Audio optimization method, device and equipment of smart wearable device and storage medium

Abstract

The present application relates to the technical field of smart wear, especially to an audio optimization method, device and equipment of smart wear equipment and storage medium, the present application obtains driving data and head movement data, and compensates the head movement data according to the driving data, obtains the target head movement data after compensation, calculates based on the target head movement data after compensation, obtains the head posture solution, thereby reducing the influence of driving process on autonomous head movement, finally, the sound field is calculated by the head posture solution, and then the sound field head movement optimization is realized, the tracking of audio and autonomous head movement is realized, the technical problem that the audio playing effect of smart wear equipment is poor in the prior art driving scene is avoided, and the audio playing effect is improved.

Description

Technical Field

[0001] This invention relates to the field of smart wearable technology, and in particular to an audio optimization method, apparatus, device, and storage medium for smart wearable devices. Background Technology

[0002] When users use VR devices in a vehicle-riding scenario, the vehicle will experience movements such as bumps, turns, and braking. Since VR devices rely solely on built-in sensor data and software logic, they cannot distinguish between the vehicle's movement and the user's own head movements. This leads to many misjudgments, affecting the user experience of smart wearable devices. In particular, when smart wearable devices perform 3D surround sound / head-tracking audio effects, the audio may be out of sync with the virtual video in the VR device, and the audio playback quality may be poor, impacting the user experience.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this invention is to provide an audio optimization method, apparatus, device, and storage medium for smart wearable devices, aiming to solve the technical problem of poor audio playback performance of smart wearable devices in the context of commuting.

[0005] To achieve the above objectives, the present invention provides an audio optimization method for smart wearable devices, the method comprising the following steps: Acquire driving data and head movement data; The head movement data is numerically compensated based on the driving data to obtain the target head movement data; The head posture solution is obtained by calculating based on the target head motion data; The sound field is calculated based on the head posture solution, and the sound field head movement is optimized based on the calculation results.

[0006] Optionally, the driving data includes vehicle acceleration, road condition information, and turning information; The step of numerically compensating the head movement data based on the driving data to obtain the target head movement data includes: A target correction coefficient is generated based on the vehicle acceleration, the road condition information, and the turning information. The head movement data is numerically compensated based on the target correction coefficient to obtain the target head movement data.

[0007] Optionally, generating the target correction coefficient based on the vehicle acceleration, the road condition information, and the turning information includes: The target correction coefficients corresponding to the vehicle acceleration, road condition information, and turning information are determined based on a preset mapping relationship. The preset mapping relationship includes: a first correction coefficient for the head motion data under different vehicle acceleration intervals, a second correction coefficient for the head motion data under different road condition information intervals, and a third correction coefficient for the head motion data under different turning information intervals. The target correction coefficient is the sum of the first correction coefficient, the second correction coefficient, and the third correction coefficient.

[0008] Optionally, the target correction coefficients include: a forward correction coefficient, a lateral correction coefficient, and a vertical correction coefficient, and the head motion data includes forward acceleration, lateral acceleration, and vertical acceleration; The step of correcting the head movement data according to the target correction coefficient includes: The forward acceleration is corrected according to the forward correction coefficient; The lateral acceleration is corrected according to the lateral correction coefficient; The vertical acceleration is corrected according to the vertical correction coefficient.

[0009] Optionally, the head motion data further includes: acceleration data, gyroscope data, and magnetometer data, and the head attitude solution includes: Euler angles and quaternions; The calculation based on the target head motion data to obtain the head pose solution includes: Acquire magnetometer data; The gyroscope data is corrected based on the magnetometer data and the acceleration data to obtain the target gyroscope data; The quaternion corresponding to the target gyroscope data is determined by a preset quaternion differential model. Euler angles are generated based on the quaternion using a preset transformation strategy.

[0010] Optionally, the audio optimization method for the smart wearable device further includes: The target gyroscope data is split to obtain Euler angles, which include pitch angle, roll angle and yaw angle; The quaternions corresponding to the pitch angle, roll angle, and heading angle are determined based on a preset conversion model.

[0011] Optionally, acquiring driving data and head movement data includes: Identify the scene in which the smart wearable device is located; When the scenario is a passenger scenario, a data transmission channel is established between the vehicle and the target vehicle; When the smart wearable device activates the head-motion sound effect mode, it acquires head-motion data and receives driving data sent by the target vehicle through the data transmission channel.

[0012] Furthermore, to achieve the above objectives, the present invention also proposes an audio optimization device for a smart wearable device, the audio optimization device for the smart wearable device comprising: The acquisition module is used to acquire driving data and head movement data; The compensation module is used to perform numerical compensation on the head movement data based on the driving data to obtain the target head movement data; The calculation module is used to calculate the head posture solution based on the target head motion data; The optimization module is used to calculate the sound field based on the head posture solution and optimize the sound field head movement based on the calculation results.

[0013] Furthermore, to achieve the above objectives, the present invention also proposes an audio optimization device for a smart wearable device, the audio optimization device for a smart wearable device comprising: a memory, a processor, and an audio optimization program for a smart wearable device stored in the memory and executable on the processor, the audio optimization program for a smart wearable device being configured to implement the steps of the audio optimization method for a smart wearable device as described above.

[0014] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing an audio optimization program for a smart wearable device, wherein when the audio optimization program for the smart wearable device is executed by a processor, it implements the steps of the audio optimization method for the smart wearable device as described above.

[0015] This invention discloses an audio optimization method for smart wearable devices. The method includes: acquiring driving data and head movement data; performing numerical compensation on the head movement data based on the driving data to obtain target head movement data; calculating a head posture solution based on the target head movement data; performing sound field calculation based on the head posture solution; and optimizing the sound field head movement based on the calculation results. This invention reduces the impact of driving on autonomous head movement by acquiring driving data and head movement data, performing numerical compensation on the head movement data based on the driving data to obtain compensated target head movement data, and then calculating a head posture solution based on the compensated target head movement data. Finally, by performing sound field calculation on the head posture solution, sound field head movement optimization is achieved, enabling audio and autonomous head movement tracking. This avoids the technical problem of poor audio playback effect of smart wearable devices in car riding scenarios in existing technologies, and improves the audio playback effect. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of the audio optimization device of the smart wearable device in the hardware operating environment involved in the embodiments of the present invention; Figure 2This is a flowchart illustrating the first embodiment of the audio optimization method for a smart wearable device according to the present invention. Figure 3 This is a schematic diagram of the overall control logic of an embodiment of the audio optimization method for a smart wearable device according to the present invention; Figure 4 This is a flowchart illustrating the second embodiment of the audio optimization method for a smart wearable device according to the present invention; Figure 5 This is a flowchart illustrating the third embodiment of the audio optimization method for a smart wearable device according to the present invention. Figure 6 This is a schematic diagram of quaternion and Euler angle transformation in the first embodiment of the audio optimization method for the smart wearable device of the present invention; Figure 7 This is a structural block diagram of the first embodiment of the audio optimization device for the smart wearable device of the present invention.

[0017] 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

[0018] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0019] Reference Figure 1 , Figure 1 This is a schematic diagram of the audio optimization device structure of a smart wearable device in the hardware operating environment of an embodiment of the present invention.

[0020] like Figure 1 As shown, the audio optimization device of this smart wearable device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0021] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the audio optimization device for smart wearable devices and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0022] like Figure 1 As shown, the memory 1005, which serves as a storage medium, may include an operating system, a network communication module, a user interface module, and an audio optimization program for smart wearable devices.

[0023] exist Figure 1 In the audio optimization device of the smart wearable device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the audio optimization device of the smart wearable device of the present invention can be set in the audio optimization device of the smart wearable device. The audio optimization device of the smart wearable device calls the audio optimization program of the smart wearable device stored in the memory 1005 through the processor 1001 and executes the audio optimization method of the smart wearable device provided in the embodiment of the present invention.

[0024] This invention provides an audio optimization method for smart wearable devices, referring to... Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of an audio optimization method for a smart wearable device according to the present invention.

[0025] In this embodiment, the audio optimization method for the smart wearable device includes the following steps: Step S10: Obtain driving data and head movement data.

[0026] It should be noted that the execution subject of the method in this embodiment refers to a device with functions such as data processing, network communication, and program execution, such as a control chip or controller of a smart wearable device. It can also be other devices that can achieve the same or similar functions. This embodiment does not impose specific limitations on this. In this embodiment and the following embodiments, the control chip of a smart wearable device will be used as an example for explanation.

[0027] It should be noted that the smart wearable device mentioned in this embodiment and the following embodiments refers to a virtual reality (VR) device or an augmented reality (AR) device, such as a VR headset or AR glasses, etc. This embodiment does not impose any specific limitations on this.

[0028] It is understandable that driving data includes, but is not limited to, driving acceleration, road condition information (degree of bumpiness), and turning information; head motion data includes, but is not limited to, acceleration data, gyroscope data (angular velocity data), and magnetometer data.

[0029] In the specific implementation, vehicle acceleration, road condition information (bumpiness level), and turning information are all collected by the vehicle and transmitted wirelessly to the smart wearable device for storage, so as to facilitate audio optimization. The acceleration data in the head motion data is collected by the accelerometer installed in the smart wearable device. Both the gyroscope data and acceleration data in the head motion data can be measured by the six-axis inertial measurement unit (IMU) installed in the smart wearable device. In addition, in this embodiment, the smart wearable device may be equipped with a six-axis vertical reference unit (VRU) for data calibration.

[0030] An inertial measurement unit (IMU) is a device that measures the three-axis angular velocity and acceleration of an object. An IMU may contain a three-axis gyroscope and a three-axis accelerometer to measure the angular velocity and acceleration of an object in three-dimensional space.

[0031] Furthermore, prior to step S10, the procedure also includes: Identify the scene in which the smart wearable device is located; When the scenario is a passenger scenario, a data transmission channel is established between the vehicle and the target vehicle; When the smart wearable device activates the head-motion sound effect mode, it acquires head-motion data and receives driving data sent by the target vehicle through the data transmission channel.

[0032] In the specific implementation, refer to Figure 3 , Figure 3 This is a schematic diagram of the overall process of this embodiment. When the scenario in which the smart wearable device is located is a car ride scenario, a data transmission channel can be established with the target vehicle through wireless communication channels such as Bluetooth or WiFi to facilitate subsequent driving data transmission. When the smart wearable device turns on the head movement sound effect mode, it collects head movement data through the built-in six-axis inertial measurement unit or six-axis vertical reference unit, and receives information such as driving acceleration, road condition information (bumpiness) and turning information sent by the vehicle.

[0033] Step S20: Perform numerical compensation on the head movement data based on the driving data to obtain the target head movement data.

[0034] It should be understood that since the head motion data are all in three-dimensional space, in order to facilitate calculation and calibration, numerical compensation can be performed on the head motion data in the three-dimensional coordinate system in this embodiment. Therefore, before performing numerical compensation, it is necessary to determine the compensation coefficients of the driving data for different axes in the head motion data in order to minimize the impact of the driving data on the smart wearable device.

[0035] In this implementation, in order to reduce the impact of driving on smart wearable devices, the driving data in this embodiment are all raw data directly collected by vehicle sensors without filtering, so as to restore the real riding situation as much as possible.

[0036] Step S30: Calculate the head posture solution based on the target head motion data.

[0037] Understandably, in order to match the position and movement of the smart wearable device relative to the world coordinate system, this embodiment generally performs coordinate system transformation on the head movement data to convert the data in the carrier coordinate system into the navigation coordinate system. The carrier coordinate system refers to the coordinate system corresponding to the smart wearable device, and the navigation coordinate system refers to the world coordinate system.

[0038] In practical implementation, the carrier coordinate system generally refers to the coordinate system that moves with the moving object (the coordinate system fixed to the carrier): it is generally called the b (body) system (carrier system), s (sensor) system (sensor coordinate system), r (robot) system (robot coordinate system), etc., indicating that the coordinate system is fixed on the moving object and moves with the object.

[0039] To better determine the operational status of smart wearable devices, this embodiment converts head motion data in the carrier coordinate system into head motion data in the world coordinate system, thereby determining the position and posture information of the smart wearable device and enhancing the user's virtual reality or augmented reality experience.

[0040] Head pose solutions include, but are not limited to, quaternions and Euler angles.

[0041] Step S40: Calculate the sound field based on the head posture solution, and optimize the sound field head movement based on the calculation results.

[0042] In the actual implementation, after calculating Euler angles and quaternions, the sound field is calculated based on the quaternions to obtain the effect of 3D surround / head tracking, thereby improving the user experience.

[0043] This embodiment acquires driving data and head movement data, and performs numerical compensation on the head movement data based on the driving data to obtain compensated target head movement data. Then, it calculates the head posture solution based on the compensated target head movement data, thereby reducing the impact of driving on autonomous head movement. Finally, it performs sound field calculation on the head posture solution to achieve sound field head movement optimization, enabling audio and autonomous head movement tracking. This avoids the technical problem of poor audio playback effect of smart wearable devices in existing vehicle scenarios, and improves the audio playback effect.

[0044] refer to Figure 4 , Figure 4 This is a flowchart illustrating a second embodiment of an audio optimization method for a smart wearable device according to the present invention.

[0045] Based on the first embodiment described above, in this embodiment, step S20 includes: Step S201: Generate a target correction coefficient based on the vehicle acceleration, the road condition information, and the turning information.

[0046] It should be noted that the target correction coefficients include: forward correction coefficient, lateral correction coefficient, and vertical correction coefficient, which correspond to the three axes of the coordinate system and are used to correct the forward head movement data, lateral head movement data, and vertical head movement data, respectively.

[0047] Further, generating the target correction coefficient based on the vehicle acceleration, the road condition information, and the turning information includes: The target correction coefficients corresponding to the vehicle acceleration, road condition information, and turning information are determined based on a preset mapping relationship. The preset mapping relationship includes: a first correction coefficient for the head motion data under different vehicle acceleration intervals, a second correction coefficient for the head motion data under different road condition information intervals, and a third correction coefficient for the head motion data under different turning information intervals. The target correction coefficient is the sum of the first correction coefficient, the second correction coefficient, and the third correction coefficient.

[0048] In specific implementation, the first correction coefficient includes: the forward acceleration correction coefficient of the smart wearable device under different driving acceleration ranges, the lateral acceleration correction coefficient of the smart wearable device, the vertical acceleration correction coefficient of the smart wearable device, the forward angular velocity (gyroscope data) correction coefficient of the smart wearable device, the lateral angular velocity correction coefficient of the smart wearable device, and the vertical angular velocity correction coefficient of the smart wearable device. The preset mapping relationship can be found in Table 1.

[0049] Table 1

[0050] In specific implementation, if there are multiple correction coefficients for the same head motion data, the sum of each correction coefficient can be used as the target correction coefficient to numerically compensate the head motion data. For example, when the driving acceleration is between 0 and 6, the correction coefficient for the vertical head motion acceleration is +10%, while when the road condition information is normal, the correction coefficient for the vertical head motion acceleration is -35%, that is, the final target correction coefficient is -25%. This embodiment does not impose specific restrictions on this.

[0051] Step S202: Perform numerical compensation on the head movement data according to the target correction coefficient to obtain the target head movement data.

[0052] In this embodiment, the correction coefficients for the same driving data differ for different directions or different head movement data. This embodiment corrects the forward acceleration based on the forward correction coefficient, the lateral acceleration based on the lateral correction coefficient, and the vertical acceleration based on the vertical correction coefficient to achieve accurate data value compensation and reduce the impact of driving process on head movement tracking.

[0053] This embodiment determines the target correction coefficient by querying the preset mapping relationship through vehicle acceleration, road condition information, and turning information. This allows for numerical correction of head movement data for different head movement data or head movement data in different directions, reducing the impact of driving on head movement data and thus improving the playback effect of subsequent audio tracking.

[0054] refer to Figure 5 , Figure 5 This is a flowchart illustrating the third embodiment of an audio optimization method for a smart wearable device according to the present invention.

[0055] Based on the second embodiment described above, in this embodiment, step S30 includes: Step S301: Acquire magnetometer data.

[0056] It should be noted that the magnetometer measures the magnetic field strength of three axes (the Earth's magnetic field + other nearby interfering magnetic fields), such as magnets, metal objects, etc. The output is the angle between the current body and the Earth's magnetic field. The magnetometer has good low-frequency characteristics and is easily affected by the surrounding magnetic field.

[0057] Step S302: Correct the gyroscope data based on the magnetometer data and the acceleration data to obtain the target gyroscope data.

[0058] Since accelerometers measure not only gravitational acceleration but also other motion accelerations (harmful accelerations), prolonged motion can lead to significant deviations in head posture solutions. Therefore, this embodiment uses magnetometer data and acceleration data to correct gyroscope data, reducing posture deviations and improving tracking accuracy.

[0059] In the specific implementation, before performing attitude calculations, the acceleration data is standardized by passing a low-pass filter, and the magnetometer data is normalized. Then, the normalized magnetometer data is subjected to coordinate transformation, that is, the actual measured value of the magnetometer is transformed into the theoretical value of the magnetometer in the carrier coordinate system. This process is called vector product operation.

[0060] By performing a cross product operation on the correction value of the acceleration data, the actual measured value, and the theoretical and actual measured values ​​of the magnetometer data, the error value can be obtained. Adding this error value to the angular velocity collected by the gyroscope yields the target gyroscope data.

[0061] Step S303: Determine the quaternion corresponding to the target gyroscope data using a preset quaternion differential model.

[0062] Step S304: Generate Euler angles based on the quaternion using a preset transformation strategy.

[0063] It should be noted that quaternions and Euler angles are interchangeable; for specific conversion relationships, please refer to [reference needed]. Figure 6 Therefore, this embodiment does not limit the calculation of Euler angles or quaternions to be performed first. Euler angles are a set of three independent angular parameters used to determine the position of a rigid body rotating at a fixed point, consisting of roll angle θ, yaw angle ψ, and pitch angle φ. Rotation about the Z-axis is represented by yaw angle (YAW)ψ, rotation about the Y-axis by roll angle (ROLL)θ, and rotation about the X-axis by pitch angle (PITCH)φ. The quaternion attitude expression is a four-parameter expression, meaning that a transformation from one coordinate system to another can be achieved through a single rotation about a vector u defined in the reference frame. A quaternion is represented by the symbol q; it is a vector with four elements, which are functions of the vector's direction and the magnitude of the rotation.

[0064] In this embodiment, Euler angle transformation quaternions are used as an example: The coordinates of a point in the navigation coordinate system n are defined as (x, y, z). Let the coordinates of this point in the carrier coordinate system be (x', y', z'). When the carrier coordinate system deviates from the navigation coordinate system by an angle ψ in the xy plane, for any point, the relationship between the coordinates in the two coordinate systems is easily obtained:

[0065] Represented in matrix form as follows:

[0066] Rotating around the Y-axis by an angle θ (ROLL), the transformation relationship between the two coordinate systems:

[0067] Transformation between two coordinate systems when rotating about the X-axis by an angle φ (pitch):

[0068] From the previous conclusions, we can derive the relationship between the vector [xn, yn, zn] in the navigation coordinate system and the vector [xb, yb, zb] in the rotated vehicle coordinate system after a rotation involving three Euler angles:

[0069] Give the coordinate transformation matrix from vector [xb, yb, zb] in the vehicle coordinate system to vector [xn, yn, zn] in the navigation coordinate system:

[0070] Therefore, we can obtain the coordinate transformation matrix expressed in Euler angles:

[0071] This embodiment calculates quaternions and Euler angles based on the target acceleration, gyroscope data, and magnetometer data of the smart wearable device, so as to facilitate subsequent sound field calculations, achieve sound field head motion optimization, and improve audio playback effect.

[0072] Furthermore, this embodiment of the invention also proposes a storage medium storing an audio optimization program for a smart wearable device. When the audio optimization program for the smart wearable device is executed by a processor, it implements the steps of the audio optimization method for the smart wearable device as described above.

[0073] Since this storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.

[0074] Reference Figure 7 , Figure 7 This is a structural block diagram of the first embodiment of the audio optimization device for the smart wearable device of the present invention.

[0075] like Figure 7 As shown, the audio optimization device for a smart wearable device proposed in this embodiment of the invention includes: The acquisition module 10 is used to acquire driving data and head movement data.

[0076] The compensation module 20 is used to perform numerical compensation on the head movement data based on the driving data to obtain the target head movement data.

[0077] The calculation module 30 is used to calculate the head posture solution based on the target head motion data.

[0078] The optimization module 40 is used to perform sound field calculation based on the head posture solution and to optimize the sound field head movement based on the calculation results.

[0079] In one embodiment, the compensation module 20 is further configured to generate a target correction coefficient based on the vehicle acceleration, the road condition information, and the turning information; and to perform numerical compensation on the head motion data based on the target correction coefficient to obtain target head motion data.

[0080] In one embodiment, the compensation module 20 is further configured to determine target correction coefficients corresponding to the vehicle acceleration, the road condition information, and the turning information based on a preset mapping relationship. The preset mapping relationship includes: a first correction coefficient for the head motion data under different vehicle acceleration intervals, a second correction coefficient for the head motion data under different road condition information intervals, and a third correction coefficient for the head motion data under different turning information intervals. The target correction coefficient is the sum of the first correction coefficient, the second correction coefficient, and the third correction coefficient.

[0081] In one embodiment, the compensation module 20 is further configured to correct the forward acceleration according to the forward correction coefficient; correct the lateral acceleration according to the lateral correction coefficient; and correct the vertical acceleration according to the vertical correction coefficient.

[0082] In one embodiment, the calculation module 30 is further configured to acquire magnetometer data; correct the gyroscope data based on the magnetometer data and the acceleration data to obtain target gyroscope data; determine the quaternion corresponding to the target gyroscope data through a preset quaternion differential model; and generate Euler angles based on the quaternion through a preset transformation strategy.

[0083] In one embodiment, the calculation module 30 is further configured to decompose the target gyroscope data to obtain Euler angles, the Euler angles including pitch angle, roll angle and yaw angle; and determine the quaternions corresponding to the pitch angle, roll angle and yaw angle based on a preset transformation model.

[0084] In one embodiment, the acquisition module 10 is further configured to identify the scene in which the smart wearable device is located; when the scene is a vehicle-riding scene, establish a data transmission channel with the target vehicle; when the smart wearable device activates the head movement sound effect mode, acquire head movement data and receive driving data sent by the target vehicle through the data transmission channel.

[0085] This embodiment acquires driving data and head movement data, and performs numerical compensation on the head movement data based on the driving data to obtain compensated target head movement data. Then, it calculates the head posture solution based on the compensated target head movement data, thereby reducing the impact of driving on autonomous head movement. Finally, it performs sound field calculation on the head posture solution to achieve sound field head movement optimization, enabling audio and autonomous head movement tracking. This avoids the technical problem of poor audio playback effect of smart wearable devices in existing vehicle scenarios, and improves the audio playback effect.

[0086] It should be understood that although the steps in the flowcharts of this application's embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0087] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0088] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0089] In addition, for technical details not described in detail in this embodiment, please refer to the audio optimization method for smart wearable devices provided in any embodiment of the present invention, which will not be repeated here.

[0090] Furthermore, 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 system 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 system. 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 system that includes that element.

[0091] 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.

[0092] 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 read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0093] 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. An audio optimization method for a smart wearable device, characterized in that, The audio optimization method for the smart wearable device includes: Acquire driving data and head movement data, wherein the driving data includes driving acceleration, road condition information, and turning information; The target correction coefficients corresponding to the driving acceleration, the road condition information, and the turning information are determined based on a preset mapping relationship. The preset mapping relationship includes: a first correction coefficient for the head motion data under different driving acceleration intervals, a second correction coefficient for the head motion data under different road condition information intervals, and a third correction coefficient for the head motion data under different turning information intervals. The target correction coefficient is the sum of the first correction coefficient, the second correction coefficient, and the third correction coefficient. The head movement data is numerically compensated according to the target correction coefficient to obtain the target head movement data; Calculate the head posture solution based on the target head motion data; The sound field is calculated based on the head posture solution, and the sound field head movement is optimized based on the calculation results; The target correction coefficients are at least categorized as follows: forward correction coefficient, lateral correction coefficient, and vertical correction coefficient. The head motion data includes acceleration data, which includes forward acceleration, lateral acceleration, and vertical acceleration. The step of numerically compensating the head motion data according to the target correction coefficients includes: The forward acceleration is corrected according to the forward correction coefficient; The lateral acceleration is corrected according to the lateral correction coefficient; The vertical acceleration is corrected according to the vertical correction coefficient.

2. The audio optimization method for a smart wearable device as described in claim 1, characterized in that, The head motion data also includes: gyroscope data and magnetometer data; the head attitude solution includes: Euler angles and quaternions. The calculation of the head pose solution based on the target head motion data includes: Acquire magnetometer data; The gyroscope data is corrected based on the magnetometer data and the acceleration data to obtain the target gyroscope data; The quaternion corresponding to the target gyroscope data is determined by a preset quaternion differential model. Euler angles are generated based on the quaternion using a preset transformation strategy.

3. The audio optimization method for a smart wearable device as described in claim 2, characterized in that, The audio optimization method for the smart wearable device further includes: The target gyroscope data is split to obtain pitch angle, roll angle, and yaw angle; The quaternions corresponding to the pitch angle, roll angle, and heading angle are determined based on a preset conversion model.

4. The audio optimization method for a smart wearable device as described in any one of claims 1-3, characterized in that, The acquisition of driving data and head movement data includes: Identify the scene in which the smart wearable device is located; When the scenario is a passenger scenario, a data transmission channel is established between the vehicle and the target vehicle; When the smart wearable device activates the head-motion sound effect mode, it acquires head-motion data and receives driving data sent by the target vehicle through the data transmission channel.

5. An audio optimization device for a smart wearable device, characterized in that, The audio optimization device for the smart wearable device includes: The acquisition module is used to acquire driving data and head movement data, wherein the driving data includes driving acceleration, road condition information and turning information; The compensation module determines target correction coefficients corresponding to the vehicle acceleration, road condition information, and turning information based on a preset mapping relationship. The preset mapping relationship includes: a first correction coefficient for the head motion data under different vehicle acceleration intervals, a second correction coefficient for the head motion data under different road condition information intervals, and a third correction coefficient for the head motion data under different turning information intervals. The target correction coefficient is the sum of the first correction coefficient, the second correction coefficient, and the third correction coefficient. The head motion data is numerically compensated according to the target correction coefficient to obtain target head motion data. The calculation module is used to calculate the head posture solution based on the target head motion data; The optimization module is used to calculate the sound field based on the head posture solution and optimize the head movement of the sound field based on the calculation results. The target correction coefficients are at least classified as: forward correction coefficients, lateral correction coefficients, and vertical correction coefficients. The head motion data includes acceleration data, which includes forward acceleration, lateral acceleration, and vertical acceleration. The compensation module is also used for: The forward acceleration is corrected according to the forward correction coefficient; The lateral acceleration is corrected according to the lateral correction coefficient; The vertical acceleration is corrected according to the vertical correction coefficient.

6. An audio optimization device for a smart wearable device, characterized in that, The audio optimization device of the smart wearable device includes: a memory, a processor, and an audio optimization program of the smart wearable device stored in the memory and executable on the processor, wherein the audio optimization program of the smart wearable device is configured to implement the audio optimization method of the smart wearable device as described in any one of claims 1 to 4.

7. A storage medium, characterized in that, The storage medium stores an audio optimization program for a smart wearable device, which, when executed by a processor, implements the audio optimization method for a smart wearable device as described in any one of claims 1 to 4.

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