduction method according to any one of claims 1 to 4, characterized in that, Each of the first microphones is located in a directional region, and each directional region includes a left region, a right region, a left rear region, and a right rear region, which are divided on the outer side of the helmet according to the position of the user's left and right ears when wearing the helmet.

6. A helmet noise reduction device, characterized in that, The helmet noise reduction device is deployed on a cycling helmet. At least two first microphones are located on the outer side of the helmet body, and at least one second microphone is also located on the outer side of the helmet body. The second microphone is positioned in the forehead area, which is defined on the outer side of the helmet body according to the position of the user's forehead when wearing the helmet. The first microphones are located on the outer side of the helmet body excluding the forehead area. The helmet noise reduction device includes: A signal acquisition device is used to acquire voice signals through the helmet's microphone and to acquire first ambient noise signals through each of the first microphones. A noise suppression module is used to acquire a noise reduction reference value and perform noise suppression processing on each of the first environmental noise signals, wherein the noise value of the processed noise signal is less than or equal to the noise reduction reference value. Specifically, the noise suppression module is used to acquire a second environmental noise signal through a second microphone; calculate a second noise value of the second environmental noise signal and subtract a first preset threshold from the second noise value to obtain the noise reduction reference value. Specifically, the noise suppression module is used to detect whether the helmet's posture is a preset frontal riding posture; if the helmet's posture is the preset frontal riding posture, then the step of subtracting the first preset threshold from the second noise value to obtain the noise reduction reference value is executed; if the helmet's posture is not the preset frontal riding posture, then a second preset threshold is acquired as the noise reduction reference value. The output module is used to mix the processed noise signals with the voice signals and output them to the other end of the call.

7. A helmet, characterized in that, The helmet includes: a memory, a processor, and a helmet noise reduction program stored in the memory and executable on the processor, wherein the helmet noise reduction program, when executed by the processor, implements the steps of the helmet noise reduction method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a helmet noise reduction program, which, when executed by a processor, implements the steps of the helmet noise reduction method as described in any one of claims 1 to 5.

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