Sound effect adjusting method and system and vehicle-mounted terminal

Abstract

The invention provides a sound effect adjusting method and system and a vehicle-mounted terminal. The sound effect adjusting method comprises the steps that internal and external environment noise of a vehicle is collected, the environment noise is analyzed, and an environment noise analysis result is obtained; then monitoring a driving scene of a vehicle in real time, obtaining driving scene information, and matching a target sound effect library in combination with the environmental noise analysis result and the driving scene information; and further loading sound effect preference settings of the driver and passengers and / or identifying information states of the driver and passengers, outputting an adjustment strategy of the target sound effect library, and adjusting output parameters of the target sound effect library according to the adjustment strategy. According to the method, the sound effect can be dynamically adjusted according to the real-time driving scene and the sound effect preference and / or the information state of the driver and passengers, and personalized and comfortable auditory experience is provided; and the user does not need to manually adjust the sound effect setting, so that the operation burden of the user is simplified, and the user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of in-vehicle entertainment technology, and in particular to a sound effect adjustment method, system and in-vehicle terminal. Background Art

[0002] With the rapid development of automobile intelligence and Internet of Vehicles technology, modern cars are gradually becoming "mobile living spaces" with high interactivity, personalization and comfort requirements. People's demand for personalized experience is increasing, and in-car environment control has gradually become a hot research topic in the industry, not only limited to the adjustment of physical environments such as lighting and temperature, but also extended to the optimization of acoustic environment.

[0003] In scenarios such as high-speed driving, city congestion, or long-term driving, the ambient noise inside and outside the car will affect the passengers' auditory experience. Traditional in-car entertainment systems mainly focus on audio and video playback functions. Although some systems provide sound effect setting options, these configurations are usually static and manually adjusted, and it is difficult to adapt to complex driving environments and user needs in real time. Therefore, in actual applications, traditional systems are difficult to provide a consistent and comfortable auditory experience. Summary of the invention

[0004] In order to solve the above-mentioned technical problems, the present application provides a sound effect adjustment method, system and vehicle-mounted terminal.

[0005] Specifically, the present application provides a method for adjusting sound effects, comprising the following steps: The internal and external environmental noise of the vehicle is collected, and the environmental noise is analyzed to obtain an environmental noise analysis result.

[0006] The driving scene of the vehicle is monitored in real time, driving scene information is acquired, and a target sound effect library is matched in combination with the environmental noise analysis result and the driving scene information.

[0007] Load the sound effect preference settings of the driver and occupant and / or identify the information status of the driver and occupant, output the adjustment strategy of the target sound effect library, and adjust the output parameters of the target sound effect library according to the adjustment strategy.

[0008] In the above technical solution, by collecting and analyzing environmental noise, the system can select the most suitable sound effect library. At the same time, the system can dynamically adjust the sound effects according to real-time driving scenarios (such as highways, urban congestion, long-term driving, driving in rainy days, etc.) and the preferences and status of the driver and passengers to provide a personalized and comfortable listening experience.

[0009] In addition, users do not need to manually adjust the sound settings. The system automatically makes the best choice based on the current environment and scene, which simplifies the user's operating burden and improves the user experience.

[0010] Further, the obtaining of environmental noise analysis results includes: The environmental noise is filtered to obtain target noise, and the noise source of the target noise is obtained based on a deep learning model.

[0011] And, obtaining noise intensity according to the target noise.

[0012] In the above technical solution, filtering processing can remove background noise in the noise, making the subsequent noise source identification more accurate; the deep learning model can learn and identify complex noise patterns, provide high-precision noise source identification, and can adapt to a variety of noise environments, whether it is engine noise, wind noise, tire noise or external traffic noise, it can be accurately identified; through the identification of noise sources, the types of major noises in the environment can be understood in more detail, providing a more accurate basis for subsequent sound effect adjustments. Different types of noise correspond to different sound effect libraries, making the sound effect selection more personalized and targeted.

[0013] In addition, the noise intensity is further obtained based on the target noise. For example, "engine noise" is subdivided into "low-intensity engine noise" and "high-intensity engine noise". By obtaining the noise intensity, the system can more finely distinguish noise environments of different intensities, thereby selecting a more appropriate sound effect strategy.

[0014] Furthermore, the driving scene information includes at least weather information, road condition information and driving mode information; the matching target sound effect library includes: The target sound effect library is matched in combination with the noise source, weather information, road condition information and the driving mode information.

[0015] In the above technical solution, multi-source information is combined to match the target sound effect library, so that the matched target sound effect library can better meet the needs of current vehicle drivers and passengers, and be more adaptable to current driving scenarios.

[0016] Furthermore, after the sound effect preference settings of the driver and passenger are loaded, the method includes: analyzing the sound effect preference settings to obtain sound effect preference analysis results.

[0017] In the above technical solution, by obtaining the sound effect preference settings, the sound effect adjustment habits of the driver and passengers can be further analyzed, making the adjustment strategy more personalized and flexible, which can improve the driver and passengers' auditory experience, comfort, and driving experience.

[0018] Furthermore, the driver and passenger information status includes at least the number of drivers and passengers and their position information in the vehicle; and the adjustment strategy includes at least a volume strategy, a purity strategy and a sense of space strategy.

[0019] The adjustment strategy for outputting the target sound effect library includes: Output a volume strategy according to the sound effect preference analysis result and / or the noise intensity.

[0020] Output a purity strategy according to the sound effect preference analysis result and / or the driving scene information.

[0021] And, output a spatial sense strategy in combination with the sound effect preference analysis result, and / or the number of the occupants, their position information in the vehicle and the ambient noise analysis result.

[0022] In the above technical solution, through multi-dimensional precise adjustment of volume, spatial sense and purity, the system can provide a highly personalized auditory experience to adapt to the preferences and needs of different users; real-time adjustment of volume and purity enables the system to respond quickly to environmental changes and provide consistent auditory comfort; and the output spatial sense strategy will combine the number of drivers and passengers and their position in the car to provide the best auditory positioning and immersion.

[0023] In addition, obtaining the results of sound effect preference analysis enables the system to select sound effects based on the user's personalized needs and preferences, providing an auditory experience that is more in line with the user's preferences.

[0024] Furthermore, the adjustment strategy also includes at least a frequency response strategy; in the process of adjusting the output parameters of the target sound effect library based on the volume strategy, purity strategy and spatial sense strategy, it also includes: real-time monitoring of the current noise frequency to output a frequency response strategy based on the noise frequency.

[0025] In the above technical solution, the frequency response of the sound effect is dynamically adjusted according to the monitored noise frequency to effectively suppress noise interference and enhance the clarity of the sound effect.

[0026] Furthermore, the driver and occupant information state at least includes the driver and occupant's emotional state; and in the process of adjusting the output parameters of the target sound effect library according to the adjustment strategy, it also includes: The emotional state of the driver and passenger is acquired and analyzed in real time, so as to switch the target sound effect library based on the emotional state analysis result.

[0027] And / or collect control instructions from the driver and passengers in real time to switch the target sound effect library and / or adjust the output parameters according to the control instructions; wherein the control instructions are issued at least through voice, gesture or mobile application.

[0028] In the above technical solution, the system can continuously optimize the sound adjustment strategy according to the emotional state to improve the user experience; and through various control methods such as voice, gestures and mobile applications, users can choose the most convenient operation method according to their habits and scenarios, which improves the convenience of interaction and user experience; non-contact operation methods such as voice and gesture control reduce the manual operation of drivers and passengers during driving, reduce the risk of distraction, and improve driving safety.

[0029] Furthermore, in the process of adjusting the output parameters of the target sound effect library according to the adjustment strategy, it also includes: The output parameters are recorded in combination with the environmental noise analysis results, the driving scene information, the driver and passenger information status and the control instruction to update the sound effect preference settings based on the output parameters.

[0030] In the above technical solution, by recording and updating the sound effect preference settings, the system can make personalized adjustments based on the user's actual usage, providing a more accurate and user-preferred sound effect experience; combining multi-dimensional information to record output parameters to ensure that the sound effect settings are accurately matched to the user's current status and needs, thereby improving the accuracy and personalization of the auditory experience.

[0031] Based on the same concept, the present application also provides a sound effect adjustment system, the system comprising: The noise collection module is used to collect the internal and external environmental noise of the vehicle, analyze the environmental noise, and obtain environmental noise analysis results.

[0032] The sound effect acquisition module is used to monitor the driving scene of the vehicle in real time, obtain driving scene information, and match the target sound effect library in combination with the environmental noise analysis result and the driving scene information.

[0033] and a sound effect adjustment module, which is used to load the sound effect preference settings of the driver and passenger and / or identify the information status of the driver and passenger, output the adjustment strategy of the target sound effect library, and adjust the output parameters of the target sound effect library according to the adjustment strategy.

[0034] In the above technical solution, through noise collection and analysis, the system can accurately identify the noise environment, make targeted sound effect adjustments, and improve the accuracy and personalization of the auditory experience; combined with driving scenarios, sound effect preferences and driver and passenger information, the system can optimize the sound effects in multiple dimensions and provide an auditory experience that is more in line with user needs and preferences; and users do not need to manually adjust the sound settings, the system automatically adjusts according to the current environment and user status, which simplifies user operations and improves user experience.

[0035] Based on the same concept, the present application also provides a vehicle-mounted terminal, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the sound effect adjustment method.

[0036] Compared with the prior art, the beneficial effects of this application are: This application first collects the internal and external environmental noise of the vehicle, analyzes the environmental noise, and obtains the environmental noise analysis results; then monitors the driving scene of the vehicle in real time, obtains driving scene information, and matches the target sound effect library in combination with the environmental noise analysis results and the driving scene information; further loads the sound effect preference settings of the driver and passenger and / or identifies the information status of the driver and passenger, outputs the adjustment strategy of the target sound effect library, and adjusts the output parameters of the target sound effect library according to the adjustment strategy. This application can dynamically adjust the sound effects according to the real-time driving scene, as well as the sound effect preferences and / or information status of the driver and passenger, to provide a personalized and comfortable listening experience; and there is no need for the user to manually adjust the sound effect settings, which simplifies the user's operating burden and improves the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of the sound effect adjustment method described in an embodiment of the present application.

[0038] Figure 2 This is an initialization flow chart described in an embodiment of the present application.

[0039] Figure 3 This is a data collection flow chart described in an embodiment of the present application.

[0040] Figure 4 This is a data processing flow chart described in an embodiment of the present application.

[0041] Figure 5 This is a framework diagram of the sound effect adjustment system described in an embodiment of the present application. DETAILED DESCRIPTION

[0042] The following is a further detailed description of a sound effect adjustment method, system and vehicle-mounted terminal of the present application in conjunction with specific embodiments and drawings.

[0043] See also Figure 1 , an embodiment of the present application provides a sound effect adjustment method, including the following steps S100-S300.

[0044] The steps S100-S300 are described in detail below: Wherein, step S100: collecting the internal and external environmental noise of the vehicle, and analyzing the environmental noise to obtain the environmental noise analysis result.

[0045] Among them, see Figure 2 Before collecting data, the initialization process of the sound effect adjustment system is also involved, including: Load user preferences, sound effect library and initialize hardware; specifically, read historical user preferences from the database to obtain current output parameters, download the latest target sound effect library from the server, preload each target sound effect library for subsequent direct calls; and test the function of the current speaker, and calibrate the noise, position and heart rate of the speaker.

[0046] For further information, see Figure 3 , the obtaining of environmental noise analysis results includes: The environmental noise is filtered to obtain target noise, and the noise source of the target noise is obtained based on a deep learning model.

[0047] In some embodiments, the environmental noise inside and outside the vehicle is collected in real time through a vehicle-mounted microphone array, an acceleration sensor, and other noise collection sensors (such as wind noise or rain noise sensors); the environmental noise collected in real time needs to be filtered, and specifically an adaptive filter (such as an LMS or RLS filtering algorithm) is used to process the collected original environmental noise, thereby removing part of the reflected noise inside the vehicle.

[0048] It should be noted that, in other embodiments, those skilled in the art may also use more noise collectors to collect environmental noise, so as to collect a wider range of noise, improve the accuracy of subsequent noise classification, and improve the personalization of sound effect selection.

[0049] Among them, the LMS (Least Mean Square) filtering algorithm is an adaptive filtering algorithm based on the gradient descent method. Its core idea is to adjust the weight coefficient of the filter by minimizing the mean square value of the error signal; the RLS (Recursive Least Squares) filtering algorithm is an adaptive filtering algorithm based on the least squares method (Least Squares). Its core idea is to adjust the weight coefficient of the filter by minimizing the weighted sum of squares of the error signal.

[0050] Furthermore, in some embodiments, a deep learning model such as a convolutional neural network (CNN) or a long short-term memory network (LSTM) is used to analyze the collected and filtered noise data through the deep learning model to determine whether the noise source is from inside the car (such as passengers talking, equipment running inside the car) or outside the car (such as other vehicles, traffic noise), and based on the spectral characteristics of the noise source, it is classified into wind noise, tire noise, rain noise, external traffic noise, etc., so as to perform corresponding sound effect adaptation later.

[0051] In the above technical solution, filtering processing can remove background noise in the noise, making the subsequent noise source identification more accurate; the deep learning model can learn and identify complex noise patterns, provide high-precision noise source identification, and can adapt to a variety of noise environments, whether it is engine noise, wind noise, tire noise or external traffic noise, it can be accurately identified; through the identification of noise sources, the types of major noises in the environment can be understood in more detail, providing a more accurate basis for subsequent sound effect adjustments. Different types of noise correspond to different sound effect libraries, making the sound effect selection more personalized and targeted.

[0052] Furthermore, the obtaining of environmental noise analysis results also includes: A noise intensity is obtained according to the target noise.

[0053] In some embodiments, Fourier transform or wavelet transform is used to analyze the spectral intensity of the target noise, and a noise intensity threshold is set. According to the real-time changing data, the system divides the noise intensity into multiple levels (such as low, medium, high, and very high).

[0054] It should be noted that, in other embodiments, those skilled in the art may also adopt other analysis methods to analyze the spectrum intensity, and are not limited to the above analysis method; at the same time, the level of noise intensity can be subdivided into more levels, and is not limited to this.

[0055] In the above technical solution, based on the noise source identification, the noise intensity is further obtained according to the target noise. For example, "engine noise" is subdivided into "low-intensity engine noise" and "high-intensity engine noise". By obtaining the noise intensity, the system can more finely distinguish noise environments of different intensities, so as to select a more appropriate sound effect strategy.

[0056] After the environmental noise analysis result is obtained, step S200 may be executed.

[0057] Among them, step S200: real-time monitoring of the driving scene of the vehicle, obtaining driving scene information, and matching the target sound effect library in combination with the environmental noise analysis result and the driving scene information.

[0058] Furthermore, the driving scene information includes at least weather information, road condition information and driving mode information; the matching target sound effect library includes: The target sound effect library is matched in combination with the noise source, weather information, road condition information and the driving mode information.

[0059] In some embodiments, the driving scenario includes at least a driving environment and a driving mode. Weather information and road condition information may be obtained based on the driving environment, and driving mode information may be obtained based on the driving mode.

[0060] Among them, the weather information includes rain, snow, strong wind, etc.; the road condition information at least includes expressways, urban roads, and rural roads; the driving mode at least includes sports mode, economic mode, etc.

[0061] Specifically, the sports mode usually has a more sensitive throttle response, higher engine speed, stiffer suspension, heavier steering and greater braking force; while in the economic mode, there is usually a smoother throttle response, earlier gear shifting, softer suspension, lighter steering and other energy-saving auxiliary functions, such as enabling functions such as the start-stop system.

[0062] In different driving environments, select appropriate sound effects based on the driving mode, such as enhancing low-frequency and rhythmic sound effects in sports mode.

[0063] In the above technical solution, multi-source information is combined to match the target sound effect library, so that the matched target sound effect library can better meet the needs of current vehicle drivers and passengers, and be more adaptable to current driving scenarios.

[0064] After the target sound effect library is matched, step S300 may be executed.

[0065] Among them, step S300: loading the sound effect preference settings of the driver and passenger and / or identifying the information status of the driver and passenger, outputting the adjustment strategy of the target sound effect library, and adjusting the output parameters of the target sound effect library according to the adjustment strategy.

[0066] Furthermore, after the sound effect preference settings of the driver and passenger are loaded, the method includes: analyzing the sound effect preference settings to obtain sound effect preference analysis results.

[0067] In some embodiments, users can set specific preferences such as sound effect style, volume threshold, and playback time through the vehicle touch screen, mobile phone app, or voice assistant. Based on user usage data and feedback (such as the number of manual adjustments to the sound effect), collaborative filtering algorithms or K-means clustering are used to analyze user preferences and generate a personalized sound effect recommendation model. For example, the system can learn that a user prefers to play white noise in a high-noise environment, and automatically apply this setting when encountering a similar environment in the future.

[0068] Among them, collaborative filtering is a recommendation system algorithm that predicts users' interest in unselected objects based on user behavior data. Its core idea is to use the similarity between users or objects to make recommendations; K-means is an unsupervised learning algorithm that is used to divide a data set into K clusters so that each data point belongs to the cluster center closest to it. Its goal is to minimize the sum of squared errors of data points within the cluster.

[0069] It should be noted that, in other embodiments, those skilled in the art may also use other analysis algorithms to analyze user preferences, and are not limited to collaborative filtering algorithms or K-means clustering.

[0070] For further information, see Figure 4 The driver and passenger information status includes at least the number of drivers and passengers and their position information in the vehicle; the adjustment strategy includes at least volume strategy, purity strategy and sense of space strategy.

[0071] The adjustment strategy for outputting the target sound effect library includes: Output a volume strategy according to the sound effect preference analysis result and / or the noise intensity.

[0072] Output a purity strategy according to the sound effect preference analysis result and / or the driving scene information.

[0073] And, output a spatial sense strategy in combination with the sound effect preference analysis result, and / or the number of the occupants, their position information in the vehicle and the ambient noise analysis result.

[0074] In some embodiments, the volume range is adjusted according to the classification results of the noise intensity, and then the corresponding volume strategy is output; wherein, when the noise intensity is detected to be at a medium level, the volume of the sound effect is set to moderate; under high noise conditions, the volume is appropriately increased to enhance the sense of immersion.

[0075] In the above technical solution, through multi-dimensional precise adjustment of volume, spatial sense and purity, the system can provide a highly personalized auditory experience to adapt to the preferences and needs of different users; real-time adjustment of volume and purity enables the system to respond quickly to environmental changes and provide consistent auditory comfort; and the output spatial sense strategy will combine the number of drivers and passengers and their position in the car to provide the best auditory positioning and immersion.

[0076] The purity is adjusted by noise reduction technology. Noise reduction technology improves the purity of sound output by reducing or eliminating background noise, making the main sound effect clearer. Among them, dynamic feedback noise reduction can be performed on environmental noise based on adaptive active noise control (ANC, Active Noise Control) technology. The dual noise reduction strategy of combining feedback ANC and feedforward ANC is adopted, which can effectively offset the low-frequency noise in the car and improve the clarity of sound effects.

[0077] Among them, ANC technology is a technology that offsets or reduces ambient noise by introducing secondary noise with a phase opposite to the original noise; based on the principle of sound wave interference, when two sound waves with opposite phases and similar amplitudes meet in the same space, they will cancel each other out, thereby reducing the overall noise level.

[0078] Furthermore, in some embodiments, the sense of space can be reflected through reverberation and surround sound; reverberation increases the sense of space of sound by simulating the reflection and attenuation of sound in different environments; surround sound distributes target sound effects to different speakers through a multi-channel system to create a three-dimensional auditory environment.

[0079] Among them, virtual surround sound technology (such as HRTF technology) is used to create an immersive sound field effect for users; the microphone array is combined to locate the user's head position, and the phase difference of the audio signals of the left and right channels is adjusted in real time to simulate the surround feeling of the real sound field.

[0080] It should be noted that HRTF (Head-Related Transfer Function) is a technology in the field of acoustics that is used to simulate the perception of sound by the human auditory system; HRTF simulates the process of sound propagating to the eardrum in space, so that the sound played through headphones or other audio devices can produce a sense of spatial positioning, thereby achieving a virtual surround sound effect. In other embodiments, those skilled in the art may also adopt other methods, such as 3D sound technology, and are not limited to this.

[0081] In addition, the reverberation effect is adjusted based on the results of environmental noise analysis. For example, the reverberation is enhanced in the case of rain noise to simulate the real environmental feeling of rain sound; and the reverberation is reduced in the case of high-frequency wind noise to ensure the clarity of the sound effect.

[0082] Furthermore, in other embodiments, the number of drivers and passengers and their position information in the vehicle can be obtained based on the camera or sensor in the vehicle to dynamically adjust the output balance of each speaker to ensure that every passenger can enjoy consistent sound effects; for example, when only the driver and passengers are in the car, the system will focus on the speaker output near the driver's seat and reduce the volume of other speakers.

[0083] Furthermore, the adjustment strategy also includes at least a frequency response strategy; in the process of adjusting the output parameters of the target sound effect library based on the volume strategy, purity strategy and spatial sense strategy, it also includes: real-time monitoring of the current noise frequency to output a frequency response strategy based on the noise frequency.

[0084] In some embodiments, the frequency response corresponds to equalization, where an equalizer changes the overall sound effect by gaining or attenuating specific frequencies.

[0085] Among them, the system dynamically adjusts the equalization parameters (such as low-frequency enhancement or high-frequency attenuation) in combination with the real-time noise frequency to optimize the frequency response of the sound effect. In a low-noise environment, the system enhances the high frequency to enhance the expression of details; in a high-noise environment, it increases the low frequency to offset external interference.

[0086] In other embodiments, the dynamic range and frequency response of the sound effects can be adjusted in real time in combination with the response characteristics of each speaker to ensure the details and depth of the sound effects, and dynamic compression can be automatically performed when the volume is too high to avoid distortion that damages the speakers.

[0087] Furthermore, the driver and occupant information state at least includes the driver and occupant's emotional state; and in the process of adjusting the output parameters of the target sound effect library according to the adjustment strategy, it also includes: The emotional state of the driver and passenger is acquired and analyzed in real time, so as to switch the target sound effect library based on the emotional state analysis result.

[0088] And / or collect control instructions from the driver and passengers in real time to switch the target sound effect library and / or adjust the output parameters according to the control instructions; wherein the control instructions are issued at least through voice, gesture or mobile application.

[0089] In some embodiments, by monitoring the emotional state of the driver and passengers (such as collecting heart rate, skin electricity and other data through biosensors), the system can adjust the type and style of sound effects in a timely manner, such as playing soothing white noise when in a tense state.

[0090] In addition, in other embodiments, sound effects switching, volume adjustment, etc. can be performed through voice commands; voice control uses natural language processing (NLP) technology to ensure that control commands issued by users can still be accurately recognized even when the noise level in the car is high.

[0091] Among them, NLP mainly receives and records voice signals after the user issues a voice control command, then converts the voice signal into text form, analyzes and understands the meaning of the text command, and recognizes the intention behind the user's voice control command, such as lowering the volume; finally, according to the recognized intention, the corresponding operation is performed. In addition, the execution results or system feedback can also be converted into voice signals and played to the user through the speaker.

[0092] When touch operation is inconvenient, users can control the system through preset gestures; for example, using simple gestures to wave in front of the central control camera can switch sound modes or pause playback.

[0093] It should be noted that these preset gestures are usually pre-configured and deployed by the system, and the user can learn them through the setting interface of the central control screen. In other embodiments, the user can also define the preset gestures by himself in the setting interface.

[0094] Furthermore, users can also remotely set sound preferences outside the car through the mobile application, or achieve convenient control while driving. At the same time, they can view driving history and sound preference data analysis reports through the application.

[0095] In the above technical solution, through various control methods such as voice, gestures and mobile applications, users can choose the most convenient operation method according to their habits and scenarios, which improves the convenience of interaction and user experience; non-contact operation methods such as voice and gesture control reduce the manual operation of drivers and passengers during driving, reduce the risk of distraction, and improve driving safety.

[0096] Furthermore, in the process of adjusting the output parameters of the target sound effect library according to the adjustment strategy, it also includes: The output parameters are recorded in combination with the environmental noise analysis results, the driving scene information, the driver and passenger information status and the control instruction to update the sound effect preference settings based on the output parameters.

[0097] In some embodiments, the user's historical adjustment behavior is analyzed to identify the user's preferences and habits, and new configuration suggestions are generated in combination with the current environmental noise analysis results, driving scene information, and driver and passenger information status, such as volume range, tone preference, etc.; the generated configuration suggestions are further applied to the sound effect preference settings, and the updated sound effect preference settings are stored in a database to form personalized sound effect settings.

[0098] In the above technical solution, by recording and updating the sound effect preference settings, the system can make personalized adjustments based on the user's actual usage, providing a more accurate and user-preferred sound effect experience; combining multi-dimensional information to record output parameters to ensure that the sound effect settings are accurately matched to the user's current status and needs, thereby improving the accuracy and personalization of the auditory experience.

[0099] Further, based on the same concept, see Figure 5 The present application also provides a sound effect adjustment system, the system comprising: The noise collection module is used to collect the internal and external environmental noise of the vehicle, analyze the environmental noise, and obtain environmental noise analysis results.

[0100] The sound effect acquisition module is used to monitor the driving scene of the vehicle in real time, obtain driving scene information, and match the target sound effect library in combination with the environmental noise analysis result and the driving scene information.

[0101] and a sound effect adjustment module, which is used to load the sound effect preference settings of the driver and passenger and / or identify the information status of the driver and passenger, output the adjustment strategy of the target sound effect library, and adjust the output parameters of the target sound effect library according to the adjustment strategy.

[0102] It should be noted that the specific implementation of the sound effect adjustment system can be found in the various steps and embodiments of the sound effect adjustment method, which will not be described in detail here.

[0103] In the above technical solution, through noise collection and analysis, the system can accurately identify the noise environment, make targeted sound effect adjustments, and improve the accuracy and personalization of the auditory experience; combined with driving scenarios, sound effect preferences and driver and passenger information, the system can optimize the sound effects in multiple dimensions and provide an auditory experience that is more in line with user needs and preferences; and users do not need to manually adjust the sound settings, the system automatically adjusts according to the current environment and user status, which simplifies user operations and improves user experience.

[0104] Furthermore, based on the same concept, the present application also provides a vehicle-mounted terminal, which includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the sound effect adjustment method.

[0105] In some embodiments, the memory and processor are interconnected via a bus; the processor may be one or more CPUs. When the processor is a CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor is used to control various functional modules of the vehicle terminal and process signals.

[0106] The memory includes but is not limited to RAM (Random Access Memory), ROM (Read-Only Memory), EPROM (Erasable Programmable Read-Only Memory), and CD-ROM (Compact Disc Read-Only Memory). The memory is used to store computer programs, operating systems, various applications and data, such as storing a computer program for implementing the sound effect adjustment method.

[0107] In summary, the present application provides a sound effect adjustment method, system and vehicle-mounted terminal; first, the internal and external environmental noise of the vehicle is collected, and the environmental noise is analyzed to obtain the environmental noise analysis results; then the driving scene of the vehicle is monitored in real time, the driving scene information is obtained, and the target sound effect library is matched in combination with the environmental noise analysis results and the driving scene information; further, the sound effect preference settings of the driver and passenger are loaded and / or the information status of the driver and passenger is identified, and the adjustment strategy of the target sound effect library is output, and the output parameters of the target sound effect library are adjusted according to the adjustment strategy. The present application can dynamically adjust the sound effects according to the real-time driving scene, as well as the sound effect preferences and / or information status of the driver and passenger, to provide a personalized and comfortable auditory experience; and there is no need for the user to manually adjust the sound effect settings, which simplifies the user's operating burden and improves the user experience.

[0108] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely exemplary and are not intended to limit the scope of the present application to this. Those of ordinary skill in the art may make various changes and modifications therein without departing from the scope and spirit of the present application. All these changes and modifications are intended to be included within the scope of the present application as required by the appended claims.

[0109] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0110] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0111] The various component embodiments of the present application can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some modules according to the embodiments of the present application. The application can also be implemented as a device program (e.g., computer program and computer program product) for executing a part or all of the methods described herein. Such a program implementing the present application can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0112] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0113] Although the description of the present application is carried out in conjunction with the above specific embodiments, it is obvious that those skilled in the art can make many substitutions, modifications and changes according to the above content. Therefore, all such substitutions, improvements and changes are included in the spirit and scope of the appended claims.

Claims

1. A sound effect adjustment method, characterized in that: The following steps are involved: Collecting the internal and external environmental noise of the vehicle, and analyzing the environmental noise to obtain environmental noise analysis results; Monitor the driving scene of the vehicle in real time, obtain driving scene information, and match the target sound effect library in combination with the environmental noise analysis result and the driving scene information; Load the sound effect preference settings of the driver and occupant and / or identify the information status of the driver and occupant, output the adjustment strategy of the target sound effect library, and adjust the output parameters of the target sound effect library according to the adjustment strategy.

2. The sound effect adjustment method according to claim 1, characterized in that: The obtaining of the environmental noise analysis result includes: Filtering the environmental noise to obtain target noise, and obtaining a noise source of the target noise based on a deep learning model; And, obtaining noise intensity according to the target noise.

3. The sound effect adjustment method according to claim 1, characterized in that: The driving scene information includes at least weather information, road condition information and driving mode information; The matching target sound effect library includes: The target sound effect library is matched in combination with the noise source, weather information, road condition information and the driving mode information.

4. The sound effect adjustment method according to claim 1, characterized in that: After loading the driver's audio preferences, including: The sound effect preference setting is analyzed to obtain a sound effect preference analysis result.

5. The sound effect adjustment method according to any one of claims 2 and 4, characterized in that: The driver and passenger information state includes at least the number of drivers and passengers and their position information in the vehicle; the adjustment strategy includes at least a volume strategy, a purity strategy and a sense of space strategy; The adjustment strategy for outputting the target sound effect library includes: Outputting a volume strategy according to the sound effect preference analysis result and / or the noise intensity; Outputting a purity strategy according to the sound effect preference analysis result and / or the driving scene information; And, a spatial perception strategy is output in combination with the sound effect preference analysis result, and / or the number of the occupants, their position information in the vehicle and the ambient noise analysis result.

6. The sound effect adjustment method according to claim 5, characterized in that: The adjustment strategy at least includes a frequency response strategy; in the process of adjusting the output parameters of the target sound effect library based on the volume strategy, the purity strategy and the spatial sense strategy, it also includes: The current noise frequency is monitored in real time to output a frequency response strategy according to the noise frequency.

7. The sound effect adjustment method according to claim 6, characterized in that: The driver and occupant information state at least includes the driver and occupant's emotional state; in the process of adjusting the output parameters of the target sound effect library according to the adjustment strategy, it also includes: Acquire and analyze the emotional state of the driver and passenger in real time, so as to switch the target sound effect library based on the emotional state analysis result; And / or collect control instructions from the driver and passengers in real time to switch the target sound effect library and / or adjust the output parameters according to the control instructions; wherein the control instructions are issued at least through voice, gesture or mobile application.

8. The sound effect adjustment method according to claim 7, characterized in that: In the process of adjusting the output parameters of the target sound effect library according to the adjustment strategy, it also includes: The output parameters are recorded in combination with the environmental noise analysis results, the driving scene information, the driver and passenger information status and the control instruction to update the sound effect preference settings based on the output parameters.

9. A sound effect adjustment system, characterized in that: The sound effect adjustment method according to any one of claims 1 to 8 is adopted, wherein the sound effect adjustment system comprises: A noise collection module is used to collect the internal and external environmental noise of the vehicle, analyze the environmental noise, and obtain environmental noise analysis results; A sound effect acquisition module, used to monitor the driving scene of the vehicle in real time, obtain driving scene information, and match the target sound effect library in combination with the environmental noise analysis result and the driving scene information; and a sound effect adjustment module, which is used to load the sound effect preference settings of the driver and passenger and / or identify the information status of the driver and passenger, output the adjustment strategy of the target sound effect library, and adjust the output parameters of the target sound effect library according to the adjustment strategy.

10. A vehicle-mounted terminal, characterized in that: The vehicle-mounted terminal includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the sound effect adjustment method described in any one of claims 1-8.

Images