Compensation method and system for high-precision space sound scene of earphone

Abstract

The invention provides a compensation method and system for a high-precision space sound scene of an earphone, and is applied to the field of data processing. The preset microphone array is used for capturing the environment sound data in real time, dynamic EQ compensation is carried out according to the environment type, the intelligent earphone is helped to adapt to sound scenes in different environments, the tone quality stability and the environment adaptability are improved, meanwhile, the unique space sound scene of a user is constructed according to the music type and the frequency response, and the user experience is improved. In combination with dynamic EQ compensation, sound effect setting can be adjusted in real time according to the level and type of environmental noise, a user can obtain consistent music experience in different environments, immersion is enhanced, dynamic sound source positioning and sound field reconstruction are carried out based on a head related transmission function, and simulation volume is transmitted into ear canals, so that the user experience is improved. The head movement of the user is tracked in real time, audio rendering is adjusted, the omnibearing surround sound effect can be achieved, and more real and immersive music experience is provided for the user.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method and system for compensating high-precision spatial soundscape of headphones. Background Art

[0002] At present, smart headphones are usually equipped with multiple microphones to capture ambient sounds. These microphones are distributed in different positions of the headphones to form a microphone array in order to accurately obtain the direction and distance information of the ambient sound. However, the noise level and type in the environment are dynamically changing. When the headphones adapt to these changes in real time, it is difficult to maintain stable sound quality and spatial perception effects, and it is impossible to establish a spatial stereo sound field to bring users an immersive music experience. Summary of the invention

[0003] The present invention aims to solve the problem of how to maintain stable sound quality and spatial perception effect, establish a spatial stereo sound field to bring an immersive music experience to users, and provide a method and system for compensating high-precision spatial soundscape of headphones.

[0004] The present invention adopts the following technical means to solve the technical problem: The present invention provides a method for compensating high-precision spatial soundscape of headphones, comprising: Based on the pre-enabled sound effect function of the smart headset, a preset microphone array is used to capture the user's ambient sound data in real time, and the ambient sound information received by the smart headset is extracted; Determining whether the smart headset can establish a preset spatial soundscape; If not, then identify the environment type of the ambient sound information, apply a preset dynamic EQ to compensate for the ambient noise received by the smart headset, collect the type of music played by the smart headset in real time, dynamically adjust the frequency response according to the music type, and construct a unique spatial soundscape of the user according to the music type and the frequency response, wherein the dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low frequency or high frequency in a quiet environment; Determining whether the spatial soundscape matches a preset omnidirectional surround sound effect; If not, a preset head-related transfer function is constructed for the user, and dynamic sound source positioning and sound field reconstruction are performed through the smart headset in combination with the head-related transfer function. The preset simulated volume is transmitted to the user's ear canal from all directions, and the user's head movement is tracked in real time through the head-related transfer function. According to the head movement, the audio rendering of the smart headset is dynamically adjusted to make the sound position of the simulated volume consistent with the change of the head movement. According to the preset environmental noise parameters of the simulated volume, the playback volume and sound effect settings of the smart headset are dynamically adjusted, wherein the environmental noise parameters specifically include the environmental noise level and the environmental noise type.

[0005] Furthermore, the step of identifying the environment type of the ambient sound information includes: Based on the preset sampling rate of the smart headset, a preset noise reduction algorithm is applied to remove background noise in the ambient sound information to collect an audio signal; Determining whether the audio signal is within a preset amplitude range; If not, the audio signal is normalized, and a fast Fourier transform is performed on the audio signal to generate a spectrogram of the audio signal, and the energy distribution of each frequency component is displayed on the spectrogram. The time characteristics of the audio signal and the key features in the spectrogram are extracted, and the time characteristics and the key features are input into a pre-trained environmental classification model. According to the category label output by the environmental classification model, the environmental type of the ambient sound information is determined.

[0006] Furthermore, after the step of constructing the unique spatial soundscape of the user according to the music type and the frequency response, the method further includes: Playing a preset test signal from the smart headset and recording a frequency response curve output by the smart headset; Determining whether the frequency response curve meets a preset frequency band; If not, apply the preset head-related transfer function to perform a sound field positioning test, play the audio signal at a specific position, obtain the positioning accuracy of the smart headset output based on the audio signal, compare the positioning accuracy with the preset position, check the accuracy and stability of the audio signal, and use the preset signal generator and oscilloscope to measure the delay time of the audio signal from input to output of the smart headset.

[0007] Furthermore, the step of constructing a preset head-related transfer function for the user and performing dynamic sound source localization and sound field reconstruction through the smart headset in combination with the head-related transfer function includes: Using the built-in sensor of the smart headset to detect the movement information of the user's head in real time, perform preliminary filtering on the movement information, and dynamically adjust the audio position based on the movement information, wherein the built-in sensor specifically includes an accelerometer and a gyroscope; Determining whether the audio position matches the initial head direction of the user; If not, the smart headset is calibrated at zero point, the user's head rotation angle is calculated through the angular velocity data of the built-in sensor, and the cumulative error of the head rotation angle is corrected in combination with the preset magnetometer. According to the user's preset auricle characteristics and head characteristics, an audio filter corresponding to the audio position is established, and the virtual position of the sound source is dynamically adjusted according to the head rotation angle.

[0008] Furthermore, the step of determining whether the smart headset can establish a preset spatial sound scene also includes: Based on preset reflection conditions, a preset test sound source is applied to perform a reflection test on the smart headset to obtain at least two test results of the smart headset, wherein the reflection conditions specifically include arranging an anechoic chamber, a reverberation chamber, and using a reflective material, and the test results specifically include playing a test sound source in the anechoic chamber and capturing the headphone output with a measurement microphone, and playing a pulse signal in the reverberation chamber to measure the impulse response and reverberation time of the room; Determining whether the test result can generate a corresponding frequency response curve; If not, compare the sound pressure levels of the smart headset in different environments, optimize the internal design properties of the smart headset according to the sound pressure level, and apply a preset adaptive filter to perform reverberation suppression processing on the audio signal of the smart headset based on the reverberation characteristics of the smart headset to suppress the echo component of the audio signal, wherein the internal design properties specifically refer to the shape and material of the internal acoustic cavity of the headset.

[0009] Furthermore, the step of determining whether the spatial soundscape matches a preset omnidirectional surround sound effect further includes: Applying a preset interference sound source to perform a simulated interference test on the smart headset based on various interference test parameters to generate output audio of the smart headset, wherein the interference test parameters specifically include distance, angle arrangement and volume; Determining whether the output audio can achieve a preset spatial soundscape effect; If possible, activate the preset multi-sound source interference environment, play the preset interference audio through the smart headset respectively, and use the preset audio analyzer of the smart headset to collect audio properties in real time, wherein the audio properties specifically include frequency response, volume fluctuation and sound quality changes.

[0010] Furthermore, the step of using a preset microphone array to capture the user's ambient sound data in real time and extracting the ambient sound information received by the smart headset includes: Based on the preset spatial layout of the microphone array, beamforming is performed on the ambient sound data, and a preset positioning algorithm is applied to identify sound source attributes, wherein the sound source attributes specifically include a sound source direction and a sound source distance; Determining whether the sound source attribute matches a preset sound intensity change; If not, apply a preset envelope detection algorithm to extract the amplitude envelope of the ambient sound data, collect energy change parameters of the ambient sound data according to the amplitude envelope, extract characteristic information from the energy change parameters, and calculate the energy distribution parameters of the ambient sound data in different time periods based on the characteristic information, wherein the characteristic information specifically includes amplitude and waveform period.

[0011] The present invention also provides a headphone high-precision spatial soundscape compensation system, comprising: An extraction module, used to capture the user's ambient sound data in real time based on the sound effect function pre-enabled by the smart headset using a preset microphone array, and extract the ambient sound information received by the smart headset; A determination module, used to determine whether the smart headset can establish a preset spatial soundscape; an execution module, for, if not, identifying the environment type of the ambient sound information, applying a preset dynamic EQ to compensate for the ambient noise received by the smart headset, collecting the type of music played by the smart headset in real time, dynamically adjusting the frequency response according to the type of music, and constructing a unique spatial soundscape of the user according to the type of music and the frequency response, wherein the dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low frequency or high frequency in a quiet environment; A second judgment module is used to judge whether the spatial soundscape matches the preset omnidirectional surround sound effect; The second execution module is used to, if not, construct a preset head-related transfer function for the user, dynamically locate the sound source and reconstruct the sound field through the smart headset in combination with the head-related transfer function, apply a preset simulated volume to transmit to the user's ear canal from all directions, track the user's head movement in real time through the head-related transfer function, dynamically adjust the audio rendering of the smart headset according to the head movement, so that the sound position of the simulated volume remains consistent with the change of the head movement, and dynamically adjust the playback volume and sound effect settings of the smart headset according to the preset environmental noise parameters of the simulated volume, wherein the environmental noise parameters specifically include environmental noise level and environmental noise type.

[0012] Furthermore, the execution module also includes: A collection unit, configured to remove background noise from the ambient sound information by applying a preset noise reduction algorithm based on a preset sampling rate of the smart headset, and collect an audio signal; A judging unit, used to judge whether the audio signal is within a preset amplitude range; an execution unit, for, if not, normalizing the audio signal, performing fast Fourier transform on the audio signal, generating a spectrogram of the audio signal, displaying the energy distribution of each frequency component on the spectrogram, extracting the time features of the audio signal and the key features in the spectrogram, inputting the time features and the key features into a pre-trained environment classification model, and determining the environment type of the ambient sound information according to the category label output by the environment classification model.

[0013] Furthermore, it also includes: A recording module, used to play a preset test signal from the smart headset and record a frequency response curve output by the smart headset; A third judging module, used to judge whether the frequency response curve conforms to a preset frequency band; The third execution module is used to apply a preset head-related transfer function to perform a sound field positioning test if not, play an audio signal at a specific position, obtain the positioning accuracy of the smart headset output based on the audio signal, compare the positioning accuracy with the preset position, check the accuracy stability of the audio signal, and use a preset signal generator and oscilloscope to measure the delay time of the audio signal from input to output of the smart headset.

[0014] The present invention provides a method and system for compensating high-precision spatial soundscape of headphones, which has the following beneficial effects: The present invention uses a preset microphone array to capture environmental sound data in real time, and performs dynamic EQ compensation according to the environment type, which helps the smart headset adapt to the sound scenes in different environments, thereby improving the sound quality stability and environmental adaptability. At the same time, it constructs a user's unique spatial soundscape according to the music type and frequency response. Combined with dynamic EQ compensation, it can adjust the sound effect settings in real time according to the environmental noise level and type, so that users can obtain a consistent music experience in different environments and enhance the sense of immersion. It also performs dynamic sound source positioning and sound field reconstruction based on the head-related transfer function, combines the simulated volume transmitted into the ear canal, tracks the user's head movement in real time and adjusts the audio rendering, can achieve all-round surround sound, and provide users with a more realistic and immersive music experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for compensating high-precision spatial soundscape of headphones of the present invention; Figure 2 The structure block diagram of an embodiment of the high-precision spatial soundscape compensation system for headphones of the present invention. DETAILED DESCRIPTION

[0016] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. The implementation of the objectives, functional features and advantages of the present invention will be further described in conjunction with the embodiments and with reference to the accompanying drawings.

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Reference Figure 1 , is a method for compensating high-precision spatial soundscape of headphones in an embodiment of the present invention, comprising: S1: Based on the pre-enabled sound effect function of the smart headset, a preset microphone array is used to capture the user's ambient sound data in real time, and the ambient sound information received by the smart headset is extracted; S2: Determine whether the smart headset can establish a preset spatial sound scene; S3: If not, identifying the environment type of the ambient sound information, applying a preset dynamic EQ to compensate for the ambient noise received by the smart headset, collecting the type of music played by the smart headset in real time, dynamically adjusting the frequency response according to the music type, and constructing a unique spatial soundscape of the user according to the music type and the frequency response, wherein the dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low frequency or high frequency in a quiet environment; S4: Determine whether the spatial soundscape matches a preset omnidirectional surround sound effect; S5: If not, construct a preset head-related transfer function for the user, dynamically locate the sound source and reconstruct the sound field through the smart headset in combination with the head-related transfer function, apply a preset simulated volume to transmit it to the user's ear canal from all directions, track the user's head movement in real time through the head-related transfer function, dynamically adjust the audio rendering of the smart headset according to the head movement, so that the sound position of the simulated volume remains consistent with the change of the head movement, and dynamically adjust the playback volume and sound effect settings of the smart headset according to the preset environmental noise parameters of the simulated volume, wherein the environmental noise parameters specifically include environmental noise level and environmental noise type.

[0019] In this embodiment, based on the sound effect function pre-enabled by the user in the smart headset, the system uses a pre-set microphone array to capture the user's ambient sound data in real time, extracts the ambient sound information received by the smart headset, and then the system determines whether the smart headset can establish a pre-set spatial sound scene to execute the corresponding steps; for example, when the system determines that the smart headset can establish a pre-set spatial sound scene, the system will believe that the headset can provide the user's expected sound effects and spatial perception effects in the current environment. The system will continue to monitor the ambient sound data to ensure that the settings can be adjusted in time when the environment changes, and record the current sound effect configuration and environmental parameters for subsequent optimization. The system provides data support for the smart headset and personalized settings, and stores the current sound configuration, environmental parameters and user feedback data in the headset or supporting applications; for example, when the system determines that the smart headset cannot establish the preset spatial soundscape, the system will believe that the headset cannot provide the user's expected sound effects and spatial perception effects in the current environment. The system will identify the environmental type of the ambient sound information and apply the pre-set dynamic EQ to compensate for the ambient noise received by the smart headset. The dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low or high frequency in a quiet environment. It collects the type of music played by the smart headset in real time, dynamically adjusts the frequency response according to different music types, and adjusts the frequency response accordingly. The system builds a unique spatial soundscape for users based on the type of music and frequency response; the system can effectively suppress ambient noise by using dynamic EQ compensation, improve the user's listening experience in noisy environments, and enable the headphones to provide stable sound quality in various environments. At the same time, by dynamically adjusting the frequency response and building a unique spatial soundscape, the headphones can better meet the needs of different users and scenarios, allowing users to experience sound effects that are more in line with the characteristics of the music type, improve the expressiveness and immersion of the music, and have the ability to recognize and adapt to complex sound fields. Whether in a noisy public place or in a quiet room, the sound effects can be flexibly adjusted to ensure the best listening experience; the system then judges the spatial soundscape Whether the pre-set full-range surround sound effect can be achieved to execute the corresponding steps; for example, when the system determines that the spatial soundscape of the smart headset can match the pre-set full-range surround sound effect, the system will consider that the headset has successfully created the expected 3D sound experience in the current environment, and the user can enjoy an immersive auditory experience. The system will lock the current sound effect settings to avoid unnecessary adjustments, and allow the user to save the current sound effect settings as a custom mode for quick call in similar environments, and regularly perform hardware detection to ensure that key components such as microphone arrays and speakers are working properly, and remind users to clean the headset regularly to prevent dust and impurities from affecting the sound quality;For example, when the system determines that the spatial soundscape of the smart headset cannot match the pre-set omnidirectional surround sound effect, the system will believe that the user has not experienced the expected 3D sound effect and cannot enjoy an immersive auditory experience. The system will construct a pre-set head-related transfer function for the user, and use the smart headset to dynamically locate the sound source and reconstruct the sound field in combination with the head-related transfer function. The pre-set simulated volume is transmitted to the user's ear canal from all directions, and the user's head movement is tracked in real time through the head-related transfer function. The audio rendering of the smart headset is dynamically adjusted according to the head movement, so that the sound position of the simulated volume remains consistent with the head movement. The environmental noise parameters pre-set according to the simulated volume, which specifically include the environmental noise level and the environmental noise type, are used to dynamically adjust the smart headset. The system tracks the user's head movement in real time through the head-related transfer function, and dynamically adjusts the audio rendering according to the head movement, so that the sense of sound position changes with the head movement. This technology can maintain the spatial positioning of the sound effect when the user moves, further enhancing the sense of immersion. At the same time, according to the preset environmental noise parameters, the system can dynamically adjust the playback volume and sound effect settings of the smart headset to ensure that users can enjoy clear sound quality and good sound effects in different noise environments. According to the user's head-related transfer function and environmental noise parameters, the sound effects are dynamically adjusted to provide a personalized auditory experience, ensuring that each user can enjoy the best sound quality. Through dynamic audio rendering and real-time adjustment, the system can maintain the stability and consistency of the sound effects in different environments, improving user satisfaction. ;

[0020] It should be noted that the head-related transfer function (HRTF) is a function that describes the transfer characteristics of sound from a source through the head, auricle and torso to the ear canal. Since the shape of each person's head and auricle is different, HRTF is also personalized. Building a preset HRTF can help smart headphones reproduce accurate spatial sound effects in different environments. The specific example of building a head-related transfer function for users is as follows: Assume that a user is watching a VR movie with a smart headset. The scene in the movie includes sounds coming from different directions, such as birdsong in the front left, wind in the right, and footsteps in the back. So first of all, we need to measure HRTF. We use professional audio equipment to measure the HRTF of users in an anechoic room. We place sound sources in various directions around the user's head, play pulse signals, and use ear canal microphones to record response data. Then, we perform frequency domain analysis on the recorded data to obtain frequency responses in different directions to establish a user-specific HRTF database. Then, we use 3D scanning technology to obtain the precise shape of the user's head and auricle. Through simulation calculations, we apply the user's head and auricle shape information to the HRTF model, adjust the frequency response data, and finally integrate the personalized HRTF into the audio processing system of the smart headset. When the user watches a VR movie, the smart headset will adjust the sound direction in real time according to the user's head movement. For example, when the user turns his head to the left, the bird's chirping still comes from the left front, while the positions of other environmental sounds remain relatively unchanged, ensuring an immersive auditory experience. In summary, through personalized HRTF, the direction and distance of sound are more accurate, which enhances the user's sense of immersion. The system can adjust the audio rendering in real time according to the user's head movement, so that the sense of sound position changes with the head movement and remains consistent. Combined with the ambient noise parameters, the playback volume and sound effect settings are dynamically adjusted, so that users can still enjoy clear 3D sound effects even in noisy environments.

[0021] In this embodiment, the step S3 of identifying the environment type of the ambient sound information includes: S31: Based on the preset sampling rate of the smart headset, a preset noise reduction algorithm is applied to remove background noise in the ambient sound information to collect an audio signal; S32: Determine whether the audio signal is within a preset amplitude range; S33: If not, normalize the audio signal, perform fast Fourier transform on the audio signal, generate a spectrogram of the audio signal, display the energy distribution of each frequency component from the spectrogram, extract the time features of the audio signal and the key features in the spectrogram, input the time features and the key features into a pre-trained environmental classification model, and determine the environmental type of the ambient sound information according to the category label output by the environmental classification model.

[0022] In this embodiment, the system applies a preset noise reduction algorithm to remove background noise from ambient sound information based on a preset sampling rate of the smart headset to collect an audio signal, and then the system determines whether the audio signal is within a preset amplitude range to execute corresponding steps; for example, when the system determines that the audio signal is within a preset amplitude range, the system will consider that the signal quality is good, there is no obvious distortion or too strong / too weak, the background noise has been effectively removed, and the purity and availability of the signal are ensured. The system will regularly check the amplitude range of the audio signal to ensure that the signal is continuous and stable. At the same time, according to the user's auditory preferences and music types, the frequency response adjustment is refined to ensure that the audio performance is more in line with user expectations, and the playback volume is automatically adjusted according to the amplitude of the real-time audio signal and the user's hearing health needs to ensure comfort for long-term use; for example, when the system determines that the audio signal is not within the preset amplitude range, the system will consider that the background noise has not been removed, and the system will normalize the audio signal , perform fast Fourier transform on the audio signal to generate a spectrogram of the audio signal, display the energy distribution of each frequency component from the spectrogram, extract the time characteristics of the audio signal and the key features in the spectrogram, input these time characteristics and key features into the pre-trained environment classification model, and determine the environment type of the ambient sound information according to the category label output by the environment classification model; by generating a spectrogram through FFT, the system can accurately identify and analyze the energy distribution of each frequency component, so as to accurately distinguish between signals and noise, which helps to more effectively remove background noise and improve the clarity of the audio signal. At the same time, through the pre-trained environment classification model, the system can accurately determine the current ambient sound type according to the extracted time characteristics and key features, so that the system can adapt to different auditory environments more intelligently and provide sound optimization that is more in line with the characteristics of the environment. In addition, FFT and feature extraction can analyze the frequency components and time characteristics of the audio signal in detail, helping the system to better understand and process the audio signal and improve the accuracy of the sound quality and sound effects.

[0023] It should be added that a specific example of applying a preset noise reduction algorithm to remove background noise in the ambient sound information is as follows: Assume that the user is on the street, and the external microphone on the headset captures the surrounding car horns, pedestrians talking and wind sounds, and the internal microphone captures the residual noise in the ear. The smart headset will low-pass filter the captured noise signal, extract the main low-frequency noise, such as car engine sound and wind sound, extract the spectrum and phase information of the noise signal, analyze the frequency distribution and change characteristics of the noise, and generate an anti-phase signal with a phase opposite to the captured noise signal based on the analysis results; if the frequency of the noise signal is 100 Hz, a 100 Hz signal with an opposite phase is generated, and the anti-phase signal is superimposed on the music signal played by the headset. The anti-phase signal offsets the environmental noise while retaining the music signal. The smart headset monitors the changes in environmental noise in real time. For example, if the noise on the street suddenly increases, the headset perceives this change through the feedback system and enhances the noise reduction effect by adaptively adjusting the noise reduction parameters; for example, the anti-phase signal strength in the low-frequency band is increased to better offset the car engine sound.

[0024] It should be noted that the training process of the environment classification model is as follows: First, collect audio data from different environments, including "noisy streets", "coffee shop", "office", and "home". For each environment category, collect enough audio samples to ensure the diversity and representativeness of the samples. For example, "noisy streets" includes recordings from different time periods and locations. Then perform data preprocessing, divide the collected audio data into segments of fixed length, such as 2 seconds per segment, extract temporal features and spectral features from each audio segment, such as short-time energy, zero crossing rate, frequency peak, and spectral centroid, normalize the extracted features, and standardize the feature values ​​to between 0 and 1. Then select a machine learning model suitable for audio classification, such as convolutional neural network (CNN), recurrent neural network (RNN), or support vector machine (SVM), and perform model training. Label each audio segment with the corresponding environment category label, such as "noisy streets" and "coffee shop". Finally, input the feature data and corresponding labels of the audio segment into the model. Through repeated training, the model learns the correspondence between different environmental features and labels. Use an independent validation set to test the model performance to ensure that the model can accurately classify different environments. The specific process of outputting the category label is to first extract and normalize the features. In real-time applications, the time features and spectral features are extracted from the current environmental audio signal, and the extracted features are normalized to ensure that they are consistent with the features during training. Then, the normalized feature data is input into the pre-trained environmental classification model. The model calculates the output based on the input features through the forward propagation process. This output is usually a probability distribution, which indicates the probability that the audio clip belongs to each environmental category. According to the output probability distribution, the category with the highest probability is selected as the environmental label. For example, if the model outputs the highest probability of the "noisy street" category, the current environment is judged as a "noisy street"; The time feature and the key feature are input into the pre-trained environment classification model. A specific example of the category label output by the environment classification model is as follows: Assume that a user uses headphones on the street. The microphone in the headphones captures the ambient sound in real time. From the captured ambient sound, the system extracts time features (such as short-time energy and zero-crossing rate) and spectrum features (such as frequency peak and spectrum centroid), normalizes the extracted features, and inputs the normalized feature data into the pre-trained environment classification model. The model receives the feature input, processes it through the internal neural network layer, and calculates the probability of each environment category. For example, the model outputs the following probability distribution: Noisy streets: 0.85; Coffee shop: 0.10; Office: 0.03; At home: 0.02; Based on the above probability distribution, the model selects the category with the highest probability, "noisy streets", as the label of the current environment; after confirming that the current environment is "noisy streets", the system will adjust the sound effect settings, such as enhancing the human voice frequency band, applying a specific noise reduction algorithm, and suppressing low-frequency traffic noise and high-frequency background music noise.

[0025] In this embodiment, after step S3 of constructing the unique spatial soundscape of the user according to the music type and the frequency response, the method further includes: S301: Playing a preset test signal from the smart headset, and recording a frequency response curve output by the smart headset; S302: Determine whether the frequency response curve meets a preset frequency band; S303: If not, apply the preset head-related transfer function to perform a sound field positioning test, play an audio signal at a specific position, obtain the positioning accuracy of the smart headset output based on the audio signal, compare the positioning accuracy with the preset position, check the accuracy and stability of the audio signal, and use a preset signal generator and oscilloscope to measure the delay time of the audio signal from input to output of the smart headset.

[0026] In this embodiment, the system plays a preset test signal from the smart headset, records the frequency response curve of the smart headset output, and then the system determines whether the frequency response curve meets the preset frequency band to execute the corresponding steps; for example, when the system determines that the frequency response curve of the smart headset output can meet the preset frequency band, the system will consider that the smart headset can correctly reproduce the expected audio effect in the current environment, and the sound heard by the user is clear and high-quality. The system will record the current working state of the headset as normal, and continue to perform subsequent audio processing and playback tasks. At the same time, according to the type and content of the music played in real time, the equalizer settings are dynamically adjusted to ensure the optimal presentation of each frequency band of the music, and after confirming that the headset output meets the preset standards, the system will continue to monitor the frequency response and environmental changes of the headset to ensure the continuous provision of high-quality sound effects; for example, when the system determines that the frequency response curve of the smart headset output cannot meet the preset frequency band, the system If the system believes that the smart headset cannot reproduce the expected audio effect in the current environment, the system will apply a preset head-related transfer function to perform a sound field positioning test, play audio signals at specific locations, and obtain the positioning accuracy of the smart headset output based on these audio signals. The positioning accuracy is compared with the preset position to check the accuracy and stability of the audio signal, and finally a pre-set signal generator and oscilloscope are used to measure the delay time of the audio signal from input to smart headset to output. Through the sound field positioning test, the system can improve the performance of the headset in 3D sound effects and spatial audio, allowing users to experience more realistic and immersive sound effects. At the same time, by measuring the delay time of the audio signal from input to output, it ensures that the headset has low latency and high stability when transmitting audio signals, improves sound quality and user experience, and can automatically detect and diagnose audio reproduction problems, find and fix problems through specific test methods (such as HRTF testing and delay measurement), and ensure headset performance.

[0027] It should be noted that a specific example of applying a preset head-related transfer function to perform a sound field localization test is as follows: Suppose a specific device is used to measure a user's HRTF and generate its own HRTF data. If there is no user-specific HRTF data, the average HRTF data in the general HRTF database is used to generate sweep signals and pulse signals, covering the audio range from 20Hz to 20kHz. Then the test signal is played through the smart headset, and the signal is played in turn from four virtual positions: front, left, right and back. The audio signal played by the headset is recorded using the built-in microphone or an external measuring device. The recorded signal is combined with the HRTF data, and the positioning result of the headset output is calculated. The positioning result is compared with the preset sound source position, and the positioning error is calculated. If the front signal is positioned to the left, there may be a problem with the HRTF data or the headphone frequency response. Finally, according to the analysis results, the HRTF data or the audio processing parameters of the headset are adjusted and tested again. Through repeated testing and optimization, the accuracy of the sound field positioning of the headset is ensured, and the positioning error is within an acceptable range.

[0028] In this embodiment, a preset head-related transfer function is constructed for the user, and step S5 of performing dynamic sound source localization and sound field reconstruction through the smart headset in combination with the head-related transfer function includes: S51: using a built-in sensor of the smart headset to detect movement information of the user's head in real time, performing preliminary filtering processing on the movement information, and dynamically adjusting the audio position based on the movement information, wherein the built-in sensor specifically includes an accelerometer and a gyroscope; S52: Determine whether the audio position matches the initial head direction of the user; S53: If not, perform zero-point calibration on the smart headset, calculate the user's head rotation angle through the angular velocity data of the built-in sensor, correct the cumulative error of the head rotation angle in combination with the preset magnetometer, establish an audio filter corresponding to the audio position according to the user's preset auricle features and head features, and dynamically adjust the virtual position of the sound source according to the head rotation angle.

[0029] In this embodiment, the system uses the built-in sensors of the smart headset to detect the movement information of the user's head in real time, perform preliminary filtering on the movement information, dynamically adjust the audio position based on the movement information, and then the system determines whether the audio position is consistent with the user's initial head direction to execute the corresponding steps; for example, when the system determines that the audio position of the smart headset can match the user's initial head direction, the system will consider that the audio rendering and head tracking functions are normal, and the user can experience the expected 3D sound effects and immersive auditory experience. The system will confirm that the head tracking and audio rendering functions are normal, ensure that the audio position is consistent with the user's head movement, and record the current head position and audio rendering parameters as benchmark data for comparison and backtracking when problems arise, and continuously monitor the movement information of the user's head, dynamically adjust the audio rendering position, and ensure real-time consistency between the audio and the user's head direction; for example, when When the system determines that the audio position of the smart headset cannot match the user's initial head direction, the system will believe that the user cannot experience the expected 3D sound effects and immersive auditory experience. The system will perform zero-point calibration on the smart headset, calculate the user's head rotation angle through the angular velocity data of the built-in sensor, and use the pre-set magnetometer to correct the cumulative error of the head rotation angle. According to the user's pre-set auricle characteristics and head characteristics, an audio filter corresponding to the audio position is established, and the virtual position of the sound source is dynamically adjusted according to the head rotation angle. By performing zero-point calibration on the smart headset, the system can accurately calculate the head rotation angle, reduce errors, and ensure the accuracy of the audio position. At the same time, the virtual position of the sound source is dynamically adjusted to ensure that the audio position is synchronized with the user's head movement, thereby enhancing the immersiveness of the 3D sound effects. In addition, based on the user's auricle characteristics and head characteristics, an audio filter is established to provide personalized audio optimization and enhance the user experience.

[0030] It should be noted that the specific examples are as follows: Assuming that the user turns his head during the game, the system detects that the audio position is inconsistent with the head direction, performs zero-point calibration, and resets the initial direction. When the user continues to turn his head, the built-in sensor collects angular velocity data, and the system calculates the precise rotation angle of the head. After a long game time, the system uses magnetometer data to correct the accumulated error of the head rotation angle to ensure accurate sound positioning, and then establishes a personalized audio filter based on the user's auricle and head characteristics to optimize the game sound effects. When the user turns his head during the game, the system dynamically adjusts the virtual position of the sound source according to the rotation angle to ensure that the sound effect is consistent with the visual direction and enhance the sense of immersion. Through the above steps, the system can effectively improve the accuracy and immersion of 3D sound effects, because the zero-point calibration and magnetometer correction cumulative errors ensure accuracy and stability for long-term use, and dynamically adjust the virtual position of the sound source to be consistent with the direction of the user's head to improve the user's auditory experience. The application of personalized audio filters optimizes the sound effects according to user characteristics, further improving user satisfaction and immersive experience.

[0031] In this embodiment, the step S2 of determining whether the smart headset can establish a preset spatial sound scene further includes: S21: Based on a preset reflection condition, a preset test sound source is applied to perform a reflection test on the smart headset to obtain at least two test results of the smart headset, wherein the reflection condition specifically includes arranging an anechoic chamber, a reverberation chamber, and using a reflective material, and the test result specifically includes playing a test sound source in the anechoic chamber and capturing the headphone output with a measuring microphone, and playing a pulse signal in the reverberation chamber to measure the impulse response and reverberation time of the room; S22: Determine whether the test result can generate a corresponding frequency response curve; S23: If not, compare the sound pressure levels of the smart headset in different environments, optimize the internal design attributes of the smart headset according to the sound pressure levels, and apply a preset adaptive filter to perform reverberation suppression processing on the audio signal of the smart headset according to the reverberation characteristics of the smart headset to suppress the echo component of the audio signal, wherein the internal design attributes specifically refer to the shape and material of the internal acoustic cavity of the headset.

[0032] In this embodiment, the system is based on a pre-set reflection condition, which specifically includes arranging an anechoic chamber, a reverberation chamber, and using reflective materials, and applies a pre-set test sound source to perform a reflection test on the smart headset, and obtains at least two test results corresponding to the smart headset, and the test results specifically include playing the test sound source in the anechoic chamber and capturing the headphone output with a measuring microphone, and playing a pulse signal in the reverberation chamber to measure the impulse response and reverberation time of the room, and then the system determines whether these test results can generate corresponding frequency response curves to execute corresponding steps; for example, when the system determines that the test result output by the smart headset can generate a corresponding frequency response curve, the system will consider that the smart headset is The acoustic performance of headphones under different reflection conditions has a certain degree of stability and predictability. The system will conduct a detailed analysis of the generated frequency response curve, including observing the shape, amplitude and frequency range of the curve, which is helpful to evaluate the reflection characteristics of smart headphones in different environmental conditions such as anechoic chambers and reverberation chambers, as well as possible problems or advantages. At the same time, according to the analysis results of the reflection characteristics, the audio processing strategy of the smart headphones is adjusted, including adjusting the noise cancellation algorithm, equalizer settings or reverberation effects to optimize the audio output effect in different environments, and the generated frequency response curve and related analysis data are recorded for future reference. These data and results are very important for future optimization and Improvement work is very important; for example, when the system determines that the test results of the smart headset output cannot generate the corresponding frequency response curve, the system will think that the reflective acoustic performance of the smart headset is unstable and unpredictable. The system will compare the sound pressure levels of the smart headset in different environments, and optimize the internal design attributes of the smart headset according to different sound pressure levels. The internal design attributes are specifically the shape and material of the sound cavity inside the headset. According to the reverberation characteristics of the smart headset, a pre-set adaptive filter is used to perform reverberation suppression on the audio signal of the smart headset to suppress the echo component of the audio signal; the system compares the sound pressure levels of the smart headset in different environments, and optimizes the smart headset according to different sound pressure levels. The internal design properties of the headphones can improve the stability of smart headphones in different environments, helping to ensure that smart headphones can provide consistent audio performance in a variety of environments. At the same time, adjusting the shape and material of the internal acoustic cavity of the smart headphones can optimize their acoustic performance and improve the clarity and quality of the audio output, which helps to enhance the user's auditory experience and enable them to better enjoy music and other audio content. In addition, applying adaptive filters to suppress reverberation of the audio signals of the smart headphones helps to reduce echo components and improve audio clarity and audibility, allowing users to hear music and sounds more clearly when using smart headphones, reducing the interference of environmental noise on the audio experience.

[0033] In this embodiment, the step S4 of determining whether the spatial sound scene matches the preset omnidirectional surround sound effect further includes: S41: Applying a preset interference sound source to perform a simulated interference test on the smart headset based on various interference test parameters to generate output audio of the smart headset, wherein the interference test parameters specifically include distance, angle arrangement and volume; S42: Determine whether the output audio can achieve a preset spatial soundscape effect; S43: If yes, activate the preset multi-sound source interference environment, play the preset interference audios respectively through the smart headset, and use the preset audio analyzer of the smart headset to collect audio properties in real time, wherein the audio properties specifically include frequency response, volume fluctuation and sound quality change.

[0034] In this embodiment, the system applies a pre-set interference sound source to perform a simulated interference test on the smart headset based on various interference test parameters. The interference test parameters specifically include distance, angle arrangement and volume to generate output audio of the smart headset, and then the system determines whether the output audio can achieve the pre-set spatial soundscape effect to execute the corresponding steps; for example, when the system determines that the output audio cannot achieve the pre-set spatial soundscape effect, the system will believe that the current smart headset is unable to meet the expected spatial soundscape effect when facing different interference sound sources. The audio performance, the system will collect the results of the interference test, determine which interference parameters have caused the quality of the output audio to deteriorate, and compare the test results under different interference conditions. At the same time, according to the cause of the problem, the audio processing algorithm of the smart headset is optimized, including an enhanced noise reduction algorithm, an adaptive filtering algorithm and a spatial audio processing algorithm, to better cope with different interference conditions, and after the optimization, the simulated interference test is performed again to verify whether the improvement measures are effective, and multiple tests are performed to ensure that the smart headset can provide the expected spatial soundscape effect under different interference conditions; for example, when the system When it is determined that the output audio can achieve the preset spatial soundscape effect, the system will consider that the audio performance meets the expected spatial soundscape effect. The system will activate the preset multi-source interference environment, play the preset interference audio through the smart headphones, and use the pre-set audio analyzer of the smart headphones to collect audio properties in real time. The audio properties specifically include frequency response, volume fluctuation and sound quality changes. The system can verify the performance of the smart headphones in complex environments and ensure its robustness by testing in a multi-source interference environment. By dealing with a variety of interference conditions, the smart headphones can demonstrate their reliability and stability in actual usage scenarios. At the same time, by playing the pre-set interference audio and collecting audio properties in real time, the system can identify and analyze the impact of different interference conditions on audio performance, which helps to further optimize the audio processing algorithm of the smart headphones, so that they can better deal with interference in complex environments. In addition, real-time collection and analysis of audio properties can comprehensively evaluate the performance of the smart headphones. These data help to gain an in-depth understanding of the performance of the smart headphones under different conditions, and provide a basis for whether the subsequent spatial soundscape can match the preset all-round surround sound effect.

[0035] In this embodiment, a preset microphone array is used to capture the user's ambient sound data in real time, and step S1 of extracting the ambient sound information received by the smart headset includes: S11: Based on the preset spatial layout of the microphone array, beamforming is performed on the ambient sound data, and a preset positioning algorithm is applied to identify sound source attributes, wherein the sound source attributes specifically include a sound source direction and a sound source distance; S12: Determine whether the sound source attribute matches a preset sound intensity change; S13: If not, apply a preset envelope detection algorithm to extract the amplitude envelope of the ambient sound data, collect energy change parameters of the ambient sound data according to the amplitude envelope, extract characteristic information from the energy change parameters, and calculate the energy distribution parameters of the ambient sound data in different time periods based on the characteristic information, wherein the characteristic information specifically includes amplitude and waveform period.

[0036] In this embodiment, the system performs beamforming on the environmental sound data based on the pre-set spatial layout of the microphone array, and applies a pre-set positioning algorithm to identify the sound source attributes, which specifically include the sound source direction and the sound source distance. The system then determines whether these sound source attributes match the pre-set sound intensity changes to execute the corresponding steps; for example, when the system determines that the sound source attributes can match the pre-set sound intensity changes, the system will consider that the smart headset has successfully identified and located the sound source in the environment, and can accurately perceive the direction, distance and sound intensity changes of the sound source. The system will optimize the audio experience based on the matched sound source attributes, such as adjusting the volume of the headset, the equalizer settings or the spatial audio effects to ensure that the user can clearly hear and locate a specific sound source, providing a more realistic spatial sound effect. At the same time, if there are multiple sound sources in the environment, the system can apply dynamic EQ compensation to enhance the frequency band of the main sound source (such as human voice) and suppress other background noise to ensure that the user can focus on important sounds, and record the relevant data of the sound source attributes in the current environment for subsequent analysis and improvement, because the positioning algorithm and audio can be continuously optimized by analyzing these data. frequency processing strategy; for example, when the system determines that the sound source attribute cannot match the preset sound intensity change, the system will think that the smart headset has not identified and located the sound source in the environment, and the system will apply the preset envelope detection algorithm to extract the amplitude envelope of the ambient sound data, collect the energy change parameters of the ambient sound data according to the amplitude envelope, and extract feature information from these energy change parameters. The feature information specifically includes amplitude and waveform period, and the energy distribution parameters of the ambient sound data in different time periods are calculated based on these feature information; by extracting the amplitude envelope of the ambient sound data through the envelope detection algorithm, the system can more accurately capture and analyze the energy changes of the ambient sound, which helps to improve the accuracy of sound source identification, especially in complex noise environments. At the same time, based on feature information such as amplitude and waveform period, the system can analyze the ambient sound data more carefully. This refined sound feature analysis helps to better understand and distinguish different sound sources, and calculate the energy distribution parameters of the ambient sound data in different time periods. The system can dynamically adapt to changes in ambient sound, whether it is a sudden noise peak or continuous background noise, it can be effectively identified and processed, thereby improving the adaptability of the system.

[0037] It should be noted that the specific examples of applying the preset positioning algorithm to identify the sound source attributes are as follows: Suppose there is an intelligent headset system equipped with four microphones distributed at different positions of the headset, and the signals collected by the four microphones are S1(t), S2(t), S3(t) and S4(t) respectively; each signal is preprocessed, including filtering and noise reduction, to obtain the preprocessed signals S1′(t), S2′(t), S3′(t), and S4′(t); then a target direction is selected, the time difference of the sound waves reaching each microphone in this direction is calculated, and each signal is delayed corrected so that the sound waves from the target direction are aligned in time, and the aligned signals are weighted and combined to obtain the beamformed signal Sb(t); then Sb(t) is Fourier transformed to obtain the frequency domain signal Sb(f); by extracting feature information such as the main frequency components, the amplitude spectrum and phase spectrum of the signal, TDOA is used The method obtains the direction information of the sound source by calculating the time difference between S1′(t) and S2′(t); finally, the time difference of multiple microphone pairs is combined and the geometric triangulation method is used to calculate the precise position of the sound source. According to the calculated time difference and geometric relationship, the azimuth and elevation of the sound source are determined, and the distance of the sound source is estimated.

[0038] It should be added that a specific example of applying a preset envelope detection algorithm to extract the amplitude envelope of the ambient sound data is as follows: Suppose we have a piece of environmental sound data x(t), which contains the sound of a person talking in a quiet room. First, we need to perform signal preprocessing. Preprocess x(t) to filter out high-frequency noise and low-frequency interference to obtain the preprocessed signal x′(t). Then calculate the absolute value of x′(t) to obtain |x′(t)|, whose waveform contains the instantaneous amplitude information of the signal. Assume a Butterworth filter with a cutoff frequency of 20 Hz. Perform a low-pass filter on |x′(t)| to obtain the smoothed signal y(t). Then select Hilbert transform as the envelope detection algorithm, calculate the Hilbert transform of x′(t), and obtain the analytical signal z(t). The real part of the analytical signal z(t) is x′(t), and the imaginary part is the signal after the Hilbert transform. Calculate the modulus of z(t), that is, the formula is as follows: ; Finally, features are extracted from the envelope signal, and the features are as follows: Maximum amplitude: Average Amplitude: Rate of change: ; The envelope signal (t) is obtained through the above steps, and the maximum amplitude is 0.8, the average amplitude is 0.3, and the rate of change is 0.05 at a certain moment. These feature information can be used for further analysis, such as determining whether the sound data belongs to speaking sound in environmental classification, or for identifying and enhancing the human voice part in noise reduction processing; by extracting the amplitude envelope of environmental sound data through the envelope detection algorithm, the system can better understand the macroscopic changes of the signal, thereby providing useful information in applications such as noise suppression, sound source localization and environmental perception, and improving the audio processing performance and user experience of smart headphones.

[0039] Reference Figure 2 , a high-precision spatial soundscape compensation system for headphones in one embodiment of the present invention, comprising: An extraction module 10 is used to capture the user's ambient sound data in real time based on the sound effect function pre-enabled by the smart headset using a preset microphone array, and extract the ambient sound information received by the smart headset; A determination module 20, configured to determine whether the smart headset can establish a preset spatial soundscape; The execution module 30 is used to, if not, identify the environment type of the ambient sound information, apply a preset dynamic EQ to compensate for the ambient noise received by the smart headset, collect the type of music played by the smart headset in real time, dynamically adjust the frequency response according to the music type, and construct a unique spatial soundscape of the user according to the music type and the frequency response, wherein the dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low frequency or high frequency in a quiet environment; A second judgment module 40 is used to judge whether the spatial soundscape matches a preset omnidirectional surround sound effect; The second execution module 50 is used to, if not, construct a preset head-related transfer function for the user, dynamically locate the sound source and reconstruct the sound field through the smart headset in combination with the head-related transfer function, apply a preset simulated volume to be transmitted to the ear canal of the user from all directions, track the head movement of the user in real time through the head-related transfer function, dynamically adjust the audio rendering of the smart headset according to the head movement, so that the sound position of the simulated volume remains consistent with the change of the head movement, and dynamically adjust the playback volume and sound effect settings of the smart headset according to the preset environmental noise parameters of the simulated volume, wherein the environmental noise parameters specifically include environmental noise level and environmental noise type.

[0040] In this embodiment, the extraction module 10 uses a pre-set microphone array to capture the user's ambient sound data in real time based on the sound effect function pre-enabled by the user in the smart headset, and extracts the ambient sound information received by the smart headset. The judgment module 20 then judges whether the smart headset can establish a pre-set spatial sound scene to execute the corresponding steps; for example, when the system determines that the smart headset can establish a pre-set spatial sound scene, the system will believe that the headset can provide the user's expected sound effects and spatial perception effects in the current environment. The system will continue to monitor the ambient sound data to ensure that the settings can be adjusted in time when the environment changes, and record the current sound effect configuration and environmental parameters for later use. The system provides data support for continuous optimization and personalized settings, and stores the current sound effect configuration, environmental parameters and user feedback data in the headphones or supporting applications; for example, when the system determines that the smart headphones cannot establish the preset spatial soundscape, the execution module 30 will consider that the headphones cannot provide the user's expected sound effects and spatial perception effects in the current environment. The system will identify the environmental type of the ambient sound information and apply a pre-set dynamic EQ to compensate for the ambient noise received by the smart headphones. The dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low or high frequency in a quiet environment, collecting the type of music played by the smart headphones in real time, and dynamically adjusting the frequency response according to different music types. The system can effectively suppress ambient noise by using dynamic EQ compensation, improve the user's listening experience in a noisy environment, and enable the headphones to provide stable sound quality in various environments. At the same time, by dynamically adjusting the frequency response and building a unique spatial soundscape, the headphones can better meet the needs of different users and scenarios, allowing users to experience sound effects that are more in line with the characteristics of the music type, improve the expressiveness and immersion of the music, and recognize and adapt to the ability of complex sound fields. Whether in a noisy public place or in a quiet room, the sound effects can be flexibly adjusted to ensure the best listening experience; then the second judgment module 40 judges Whether the spatial soundscape can achieve the pre-set full-range surround sound effect, so as to execute the corresponding steps; for example, when the system determines that the spatial soundscape of the smart headset can match the pre-set full-range surround sound effect, the system will consider that the headset has successfully created the expected 3D sound experience in the current environment, and the user can enjoy an immersive auditory experience. The system will lock the current sound effect settings to avoid unnecessary adjustments, and allow the user to save the current sound effect settings as a custom mode for quick call in a similar environment, and regularly perform hardware detection to ensure that key components such as microphone arrays and speakers are working properly, and remind users to clean the headset regularly to prevent dust and impurities from affecting the sound quality;For example, when the system determines that the spatial soundscape of the smart headset cannot match the pre-set omnidirectional surround sound effect, the second execution module 50 will think that the user has not experienced the expected 3D sound effect and cannot enjoy an immersive auditory experience. The system will construct a pre-set head-related transfer function for the user, and dynamically locate the sound source and reconstruct the sound field through the smart headset in combination with the head-related transfer function. The pre-set simulated volume is transmitted to the user's ear canal from all directions, and the user's head movement is tracked in real time through the head-related transfer function. The audio rendering of the smart headset is dynamically adjusted according to the head movement, so that the sound position of the simulated volume remains consistent with the head movement. The environmental noise parameters pre-set according to the simulated volume, which specifically include the environmental noise level and the environmental noise type, are dynamically adjusted. Smart headset playback volume and sound effect settings; The system tracks the user's head movement in real time through the head-related transfer function, and dynamically adjusts the audio rendering according to the head movement, so that the sense of sound position changes with the head movement. This technology can maintain the spatial positioning of the sound effect when the user moves, further enhancing the sense of immersion. At the same time, according to the preset environmental noise parameters, the system can dynamically adjust the playback volume and sound effect settings of the smart headset to ensure that users can enjoy clear sound quality and good sound effects in different noise environments. And according to the user's head-related transfer function and environmental noise parameters, the sound effect is dynamically adjusted to provide a personalized auditory experience, ensuring that each user can enjoy the best sound quality. Through dynamic audio rendering and real-time adjustment, the system can maintain the stability and consistency of the sound effect in different environments, improving user satisfaction. ;

[0041] In this embodiment, the execution module further includes: A collection unit, configured to remove background noise from the ambient sound information by applying a preset noise reduction algorithm based on a preset sampling rate of the smart headset, and collect an audio signal; A judging unit, used to judge whether the audio signal is within a preset amplitude range; an execution unit, for, if not, normalizing the audio signal, performing fast Fourier transform on the audio signal, generating a spectrogram of the audio signal, displaying the energy distribution of each frequency component on the spectrogram, extracting the time features of the audio signal and the key features in the spectrogram, inputting the time features and the key features into a pre-trained environment classification model, and determining the environment type of the ambient sound information according to the category label output by the environment classification model.

[0042] In this embodiment, the system applies a preset noise reduction algorithm to remove background noise from ambient sound information based on a preset sampling rate of the smart headset to collect an audio signal, and then the system determines whether the audio signal is within a preset amplitude range to execute corresponding steps; for example, when the system determines that the audio signal is within a preset amplitude range, the system will consider that the signal quality is good, there is no obvious distortion or too strong / too weak, the background noise has been effectively removed, and the purity and availability of the signal are ensured. The system will regularly check the amplitude range of the audio signal to ensure that the signal is continuous and stable. At the same time, according to the user's auditory preferences and music types, the frequency response adjustment is refined to ensure that the audio performance is more in line with user expectations, and the playback volume is automatically adjusted according to the amplitude of the real-time audio signal and the user's hearing health needs to ensure comfort for long-term use; for example, when the system determines that the audio signal is not within the preset amplitude range, the system will consider that the background noise has not been removed, and the system will normalize the audio signal , perform fast Fourier transform on the audio signal to generate a spectrogram of the audio signal, display the energy distribution of each frequency component from the spectrogram, extract the time characteristics of the audio signal and the key features in the spectrogram, input these time characteristics and key features into the pre-trained environment classification model, and determine the environment type of the ambient sound information according to the category label output by the environment classification model; by generating a spectrogram through FFT, the system can accurately identify and analyze the energy distribution of each frequency component, so as to accurately distinguish between signals and noise, which helps to more effectively remove background noise and improve the clarity of the audio signal. At the same time, through the pre-trained environment classification model, the system can accurately determine the current ambient sound type according to the extracted time characteristics and key features, so that the system can adapt to different auditory environments more intelligently and provide sound optimization that is more in line with the characteristics of the environment. In addition, FFT and feature extraction can analyze the frequency components and time characteristics of the audio signal in detail, helping the system to better understand and process the audio signal and improve the accuracy of the sound quality and sound effects.

[0043] In this embodiment, it also includes: A recording module, used to play a preset test signal from the smart headset and record a frequency response curve output by the smart headset; A third judging module, used to judge whether the frequency response curve conforms to a preset frequency band; The third execution module is used to apply a preset head-related transfer function to perform a sound field positioning test if not, play an audio signal at a specific position, obtain the positioning accuracy of the smart headset output based on the audio signal, compare the positioning accuracy with the preset position, check the accuracy stability of the audio signal, and use a preset signal generator and oscilloscope to measure the delay time of the audio signal from input to output of the smart headset.

[0044] In this embodiment, the system plays a preset test signal from the smart headset, records the frequency response curve of the smart headset output, and then the system determines whether the frequency response curve meets the preset frequency band to execute the corresponding steps; for example, when the system determines that the frequency response curve of the smart headset output can meet the preset frequency band, the system will consider that the smart headset can correctly reproduce the expected audio effect in the current environment, and the sound heard by the user is clear and high-quality. The system will record the current working state of the headset as normal, and continue to perform subsequent audio processing and playback tasks. At the same time, according to the type and content of the music played in real time, the equalizer settings are dynamically adjusted to ensure the optimal presentation of each frequency band of the music, and after confirming that the headset output meets the preset standards, the system will continue to monitor the frequency response and environmental changes of the headset to ensure the continuous provision of high-quality sound effects; for example, when the system determines that the frequency response curve of the smart headset output cannot meet the preset frequency band, the system If the system believes that the smart headset cannot reproduce the expected audio effect in the current environment, the system will apply a preset head-related transfer function to perform a sound field positioning test, play audio signals at specific locations, and obtain the positioning accuracy of the smart headset output based on these audio signals. The positioning accuracy is compared with the preset position to check the accuracy and stability of the audio signal, and finally a pre-set signal generator and oscilloscope are used to measure the delay time of the audio signal from input to smart headset to output. Through the sound field positioning test, the system can improve the performance of the headset in 3D sound effects and spatial audio, allowing users to experience more realistic and immersive sound effects. At the same time, by measuring the delay time of the audio signal from input to output, it ensures that the headset has low latency and high stability when transmitting audio signals, improves sound quality and user experience, and can automatically detect and diagnose audio reproduction problems, find and fix problems through specific test methods (such as HRTF testing and delay measurement), and ensure headset performance.

[0045] In this embodiment, the second execution module further includes: A detection unit, configured to use a built-in sensor of the smart headset to detect movement information of the user's head in real time, perform preliminary filtering on the movement information, and dynamically adjust the audio position based on the movement information, wherein the built-in sensor specifically includes an accelerometer and a gyroscope; A second determination unit, configured to determine whether the audio position matches an initial head direction of the user; The second execution unit is used to perform zero-point calibration on the smart headset if not, calculate the user's head rotation angle through the angular velocity data of the built-in sensor, correct the cumulative error of the head rotation angle in combination with the preset magnetometer, establish an audio filter corresponding to the audio position according to the user's preset auricle features and head features, and dynamically adjust the virtual position of the sound source according to the head rotation angle.

[0046] In this embodiment, the system uses the built-in sensors of the smart headset to detect the movement information of the user's head in real time, perform preliminary filtering on the movement information, dynamically adjust the audio position based on the movement information, and then the system determines whether the audio position is consistent with the user's initial head direction to execute the corresponding steps; for example, when the system determines that the audio position of the smart headset can match the user's initial head direction, the system will consider that the audio rendering and head tracking functions are normal, and the user can experience the expected 3D sound effects and immersive auditory experience. The system will confirm that the head tracking and audio rendering functions are normal, ensure that the audio position is consistent with the user's head movement, and record the current head position and audio rendering parameters as benchmark data for comparison and backtracking when problems arise, and continuously monitor the movement information of the user's head, dynamically adjust the audio rendering position, and ensure real-time consistency between the audio and the user's head direction; for example, when When the system determines that the audio position of the smart headset cannot match the user's initial head direction, the system will believe that the user cannot experience the expected 3D sound effects and immersive auditory experience. The system will perform zero-point calibration on the smart headset, calculate the user's head rotation angle through the angular velocity data of the built-in sensor, and use the pre-set magnetometer to correct the cumulative error of the head rotation angle. According to the user's pre-set auricle characteristics and head characteristics, an audio filter corresponding to the audio position is established, and the virtual position of the sound source is dynamically adjusted according to the head rotation angle. By performing zero-point calibration on the smart headset, the system can accurately calculate the head rotation angle, reduce errors, and ensure the accuracy of the audio position. At the same time, the virtual position of the sound source is dynamically adjusted to ensure that the audio position is synchronized with the user's head movement, thereby enhancing the immersiveness of the 3D sound effects. In addition, based on the user's auricle characteristics and head characteristics, an audio filter is established to provide personalized audio optimization and enhance the user experience.

[0047] In this embodiment, the judgment module further includes: an acquisition unit, configured to perform a reflection test on the smart headset based on a preset reflection condition and a preset test sound source, and obtain at least two test results of the smart headset, wherein the reflection condition specifically includes arranging an anechoic chamber, a reverberation chamber, and using a reflective material, and the test result specifically includes playing a test sound source in the anechoic chamber and capturing the headphone output with a measuring microphone, and playing a pulse signal in the reverberation chamber to measure the impulse response and reverberation time of the room; A third judging unit, used to judge whether the test result can generate a corresponding frequency response curve; The third execution unit is used to compare the sound pressure levels of the smart headset in different environments if it is not possible, optimize the internal design properties of the smart headset according to the sound pressure level, and apply a preset adaptive filter to perform reverberation suppression processing on the audio signal of the smart headset according to the reverberation characteristics of the smart headset, so as to suppress the echo component of the audio signal, wherein the internal design property is specifically the shape and material of the internal sound cavity of the headset.

[0048] In this embodiment, the system is based on a pre-set reflection condition, which specifically includes arranging an anechoic chamber, a reverberation chamber, and using reflective materials, and applies a pre-set test sound source to perform a reflection test on the smart headset, and obtains at least two test results corresponding to the smart headset, and the test results specifically include playing the test sound source in the anechoic chamber and capturing the headphone output with a measuring microphone, and playing a pulse signal in the reverberation chamber to measure the impulse response and reverberation time of the room, and then the system determines whether these test results can generate corresponding frequency response curves to execute corresponding steps; for example, when the system determines that the test result output by the smart headset can generate a corresponding frequency response curve, the system will consider that the smart headset is The acoustic performance of headphones under different reflection conditions has a certain degree of stability and predictability. The system will conduct a detailed analysis of the generated frequency response curve, including observing the shape, amplitude and frequency range of the curve, which is helpful to evaluate the reflection characteristics of smart headphones in different environmental conditions such as anechoic chambers and reverberation chambers, as well as possible problems or advantages. At the same time, according to the analysis results of the reflection characteristics, the audio processing strategy of the smart headphones is adjusted, including adjusting the noise cancellation algorithm, equalizer settings or reverberation effects to optimize the audio output effect in different environments, and the generated frequency response curve and related analysis data are recorded for future reference. These data and results are very important for future optimization and Improvement work is very important; for example, when the system determines that the test results of the smart headset output cannot generate the corresponding frequency response curve, the system will think that the reflective acoustic performance of the smart headset is unstable and unpredictable. The system will compare the sound pressure levels of the smart headset in different environments, and optimize the internal design attributes of the smart headset according to different sound pressure levels. The internal design attributes are specifically the shape and material of the sound cavity inside the headset. According to the reverberation characteristics of the smart headset, a pre-set adaptive filter is used to perform reverberation suppression on the audio signal of the smart headset to suppress the echo component of the audio signal; the system compares the sound pressure levels of the smart headset in different environments, and optimizes the smart headset according to different sound pressure levels. The internal design properties of the headphones can improve the stability of smart headphones in different environments, helping to ensure that smart headphones can provide consistent audio performance in a variety of environments. At the same time, adjusting the shape and material of the internal acoustic cavity of the smart headphones can optimize their acoustic performance and improve the clarity and quality of the audio output, which helps to enhance the user's auditory experience and enable them to better enjoy music and other audio content. In addition, applying adaptive filters to suppress reverberation of the audio signals of the smart headphones helps to reduce echo components and improve audio clarity and audibility, allowing users to hear music and sounds more clearly when using smart headphones, reducing the interference of environmental noise on the audio experience.

[0049] In this embodiment, the second determination module further includes: A generating unit, configured to apply a preset interference sound source to perform a simulated interference test on the smart headset based on various interference test parameters, and generate output audio of the smart headset, wherein the interference test parameters specifically include distance, angle arrangement, and volume; A fourth determination unit, configured to determine whether the output audio can achieve a preset spatial soundscape effect; The fourth execution unit is used to activate the preset multi-sound source interference environment if possible, play the preset interference audio through the smart headset respectively, and use the preset audio analyzer of the smart headset to collect audio properties in real time, wherein the audio properties specifically include frequency response, volume fluctuation and sound quality change.

[0050] In this embodiment, the system applies a pre-set interference sound source to perform a simulated interference test on the smart headset based on various interference test parameters. The interference test parameters specifically include distance, angle arrangement and volume to generate output audio of the smart headset, and then the system determines whether the output audio can achieve the pre-set spatial soundscape effect to execute the corresponding steps; for example, when the system determines that the output audio cannot achieve the pre-set spatial soundscape effect, the system will believe that the current smart headset is unable to meet the expected spatial soundscape effect when facing different interference sound sources. The audio performance, the system will collect the results of the interference test, determine which interference parameters have caused the quality of the output audio to deteriorate, and compare the test results under different interference conditions. At the same time, according to the cause of the problem, the audio processing algorithm of the smart headset is optimized, including an enhanced noise reduction algorithm, an adaptive filtering algorithm and a spatial audio processing algorithm, to better cope with different interference conditions, and after the optimization, the simulated interference test is performed again to verify whether the improvement measures are effective, and multiple tests are performed to ensure that the smart headset can provide the expected spatial soundscape effect under different interference conditions; for example, when the system When it is determined that the output audio can achieve the preset spatial soundscape effect, the system will consider that the audio performance meets the expected spatial soundscape effect. The system will activate the preset multi-source interference environment, play the preset interference audio through the smart headphones, and use the pre-set audio analyzer of the smart headphones to collect audio properties in real time. The audio properties specifically include frequency response, volume fluctuation and sound quality changes. The system can verify the performance of the smart headphones in complex environments and ensure its robustness by testing in a multi-source interference environment. By dealing with a variety of interference conditions, the smart headphones can demonstrate their reliability and stability in actual usage scenarios. At the same time, by playing the pre-set interference audio and collecting audio properties in real time, the system can identify and analyze the impact of different interference conditions on audio performance, which helps to further optimize the audio processing algorithm of the smart headphones, so that they can better deal with interference in complex environments. In addition, real-time collection and analysis of audio properties can comprehensively evaluate the performance of the smart headphones. These data help to gain an in-depth understanding of the performance of the smart headphones under different conditions, and provide a basis for whether the subsequent spatial soundscape can match the preset all-round surround sound effect.

[0051] In this embodiment, the extraction module further includes: an identification unit, configured to perform beamforming on the ambient sound data based on a preset spatial layout of the microphone array, and apply a preset positioning algorithm to identify sound source attributes, wherein the sound source attributes specifically include a sound source direction and a sound source distance; A fifth judgment unit, used to judge whether the sound source attribute matches a preset sound intensity change; The fifth execution unit is used to, if not, apply a preset envelope detection algorithm to extract the amplitude envelope of the ambient sound data, collect energy change parameters of the ambient sound data according to the amplitude envelope, extract characteristic information from the energy change parameters, and calculate the energy distribution parameters of the ambient sound data in different time periods based on the characteristic information, wherein the characteristic information specifically includes amplitude and waveform period.

[0052] In this embodiment, the system performs beamforming on the environmental sound data based on the pre-set spatial layout of the microphone array, and applies a pre-set positioning algorithm to identify the sound source attributes, which specifically include the sound source direction and the sound source distance. The system then determines whether these sound source attributes match the pre-set sound intensity changes to execute the corresponding steps; for example, when the system determines that the sound source attributes can match the pre-set sound intensity changes, the system will consider that the smart headset has successfully identified and located the sound source in the environment, and can accurately perceive the direction, distance and sound intensity changes of the sound source. The system will optimize the audio experience based on the matched sound source attributes, such as adjusting the volume of the headset, the equalizer settings or the spatial audio effects to ensure that the user can clearly hear and locate a specific sound source, providing a more realistic spatial sound effect. At the same time, if there are multiple sound sources in the environment, the system can apply dynamic EQ compensation to enhance the frequency band of the main sound source (such as human voice) and suppress other background noise to ensure that the user can focus on important sounds, and record the relevant data of the sound source attributes in the current environment for subsequent analysis and improvement, because the positioning algorithm and audio can be continuously optimized by analyzing these data. frequency processing strategy; for example, when the system determines that the sound source attribute cannot match the preset sound intensity change, the system will think that the smart headset has not identified and located the sound source in the environment, and the system will apply the preset envelope detection algorithm to extract the amplitude envelope of the ambient sound data, collect the energy change parameters of the ambient sound data according to the amplitude envelope, and extract feature information from these energy change parameters. The feature information specifically includes amplitude and waveform period, and the energy distribution parameters of the ambient sound data in different time periods are calculated based on these feature information; by extracting the amplitude envelope of the ambient sound data through the envelope detection algorithm, the system can more accurately capture and analyze the energy changes of the ambient sound, which helps to improve the accuracy of sound source identification, especially in complex noise environments. At the same time, based on feature information such as amplitude and waveform period, the system can analyze the ambient sound data more carefully. This refined sound feature analysis helps to better understand and distinguish different sound sources, and calculate the energy distribution parameters of the ambient sound data in different time periods. The system can dynamically adapt to changes in ambient sound, whether it is a sudden noise peak or continuous background noise, it can be effectively identified and processed, thereby improving the adaptability of the system.

[0053] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for compensating high-precision spatial soundscape of headphones, characterized in that: The following steps are involved: Based on the pre-enabled sound effect function of the smart headset, a preset microphone array is used to capture the user's ambient sound data in real time, and the ambient sound information received by the smart headset is extracted; Determining whether the smart headset can establish a preset spatial soundscape; If not, then identify the environment type of the ambient sound information, apply a preset dynamic EQ to compensate for the ambient noise received by the smart headset, collect the type of music played by the smart headset in real time, dynamically adjust the frequency response according to the music type, and construct a unique spatial soundscape of the user according to the music type and the frequency response, wherein the dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low frequency or high frequency in a quiet environment; Determining whether the spatial soundscape matches a preset omnidirectional surround sound effect; If not, a preset head-related transfer function is constructed for the user, and dynamic sound source positioning and sound field reconstruction are performed through the smart headset in combination with the head-related transfer function. The preset simulated volume is transmitted to the user's ear canal from all directions, and the user's head movement is tracked in real time through the head-related transfer function. According to the head movement, the audio rendering of the smart headset is dynamically adjusted to make the sound position of the simulated volume consistent with the change of the head movement. According to the preset environmental noise parameters of the simulated volume, the playback volume and sound effect settings of the smart headset are dynamically adjusted, wherein the environmental noise parameters specifically include the environmental noise level and the environmental noise type.

2. The method for compensating high-precision spatial soundscape of headphones according to claim 1, characterized in that: The step of identifying the environment type of the ambient sound information includes: Based on the preset sampling rate of the smart headset, a preset noise reduction algorithm is applied to remove background noise in the ambient sound information to collect an audio signal; Determining whether the audio signal is within a preset amplitude range; If not, the audio signal is normalized, and a fast Fourier transform is performed on the audio signal to generate a spectrogram of the audio signal, and the energy distribution of each frequency component is displayed on the spectrogram. The time characteristics of the audio signal and the key features in the spectrogram are extracted, and the time characteristics and the key features are input into a pre-trained environmental classification model. According to the category label output by the environmental classification model, the environmental type of the ambient sound information is determined.

3. The method for compensating high-precision spatial soundscape of headphones according to claim 1, characterized in that: After the step of constructing the user's unique spatial soundscape based on the music type and the frequency response, the method further includes: Playing a preset test signal from the smart headset and recording a frequency response curve output by the smart headset; Determining whether the frequency response curve meets a preset frequency band; If not, apply the preset head-related transfer function to perform a sound field positioning test, play the audio signal at a specific position, obtain the positioning accuracy of the smart headset output based on the audio signal, compare the positioning accuracy with the preset position, check the accuracy and stability of the audio signal, and use the preset signal generator and oscilloscope to measure the delay time of the audio signal from input to output of the smart headset.

4. The method for compensating high-precision spatial soundscape of headphones according to claim 1, characterized in that: The step of constructing a preset head-related transfer function for the user, and performing dynamic sound source localization and sound field reconstruction through the smart headset in combination with the head-related transfer function includes: Using the built-in sensor of the smart headset to detect the movement information of the user's head in real time, perform preliminary filtering on the movement information, and dynamically adjust the audio position based on the movement information, wherein the built-in sensor specifically includes an accelerometer and a gyroscope; Determining whether the audio position matches the initial head direction of the user; If not, the smart headset is calibrated at zero point, the user's head rotation angle is calculated through the angular velocity data of the built-in sensor, and the cumulative error of the head rotation angle is corrected in combination with the preset magnetometer. According to the user's preset auricle characteristics and head characteristics, an audio filter corresponding to the audio position is established, and the virtual position of the sound source is dynamically adjusted according to the head rotation angle.

5. The method for compensating high-precision spatial soundscape of headphones according to claim 1, characterized in that: The step of determining whether the smart headset can establish a preset spatial sound scene also includes: Based on preset reflection conditions, a preset test sound source is applied to perform a reflection test on the smart headset to obtain at least two test results of the smart headset, wherein the reflection conditions specifically include arranging an anechoic chamber, a reverberation chamber, and using a reflective material, and the test results specifically include playing a test sound source in the anechoic chamber and capturing the headphone output with a measurement microphone, and playing a pulse signal in the reverberation chamber to measure the impulse response and reverberation time of the room; Determine whether the test result can generate a corresponding frequency response curve; If not, compare the sound pressure levels of the smart headset in different environments, optimize the internal design properties of the smart headset according to the sound pressure level, and apply a preset adaptive filter to perform reverberation suppression processing on the audio signal of the smart headset based on the reverberation characteristics of the smart headset to suppress the echo component of the audio signal, wherein the internal design properties specifically refer to the shape and material of the internal acoustic cavity of the headset.

6. The method for compensating high-precision spatial soundscape of headphones according to claim 1, characterized in that: The step of determining whether the spatial soundscape matches the preset omnidirectional surround sound effect further includes: Applying a preset interference sound source to perform a simulated interference test on the smart headset based on various interference test parameters to generate output audio of the smart headset, wherein the interference test parameters specifically include distance, angle arrangement and volume; Determining whether the output audio can achieve a preset spatial soundscape effect; If possible, activate the preset multi-sound source interference environment, play the preset interference audio through the smart headset respectively, and use the preset audio analyzer of the smart headset to collect audio properties in real time, wherein the audio properties specifically include frequency response, volume fluctuation and sound quality changes.

7. The method for compensating high-precision spatial soundscape of headphones according to claim 1, characterized in that: The step of using a preset microphone array to capture the user's ambient sound data in real time and extracting the ambient sound information received by the smart headset includes: Based on the preset spatial layout of the microphone array, beamforming is performed on the ambient sound data, and a preset positioning algorithm is applied to identify sound source attributes, wherein the sound source attributes specifically include a sound source direction and a sound source distance; Determining whether the sound source attribute matches a preset sound intensity change; If not, apply a preset envelope detection algorithm to extract the amplitude envelope of the ambient sound data, collect energy change parameters of the ambient sound data according to the amplitude envelope, extract characteristic information from the energy change parameters, and calculate the energy distribution parameters of the ambient sound data in different time periods based on the characteristic information, wherein the characteristic information specifically includes amplitude and waveform period.

8. A high-precision spatial soundscape compensation system for headphones, characterized in that: include: An extraction module, used to capture the user's ambient sound data in real time based on the sound effect function pre-enabled by the smart headset using a preset microphone array, and extract the ambient sound information received by the smart headset; A determination module, used to determine whether the smart headset can establish a preset spatial soundscape; an execution module, for, if not, identifying the environment type of the ambient sound information, applying a preset dynamic EQ to compensate for the ambient noise received by the smart headset, collecting the type of music played by the smart headset in real time, dynamically adjusting the frequency response according to the type of music, and constructing a unique spatial soundscape of the user according to the type of music and the frequency response, wherein the dynamic EQ specifically includes enhancing the human voice frequency band in a noisy environment and adjusting the low frequency or high frequency in a quiet environment; A second judgment module is used to judge whether the spatial soundscape matches the preset omnidirectional surround sound effect; The second execution module is used to, if not, construct a preset head-related transfer function for the user, dynamically locate the sound source and reconstruct the sound field through the smart headset in combination with the head-related transfer function, apply a preset simulated volume to transmit to the user's ear canal from all directions, track the user's head movement in real time through the head-related transfer function, dynamically adjust the audio rendering of the smart headset according to the head movement, so that the sound position of the simulated volume remains consistent with the change of the head movement, and dynamically adjust the playback volume and sound effect settings of the smart headset according to the preset environmental noise parameters of the simulated volume, wherein the environmental noise parameters specifically include environmental noise level and environmental noise type.

9. The headphone high-precision spatial soundscape compensation system according to claim 8, characterized in that: The execution module also includes: A collection unit, configured to remove background noise from the ambient sound information by applying a preset noise reduction algorithm based on a preset sampling rate of the smart headset, and collect an audio signal; A judging unit, used to judge whether the audio signal is within a preset amplitude range; an execution unit, for, if not, normalizing the audio signal, performing fast Fourier transform on the audio signal, generating a spectrogram of the audio signal, displaying the energy distribution of each frequency component on the spectrogram, extracting the time features of the audio signal and the key features in the spectrogram, inputting the time features and the key features into a pre-trained environment classification model, and determining the environment type of the ambient sound information according to the category label output by the environment classification model.

10. The headphone high-precision spatial soundscape compensation system according to claim 8, characterized in that: Also includes: A recording module, used to play a preset test signal from the smart headset and record a frequency response curve output by the smart headset; A third judging module, used to judge whether the frequency response curve conforms to a preset frequency band; The third execution module is used to apply a preset head-related transfer function to perform a sound field positioning test if not, play an audio signal at a specific position, obtain the positioning accuracy of the smart headset output based on the audio signal, compare the positioning accuracy with the preset position, check the accuracy stability of the audio signal, and use a preset signal generator and oscilloscope to measure the delay time of the audio signal from input to output of the smart headset.

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