Vehicle-mounted audio testing method and system and medium

Abstract

The invention discloses a vehicle-mounted audio test method and system and a medium. The method comprises the following steps: acquiring vehicle audio configuration information; generating an audio test case based on the vehicle audio configuration information; executing the audio test case, including playing a test audio file and recording an output audio; analyzing the recorded output audio, and judging whether the recorded output audio meets a preset audio standard or not; and generating an audio test report according to the analysis result. According to the invention, intelligent automatic testing and personalized calibration of the vehicle audio system are realized, the production efficiency is improved, and manual inspection steps are reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent cockpits, and particularly to a vehicle audio testing method, system and medium. Background Art

[0002] The vehicle audio system is an indispensable part of modern vehicles and plays an important role in enhancing the driving experience and passenger comfort. Currently, the testing and calibration of vehicle audio systems mainly rely on EOL testing on the production line and manual operations by engineers. During production, workers detect the sound - emitting functions of in - vehicle and external speakers through human ear judgment to discover problems caused by component failures or improper installations. Audio calibration is carried out by engineers using engineering vehicles for debugging, and then the audio parameters are solidified in the production software version so that all vehicles of the same model use the same audio parameter settings.

[0003] However, this traditional method has some limitations. First, manual detection may have inaccurate judgments and it is difficult to conduct separate and precise tests on each speaker. Second, due to factors such as production batches and installation errors, using unified audio parameters may result in slight differences in sound effects between different vehicles. In addition, manual operations are time - consuming and inefficient, making it difficult to meet the requirements of large - scale production. Therefore, developing a more intelligent, efficient and accurate vehicle audio testing and calibration method has practical significance for improving production efficiency and product quality. Summary of the Invention

[0004] In view of the above - mentioned technical problems, the present invention provides a vehicle audio testing method, system and medium, which realizes the intelligent automatic testing and personalized calibration of vehicle audio systems, improves production efficiency and reduces the manual inspection steps.

[0005] In the first aspect of the present invention, a vehicle audio testing method is provided, including: Obtaining vehicle audio configuration information; Generating audio test cases based on the vehicle audio configuration information; Executing the audio test cases, including playing test audio files and recording the output audio; Analyzing the recorded output audio to determine whether it meets the preset audio standards; and Generating an audio test report according to the analysis result.

[0006] In a possible implementation manner, the generating audio test cases based on the vehicle audio configuration information includes: Generating speaker function test cases based on the vehicle audio configuration information; Generating noise cancellation test cases based on the vehicle audio configuration information; and Generate a surround sound effect test case based on the vehicle audio configuration information.

[0007] In one possible implementation, the generating a speaker function test case based on the vehicle audio configuration information includes: Generate a test audio file, where the test audio file includes a sine wave and white noise.

[0008] In one possible implementation, the generating a noise cancellation test case based on the vehicle audio configuration information includes: Record the background noise when the vehicle starts; Enable the active noise control function; and Record the in-vehicle noise again.

[0009] In one possible implementation, the generating a surround sound effect test case based on the vehicle audio configuration information includes: Generate a multi-channel surround sound test track.

[0010] In one possible implementation, the executing the audio test case includes playing the test audio file and recording the output audio, including: Play the test audio file through the in-vehicle audio system; and Use the in-vehicle microphone or an external recording device to record the output audio.

[0011] In one possible implementation, the analyzing the recorded output audio to determine whether it meets the preset audio standard includes: Use a preset audio feature extraction model to extract the feature vector of the output audio; Use a preset audio parameter analysis model to analyze the feature vector and determine whether the corresponding output audio meets the preset audio standard.

[0012] In one possible implementation, the method further includes: If the analysis result does not meet the preset audio standard, generate new audio calibration parameters; Use the new audio calibration parameters to re-execute the in-vehicle audio test method until the analysis result meets the preset audio standard.

[0013] In a second aspect of the present invention, there is provided an in-vehicle audio test system, including: A configuration acquisition module, configured to acquire vehicle audio configuration information; A test case generation module, configured to generate an audio test case based on the vehicle audio configuration information; A test execution module for executing the audio test cases, including playing a test audio file and recording the output audio; An audio analysis module for analyzing the recorded output audio to determine whether it meets a preset audio standard; and A report generation module for generating an audio test report based on the analysis result.

[0014] In a third aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon. When the computer program is run by a computer, it executes the method described in the first aspect of the embodiments of the present invention.

[0015] In summary, compared with the prior art, the present invention includes at least one of the following beneficial technical effects: realizing remote fully automated intelligent audio testing and calibration in the vehicle production process, reducing manual inspection steps, and lowering the defective parts outflow rate; shortening the production test time and improving the production efficiency by intelligently generating test cases; and simultaneously achieving individual audio calibration for each vehicle, narrowing the subtle differences in sound effects between vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of an embodiment of the vehicle-mounted audio testing method of the present invention.

[0017] Figure 2 It is a schematic structural diagram of an embodiment of the vehicle-mounted audio testing system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] It should be understood that the terms "first", "second", "third", etc. in the claims, the description, and the drawings of the present disclosure are used to distinguish different objects, rather than to describe a specific order. The terms "including" and "comprising" used in the description and claims of the present disclosure indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations. It should also be understood that the terms used in the description of the present disclosure herein are only for the purpose of describing specific embodiments, and are not intended to limit the present disclosure.

[0020] Refer to Figure 1, embodiments of the present invention provide a method for in-vehicle audio testing, including the following steps.

[0021] S1. Obtain vehicle audio configuration information. Specifically, read the preset audio configuration information through the vehicle system, including speaker layout (such as the positions, quantities, and types of front left, front right, rear left, rear right, center, subwoofer, etc.), audio input / output configuration (such as supported audio formats, sampling rates, bit rates, audio sources such as CD, Bluetooth, USB, AUX, etc., output modes such as stereo, surround sound, etc.), volume range (minimum volume, maximum volume, and audio curve parameters), and sound effect settings (such as equalizer parameters, sound effect modes, optimal listening position settings), etc.; these configuration information will be used as the basic input for generating audio test cases and test audio files to ensure that all actual configurations of the vehicle are covered during the testing process.

[0022] S2. Generate audio test cases based on the vehicle audio configuration information.

[0023] Specifically, according to the information such as the number, position, type of speakers, and audio output configuration obtained in step S1, use a pre-trained audio generation model to intelligently generate test cases and audio files that cover all speakers and sound effect modes. The test cases include, but are not limited to, speaker function tests, active noise control (ANC) tests, and surround sound effect tests, etc.; a corresponding test audio, such as a sine wave, white noise, or multi-channel audio track, is generated for each test case, and the test path is optimized in combination with the specific vehicle configuration to achieve full coverage with the minimum number of test cases.

[0024] S3. Execute the audio test cases, including playing the test audio files and recording the output audio.

[0025] Specifically, after receiving the test instruction, play the corresponding test audio files in sequence through the in-vehicle audio system according to the generated test cases; at the same time, start the in-vehicle microphone or an external recording device to record the audio output by each speaker in real time. Different channels, frequency bands, and sound effect modes can be covered during the recording process to ensure comprehensive collection of the actual sound effects of the speakers and provide a complete audio data basis for subsequent analysis.

[0026] S4. Analyze the recorded output audio to determine whether it meets the preset audio standards.

[0027] Specifically, a pre-trained audio feature extraction model and an audio parameter analysis model are used to perform multi-dimensional analysis on the recorded audio signal, including parameters such as frequency response, distortion rate, signal-to-noise ratio, dynamic range, and sound field distribution. Through technical means such as spectrum analysis, distortion detection, and phase comparison, the actual output is compared with the audio product design standard to determine whether the speaker is emitting sound normally and whether the overall sound effect meets the standard. If an abnormality is found, the specific problem type can also be identified to provide a basis for subsequent calibration.

[0028] S5, generate an audio test report according to the analysis result.

[0029] After completing the parameter analysis and judgment of the recorded audio, the test data and analysis results are automatically sorted using a preset format to generate an audio test report containing information such as the sound-emitting state of each speaker, whether the audio parameters meet the standard, the type and location of abnormalities, etc. This report can be displayed on the in-vehicle screen or uploaded to the cloud platform for quality traceability or production management. If there are situations that do not meet the standards, new audio calibration parameters can also be recommended or generated based on the analysis results for subsequent re-testing.

[0030] The in-vehicle audio test method described in the embodiments of the present invention realizes the intelligence and automation of the entire audio test process by introducing an AI large model, and has significant technical effects. It not only greatly reduces manual operations and improves test efficiency, but also can generate customized test cases and calibration parameters based on the individual configurations of vehicles to ensure the accuracy and reliability of test results. At the same time, it can automatically analyze audio quality and generate detailed test reports, improve production consistency and quality control capabilities, effectively reduce the risk of defective audio products flowing out, and enhance the user's auditory experience.

[0031] Further, as an implementation manner of the present invention, in step S2, generating an audio test case based on the vehicle audio configuration information includes: generating a speaker function test case based on the vehicle audio configuration information; generating a noise cancellation test case based on the vehicle audio configuration information; and generating a surround sound effect test case based on the vehicle audio configuration information.

[0032] In some implementation manners, generating a speaker function test case based on the vehicle audio configuration information includes: generating a test audio file, and the test audio file includes a sine wave and white noise.

[0033] Specifically, an audio generation model, such as a generative adversarial network (GAN) or an autoregressive model (such as WaveNet), is used to automatically generate audio waveforms for functional testing, such as standard test tracks like sine waves and white noise, according to the number, type, and layout information of speakers in the vehicle configuration. Exemplarily, taking WaveNet as an example, this model can generate high-quality audio signals with specific frequency ranges according to the input speaker type and target frequency characteristics, which are used to verify the sound generation function and frequency response performance of each speaker, thereby forming highly targeted and comprehensive speaker function test cases.

[0034] In some embodiments, generating a noise cancellation test case based on the vehicle audio configuration information includes: recording background noise when the vehicle starts; enabling the active noise control function; and recording the in-vehicle noise again.

[0035] Specifically, the autoregressive audio generation model WaveNet is used to customize and generate corresponding test audio signals for each speaker position based on the obtained vehicle audio configuration information (such as the position, type, number, supported frequency range, etc. of the speakers). The WaveNet model can synthesize high-fidelity audio waveforms with precise frequency control by learning the time series characteristics of the real audio waveforms when the vehicle starts, such as sine waves or band-pass noise with specific frequencies, which are used to test the sound generation ability and frequency response of the speakers. Each generated audio signal matches different types of speakers (such as high, mid, and low frequencies), and finally constitutes a set of functional test cases covering all speakers in the vehicle.

[0036] In some embodiments, generating a surround sound effect test case based on the vehicle audio configuration information includes: generating a multi-channel surround sound test track.

[0037] Specifically, the audio generation model WaveNet is used to automatically generate multi-channel surround sound test audio, such as 5.1 or 7.1 channel surround sound tracks, according to the number of channels, spatial layout, and sound effect mode of the surround sound speakers in the vehicle configuration. By modeling the time series characteristics of multi-channel audio signals, WaveNet can accurately generate audio signals with specific delays, phase relationships, and positioning information between channels, realizing the simulation of sound source directionality. The generated test tracks can be used to evaluate the sense of space, channel separation, and sound field performance of the surround sound system, thereby constructing a complete surround sound effect test case.

[0038] Further, as an embodiment of the present invention, step S3 of executing the audio test case includes: playing a test audio file through the in-vehicle audio system; and recording the output audio using an in-vehicle microphone or an external recording device.

[0039] Specifically, for the audio test cases generated by the audio generation model, call the audio playback interface of the in-vehicle audio system, send the test audio files in the corresponding formats (such as WAV, MP3, FLAC, etc.) to the in-vehicle speaker system, and activate each channel or speaker position one by one in the preset order for playback; during the playback process, the audio type (such as sine wave, white noise, multi-channel surround sound track), volume level, duration, and output path can be precisely controlled to ensure that the test signal can cover all channels and sound effect modes under specific conditions, providing a standardized and reproducible test sound source for subsequent audio recording and analysis.

[0040] While playing the test audio file, automatically start the built-in microphone in the vehicle or the connected external high-sensitivity recording device, and collect the actual sound signals of each speaker in real time according to the set recording parameters (such as sampling rate, number of recording channels, duration, etc.); the recording points can be selected according to the vehicle microphone layout or test requirements to ensure coverage of key listening areas such as the driver's seat, passenger seat, and rear row, so as to obtain comprehensive and accurate audio output data for subsequent parameter analysis and quality determination.

[0041] Further, as an implementation manner of the present invention, in step S4, analyze the recorded output audio to determine whether it meets the preset audio standard, including: Use the preset audio feature extraction model to extract the feature vector of the output audio; Use the preset audio parameter analysis model to analyze the feature vector and determine whether the corresponding output audio meets the preset audio standard.

[0042] Specifically, use a preset audio feature extraction model such as OpenL3 or VGGish to process the recorded speaker output audio. First, preprocess the audio signal, including operations such as resampling (such as unifying to 16 kHz), framing, and short-time Fourier transform (STFT); then input the processed audio into the feature extraction model. Exemplarily, taking OpenL3 as an example, this model encodes the time-frequency diagram of the audio through a deep neural network and outputs a multi-dimensional feature vector, containing high-order audio characteristic information such as frequency distribution, timbre, rhythm, and phase. The extracted feature vector can accurately reflect the audio quality of the actual output of the speaker, providing basic data support for subsequent audio parameter analysis and pass / fail determination.

[0043] Next, a preset audio parameter analysis model, such as an XGBoost or random forest model, is called to perform multi-dimensional analysis on the feature vectors generated by the audio feature extraction model (such as OpenL3 or VGGish). By learning the mapping relationship between audio features and sound quality evaluation metrics (such as frequency response flatness, signal-to-noise ratio, total harmonic distortion THD, channel separation, etc.) in a large number of labeled samples during the training phase, the audio parameter analysis model can quickly determine whether the actually recorded audio meets the product design standards during the inference phase. For example, the model can output the judgment results or scores of whether each parameter meets the standard, and based on this, determine whether the output of the speaker or audio system is qualified, thereby achieving precise evaluation of audio performance.

[0044] Further, as an implementation manner of the present invention, the method further includes: If the analysis result does not meet the preset audio standard, new audio calibration parameters are generated; The new audio calibration parameters are used to re-execute the in-vehicle audio test method until the analysis result meets the preset audio standard.

[0045] Specifically, in the corresponding analysis result, by combining the feature vectors of the non-compliant audio and the specific deviation indicators, a parameter regression optimization mechanism is used to automatically generate new audio calibration parameters. An XGBoost or neural network regression model can be used to adjust key configurations such as equalizer parameters, volume gain, channel distribution weights, and delay compensation according to the difference between the audio output and the standard parameters, so as to optimize the sound output characteristics. The generated new calibration parameters are personalized optimized for the hardware state and sound effect performance of the current vehicle.

[0046] The generated new audio calibration parameters are applied to the vehicle audio system. After adjusting configurations such as speaker gain, equalizer settings, channel delay, and sound effect mode, the complete in-vehicle audio test process is re-executed, that is, the test audio file is generated and played again, the output audio is recorded, the feature vectors are extracted and parameter analysis is performed. Referring to the above specific implementation manners, it will not be elaborated here.

[0047] If the analysis result still does not meet the audio standard, the parameters are continuously iteratively adjusted and the test process is repeated until the parameters of the output audio meet the preset standards, realizing refined and adaptive calibration of the sound effects of each vehicle.

[0048] The present invention realizes the full - process intelligence and automation of in - vehicle audio systems from testing to calibration, with significant beneficial technical effects: not only greatly reducing manual intervention and lowering the missed - inspection rate, but also automatically generating test cases and high - quality test audio based on vehicle individual configurations, achieving comprehensive coverage of speaker functions, noise control, and surround - sound effects; at the same time, having precise audio analysis and personalized calibration capabilities, being able to automatically adjust audio parameters according to the actual output to ensure that the sound effects of each vehicle reach the preset standards, significantly improving production efficiency, product consistency, and the user's auditory experience.

[0049] Referring to Figure 2 , an embodiment of the present invention also discloses an in - vehicle audio test system, including a configuration acquisition module 1, a test - case generation module 2, a test execution module 3, an audio analysis module 4, and a report generation module 5.

[0050] The configuration acquisition module 1 is used to acquire vehicle audio configuration information.

[0051] Specifically, the configuration acquisition module 1 automatically extracts configuration information related to the in - vehicle audio system by accessing the vehicle's electronic control unit (ECU) or central processing platform, including the layout of speakers (such as front, rear, left, right, center, subwoofer, etc.), quantity and type (such as full - range, high - frequency, low - frequency speakers), supported audio input / output formats (such as Bluetooth, USB, AUX, CD, etc.), sound - effect settings (such as equalizer parameters, surround - sound mode, optimal listening position, etc.), as well as volume range and curve parameters, etc.; the above - mentioned information serves as an important basis for subsequent test - case generation and audio analysis to ensure that the test process conforms to the actual audio - system configuration of the vehicle.

[0052] The test - case generation module 2 is used to generate audio test cases based on the vehicle audio configuration information.

[0053] Specifically, the test - case generation module 2 integrates an AI model based on an audio generation model (such as WaveNet), and uses the vehicle audio configuration information provided by the configuration acquisition module 1 to automatically generate audio test cases covering various test targets, including speaker - function tests, active noise control (ANC) tests, and surround - sound effect tests, etc. Exemplarily, the test - case generation module 2 generates test audio (such as sine waves, white noise, or 5.1 - channel audio tracks) with specific frequencies or channel structures according to the type and layout of different speakers to ensure that each speaker and its acoustic characteristics are accurately tested, thereby constructing an audio test scheme that highly matches the vehicle configuration and has comprehensive coverage.

[0054] The test execution module 3 is used to execute the audio test cases, including playing test audio files and recording the output audio.

[0055] The test execution module 3 receives the test audio file and test instructions output by the test case generation module 2, and plays various test audios one by one through the in-vehicle audio system according to the preset process; at the same time, it controls the in-vehicle microphone or an external recording device to synchronously record the actual audio output by the speaker. During the recording process, it can collect in groups according to channels, frequency bands or spatial positions to ensure comprehensive coverage of the sound production states and sound effects of all speakers. The test execution module 3 also supports automatic execution of multiple test rounds to facilitate subsequent comparison and evaluation by the analysis module.

[0056] The audio analysis module 4 is used to analyze the recorded output audio and determine whether it meets the preset audio standards.

[0057] Specifically, the audio analysis module 4 first calls an audio feature extraction model (such as OpenL3 or VGGish) to process the recorded output audio, and extracts a high-dimensional feature vector containing information such as frequency distribution, timbre, rhythm, and phase; then it inputs this feature vector into an audio parameter analysis model (such as XGBoost or random forest) to judge and score key audio indicators such as frequency response, distortion rate, signal-to-noise ratio, and channel separation degree, and compares them with the preset audio standards to determine whether the audio meets the standards, and can locate specific abnormal items to provide a basis for subsequent calibration.

[0058] At the same time, after the audio analysis module 4 determines that the recorded output audio does not meet the preset audio standards, it calls a pre-trained regression model (such as a neural network or XGBoost), and based on the current audio feature vector and the parameter difference from the standard deviation, automatically generates new audio calibration parameters, such as speaker gain adjustment, equalizer compensation, delay correction, channel weight allocation, etc.; the generated calibration parameters will be transmitted back to the configuration acquisition module 1 through the system feedback mechanism, and this module will update the vehicle audio configuration information and trigger a new round of test process to achieve closed-loop adaptive audio optimization.

[0059] The report generation module 5 is used to generate an audio test report according to the analysis results.

[0060] Specifically, after the audio analysis module 4 completes the analysis and judgment of various parameters of the output audio, the report generation module 5 automatically sorts out the analysis results and generates a structured audio test report. The report content includes the judgment results of whether the sound production states, frequency responses, signal-to-noise ratios, distortion rates, surround sound effects, etc. of each speaker meet the standards, as well as the description of the specific abnormal positions and types. The report can be locally displayed on the in-vehicle terminal or uploaded to the cloud system for quality traceability and production control, and at the same time supports export in PDF or data format for subsequent analysis or archiving.

[0061] The embodiment of the present invention also discloses a readable storage medium.

[0062] A readable storage medium stores a computer program which, when executed by a processor, implements the steps of the vehicle audio testing method described in any one of the above embodiments.

[0063] It can be understood that a computer-readable storage medium may include: any entity or device capable of carrying a computer program, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disc, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), and a software distribution medium, etc. The computer program includes computer program code. The computer program code may be in the form of source code, object code, an executable file, or some intermediate form, etc. A computer-readable storage medium may include: any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disc, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), and a software distribution medium, etc.

[0064] In some embodiments of the present invention, the electronic device may include a controller or a processor. The controller is a single-chip microcomputer chip integrating a processor, a memory, a communication module, etc. The processor may refer to the processor included in the controller. The processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0065] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0066] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0067] The above embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle-mounted audio testing method, characterized in that, Including: Obtain vehicle audio configuration information; Generate audio test cases based on the vehicle audio configuration information; Execute the audio test cases, including playing test audio files and recording the output audio; Analyze the recorded output audio to determine whether it meets the preset audio standards; And Generate an audio test report according to the analysis result.

2. The vehicle-mounted audio testing method according to claim 1, wherein The generating audio test cases based on the vehicle audio configuration information includes: Generate speaker function test cases based on the vehicle audio configuration information; Generate noise cancellation test cases based on the vehicle audio configuration information; and Generate surround sound effect test cases based on the vehicle audio configuration information.

3. The in-vehicle audio testing method according to claim 1, characterized in that, The generating speaker function test cases based on the vehicle audio configuration information includes: Generate a test audio file, the test audio file including a sine wave and white noise.

4. The vehicle-mounted audio testing method according to claim 2, wherein The generating noise cancellation test cases based on the vehicle audio configuration information includes: Record background noise when the vehicle starts; Enable the active noise control function; and Record the in-vehicle noise again.

5. The vehicle-mounted audio testing method according to claim 2, wherein The generating surround sound effect test cases based on the vehicle audio configuration information includes: Generate a multi-channel surround sound test track.

6. The in-vehicle audio testing method according to claim 1, wherein The executing the audio test cases, including playing test audio files and recording the output audio, includes: Play the test audio file through the in-vehicle audio system; and Use an in-vehicle microphone or an external recording device to record the output audio.

7. The vehicle-mounted audio testing method according to claim 1, characterized in that, The analyzing the recorded output audio to determine whether it meets the preset audio standards includes: Extract the feature vector of the output audio by using a preset audio feature extraction model; Analyze the feature vector by using a preset audio parameter analysis model and determine whether the corresponding output audio meets the preset audio standards.

8. The vehicle-mounted audio testing method according to claim 1, characterized in that It also includes: If the analysis result does not meet the preset audio standards, generate new audio calibration parameters; Use the new audio calibration parameters to re-execute the in-vehicle audio test method until the analysis result meets the preset audio standards.

9. An in-vehicle audio test system, characterized in that, The system includes: A configuration acquisition module for obtaining vehicle audio configuration information; A test case generation module for generating audio test cases based on the vehicle audio configuration information; A test execution module for executing the audio test cases, including playing test audio files and recording the output audio; An audio analysis module for analyzing the recorded output audio to determine whether it meets the preset audio standards; and A report generation module for generating an audio test report according to the analysis result.

10. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and when the computer program is run by a computer, it executes the in-vehicle audio test method according to any one of claims 1 to 8.

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