Vehicle music playing method and device, electronic equipment and storage medium

Abstract

The invention discloses a vehicle music playing method and device, electronic equipment and a storage medium. The method comprises the steps of collecting real-time driving behavior data of a current vehicle in a current driving process; inputting the real-time driving behavior data into a pre-trained music generation model, and outputting a current music clip matched with the real-time driving behavior data for the current vehicle; and combining the current music clip with the current basic music to realize music playing. According to the technical scheme, the music playing individuation and interactivity are enhanced, and the driving experience is improved.

Description

[0001] The priority information claimed by this application is: Application Number: 202411415778.9, Application Name: A Method, Device, Electronic Device and Storage Medium for Playing Music in a Vehicle, Application Date: 2024.10.11 Technical Field

[0002] The present invention relates to the field of artificial intelligence technology, and in particular to a method, device, electronic device and storage medium for playing vehicle music. Background Art

[0003] With the development of artificial intelligence (AI), deep learning has made significant progress in the field of music generation. Existing music generation technologies primarily focus on static music creation and lack real-time interaction with user behavior. While music is a crucial element in enhancing the driving experience, traditional in-car music systems are independent of driving behavior. Summary of the Invention

[0004] The present invention provides a method, device, electronic device and storage medium for playing music in a vehicle, so as to enhance the personalization and interactivity of music playing and improve the driving experience.

[0005] According to one aspect of the present invention, a method for playing music in a vehicle is provided, the method comprising:

[0006] Collect real-time driving behavior data of the current vehicle during the current driving process;

[0007] Inputting the real-time driving behavior data into a pre-trained music generation model, and outputting a current music clip matching the real-time driving behavior data for the current vehicle;

[0008] The current music clip is combined with the current basic music to achieve music playback.

[0009] According to another aspect of the present invention, a device for playing music in a vehicle is provided, the device comprising:

[0010] Driving behavior data collection module, used to collect real-time driving behavior data of the current vehicle during the current driving process;

[0011] a music clip output module, configured to input the real-time driving behavior data into a pre-trained music generation model and output a current music clip for the current vehicle that matches the real-time driving behavior data;

[0012] The music playing module is used to combine the current music clip with the current basic music to achieve music playing.

[0013] According to another aspect of the present invention, an electronic device is provided, comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the vehicle music playing method described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle music playing method described in any embodiment of the present invention when executed.

[0018] The technical solution of the embodiment of the present invention collects real-time driving behavior data of the current vehicle during the current driving process; inputs the real-time driving behavior data into a pre-trained music generation model to output a current music clip that matches the real-time driving behavior data for the current vehicle; combines the current music clip with the current basic music to achieve music playback, and adopts technical means to achieve music playback in real-time interaction with driving behavior. This solves the problem that traditional in-vehicle music systems are independent of driving behavior, which limits the personalization and interactivity of the driving experience, enhances the personalization and interactivity of music playback, and improves the driving experience.

[0019] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 This is a flow chart of a method for playing music in a vehicle provided in Example 1 of the present invention;

[0022] Figure 2 A schematic structural diagram of a vehicle music playback device provided in a third embodiment of the present invention;

[0023] Figure 3The present invention is a schematic structural diagram of an electronic device for implementing the vehicle music playing method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described 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 making creative efforts should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] Example 1

[0027] Figure 1 This is a flow chart of a method for playing music in a vehicle provided by the first embodiment of the present invention. This embodiment is applicable to playing music while driving a vehicle. The method can be executed by a vehicle music playing device. The vehicle music playing device can be implemented in the form of hardware and / or software. The vehicle music playing device can be configured in the vehicle main controller. Figure 1 As shown, the method includes:

[0028] S110: Collect real-time driving behavior data of the current vehicle during the current driving process.

[0029] The real-time driving behavior data may refer to the driving parameters of each component of the current vehicle during the current driving process.

[0030] Optionally, real-time driving behavior data may also include but is not limited to:

[0031] Vehicle driving status: including whether the vehicle is in an unmanned driving state. This is an important signal in the vehicle control unit (VCU) because it affects the vehicle's control of safety mechanisms such as the accelerator and brakes.

[0032] Vehicle speed: The real-time speed of the vehicle, which is crucial for driving safety and vehicle control.

[0033] Accelerator pedal opening: The degree to which the driver operates the accelerator pedal affects the acceleration of the vehicle.

[0034] Brake pedal status: The driver's operation status of the brake pedal affects the vehicle's deceleration or parking.

[0035] Steering wheel angle: The degree to which the driver operates the steering wheel, which is directly related to the vehicle's steering behavior.

[0036] Door status: Whether the door is closed or not affects vehicle safety and certain functions of the vehicle control system.

[0037] Window status: The open or closed status of the window may affect the vehicle's interior environmental control system.

[0038] Headlight status: Whether the headlights are on or off affects your driving vision at night or in bad weather.

[0039] Turn signal status: The status of the vehicle's turn signal, which communicates the vehicle's intention to turn to other road users.

[0040] Airbag Status: The deployment status of the airbag, which is related to the vehicle's passive safety systems.

[0041] Mileage: The total mileage of the vehicle, which is of reference value for maintenance and vehicle performance monitoring.

[0042] ACC (Adaptive Cruise Control) button status: the activation status of the adaptive cruise control system.

[0043] LKA (Lane Keeping Assist) button status: activation status of the lane keeping assist system.

[0044] GPS (Global Positioning System) information: The vehicle's global positioning system information is crucial for navigation and vehicle positioning.

[0045] Engine status: including engine speed, output torque, fuel consumption, etc., which is of great significance to vehicle performance and maintenance.

[0046] Tire pressure: The air pressure status of each tire affects driving safety and vehicle handling stability.

[0047] Battery Charge: The state of charge of the vehicle's battery, especially important for electric or hybrid vehicles.

[0048] Vehicle driving mode: The vehicle's driving mode, such as sports mode, economy mode, etc., affects the vehicle's performance.

[0049] In this embodiment, the real-time driving behavior data of the current vehicle during the current driving process may be collected in full, or may be collected according to a pre-set requirement list.

[0050] Optionally, before collecting the real-time driving behavior data of the current vehicle during the current driving process, the method may further include: determining current basic music for the current vehicle when the current vehicle starts to drive.

[0051] The current basic music may be the basic music played by the current vehicle during the entire current driving process. For example, the basic music may be cheerful, dynamic, lyrical, and the like.

[0052] The current basic music may be determined based on user needs, or may be automatically determined based on historical user habits or randomly determined without the user issuing an instruction.

[0053] In one scenario, determining the current base music for the current vehicle may include: responding to a first user instruction, determining the current base music from a base music library, where each base music in the base music library is pre-generated by a pre-trained music generation model; or responding to a second user instruction, generating the current base music for the current vehicle in real time using a pre-trained music generation model. The first user instruction may be an instruction to select base music from the base music library, while the second user instruction may be an instruction to generate base music for the pre-trained music generation model. In other words, in this scenario, the current base music may be pre-generated or generated in real time.

[0054] In another case, if the vehicle has been driving for a period of time and has not received any user commands, the current base music for the vehicle can be determined based on historical user habits. For example, the base music that has been played most frequently during a number of historical driving sessions can be determined as the current base music.

[0055] In another case, if the current vehicle has not received any user instructions after starting to drive for a period of time, the current basic music for the current vehicle can be randomly determined from the basic music library, or the current basic music can be randomly generated for the current vehicle through a pre-trained music generation model.

[0056] S120: Input the real-time driving behavior data into a pre-trained music generation model, and output a current music clip that matches the real-time driving behavior data for the current vehicle.

[0057] Among them, the pre-trained music generation model may include a basic music generation sub-model and a music clip generation sub-model.

[0058] Optionally, the basic music generation sub-model is obtained by training basic music sample data for at least one round. The basic music sample data may include music clips of different styles and emotions. In this embodiment, a model can be trained to generate basic music. This model can be a pre-trained deep learning model, such as a VAE (Variational Autoencoder) or a GAN (Generative Adversarial Network). The basic music generation sub-model can learn the general structure and style of music without being directly associated with specific driving behaviors.

[0059] Optionally, the music clip generation sub-model is pre-trained in the following manner: obtaining driving behavior sample data, music clip sample data, driving behavior verification data and music clip verification data; training the initial music clip generation sub-model based on the driving behavior sample data and the music clip sample data to optimize the parameters of the initial music clip generation sub-model to obtain an optimized music clip generation sub-model; evaluating the performance of the optimized music clip generation sub-model based on the driving behavior verification data and the music clip verification data, and fine-tuning the optimized music clip generation sub-model based on the evaluation results to obtain the music clip generation sub-model.

[0060] It can be understood that the initial music clip generation sub-model is first preliminarily trained using the training dataset, and then the performance of the preliminarily trained music clip generation sub-model is verified using the verification dataset (using indicators such as accuracy, recall rate or F1 score, etc.), and the sub-model is fine-tuned according to the verification results.

[0061] In an optional embodiment, the initial music clip generation sub-model is trained based on the driving behavior sample data and the music clip sample data to optimize the parameters of the initial music clip generation sub-model to obtain the optimized music clip generation sub-model, which may include: using the initial music clip generation sub-model to extract the first feature of the driving behavior sample data and the second feature of the music clip sample data; training the initial music clip generation sub-model based on the first feature and the second feature to map the first feature to the second feature and generate a music clip matching the first feature; and optimizing the parameters of the initial music clip generation sub-model through a back propagation algorithm based on the music clip matching the first feature to obtain the optimized music clip generation sub-model.

[0062] The first feature of the driving behavior sample data may refer to features such as acceleration and braking frequency, and the second feature of the music clip sample data may refer to features such as pitch, rhythm, and timbre.

[0063] In this embodiment, a deep learning model, such as an RNN or LSTM, can be used to learn the long-term dependencies between driving behavior and music. Specifically, the model can be trained using the first feature of the driving behavior sample data and the second feature of the music clip sample data. The model parameters can be optimized using a backpropagation algorithm. For example, model hyperparameters such as the learning rate, batch size, and number of training rounds can be adjusted to improve model performance.

[0064] Optionally, user feedback on the music clip generation sub-model may be obtained; and the music clip generation sub-model may be iteratively improved based on the user feedback.

[0065] In this embodiment, a user feedback function can be provided. After using this feedback function, users can complete a questionnaire survey, for example, to rate the music style, music clip 1, and music clip 2. Users can also enter their opinions (for example, by voice input and then recognizing user opinions, such as suggestions for improvement of the music style and music clips). User satisfaction can be surveyed through user feedback. This can be understood as collecting user feedback on the music generated by the optimized music clip generation sub-model to evaluate the actual effectiveness of the model, thereby iterating and improving the model based on user feedback.

[0066] Optionally, the trained music generation model can be deployed on the device side, that is, deployed in the actual vehicle system, or deployed in the cloud, that is, deployed on a cloud computing server, so that it can respond to driving behavior and generate music in real time.

[0067] The current music clip in this embodiment can be a driving sound effect corresponding to the driving behavior data, or it can be music with a rhythm that matches the driving behavior data. In short, the current music clip can make the driver of the current vehicle feel better.

[0068] S130: Combine the current music clip with the current basic music to achieve music playback.

[0069] In this embodiment, after the current driving process of the current vehicle begins, the current basic music starts playing. When driving behavior data is detected, the current music clip corresponding to the driving behavior data can be added to the basic music to achieve a personalized music playback experience.

[0070] The technical solution of the embodiment of the present invention collects real-time driving behavior data of the current vehicle during the current driving process; inputs the real-time driving behavior data into a pre-trained music generation model to output a current music clip that matches the real-time driving behavior data for the current vehicle; combines the current music clip with the current basic music to achieve music playback, and adopts technical means to achieve music playback in real-time interaction with driving behavior. This solves the problem that traditional in-vehicle music systems are independent of driving behavior, which limits the personalization and interactivity of the driving experience, enhances the personalization and interactivity of music playback, and improves the driving experience.

[0071] Example 2

[0072] Figure 2 This is a structural diagram of a vehicle music player provided by the third embodiment of the present invention. Figure 2 As shown, the device includes: a driving behavior data collection module 210, a music clip output module 220 and a music playing module 230. Among them:

[0073] The driving behavior data collection module 210 is used to collect real-time driving behavior data of the current vehicle during the current driving process;

[0074] a music clip output module 220 for inputting the real-time driving behavior data into a pre-trained music generation model and outputting a current music clip for the current vehicle that matches the real-time driving behavior data;

[0075] The music playing module 230 is configured to combine the current music clip with the current basic music to achieve music playing.

[0076] The technical solution of the embodiment of the present invention collects real-time driving behavior data of the current vehicle during the current driving process; inputs the real-time driving behavior data into a pre-trained music generation model to output a current music clip that matches the real-time driving behavior data for the current vehicle; combines the current music clip with the current basic music to achieve music playback, and adopts technical means to achieve music playback in real-time interaction with driving behavior. This solves the problem that traditional in-vehicle music systems are independent of driving behavior, which limits the personalization and interactivity of the driving experience, enhances the personalization and interactivity of music playback, and improves the driving experience.

[0077] Optionally, the vehicle music playback device further includes a current basic music determination module, which is configured to, before collecting real-time driving behavior data of the current vehicle during the current driving process:

[0078] When the current vehicle starts to travel, the current basic music is determined for the current vehicle.

[0079] Optionally, the current basic music determination module can be used to:

[0080] In response to a first user instruction, determining the current basic music from a basic music library, each basic music in the basic music library being pre-generated by the pre-trained music generation model; or

[0081] In response to a second user instruction, the current basic music is generated in real time for the current vehicle through the pre-trained music generation model.

[0082] Optionally, the pre-trained music generation model includes a basic music generation sub-model and a music clip generation sub-model.

[0083] Optionally, the basic music generation sub-model is obtained by training basic music sample data for at least one round, wherein the basic music sample data includes music clips of different styles and emotions;

[0084] The music clip generation sub-model is pre-trained in the following way:

[0085] Acquire driving behavior sample data, music clip sample data, driving behavior verification data, and music clip verification data;

[0086] Training an initial music clip generation sub-model based on the driving behavior sample data and the music clip sample data to optimize parameters of the initial music clip generation sub-model to obtain an optimized music clip generation sub-model;

[0087] The performance of the optimized music clip generation sub-model is evaluated based on the driving behavior verification data and the music clip verification data, and the optimized music clip generation sub-model is fine-tuned based on the evaluation results to obtain the music clip generation sub-model.

[0088] Optionally, the vehicle music playback device further includes an optimized music clip generation sub-model acquisition module, which is used to:

[0089] extracting a first feature of the driving behavior sample data and a second feature of the music segment sample data using an initial music segment generation sub-model;

[0090] Training the initial music clip generation sub-model according to the first feature and the second feature to map the first feature to the second feature and generate a music clip matching the first feature;

[0091] According to the music clip that matches the first feature, the parameters of the initial music clip generation sub-model are optimized by a back propagation algorithm to obtain an optimized music clip generation sub-model.

[0092] Optionally, the vehicle music playback device further includes a music clip generation sub-model improvement module, which is used to:

[0093] Obtaining user feedback on generating a sub-model for the music clip;

[0094] The music clip generation sub-model is iteratively improved according to the user feedback.

[0095] The vehicle music playback device provided in the embodiment of the present invention can execute the vehicle music playback method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0096] Example 3

[0097] Figure 3 A schematic diagram of an electronic device 300 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers or various forms of mobile devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0098] like Figure 3 As shown, the electronic device 300 includes at least one processor 301, and a memory connected to the at least one processor 301, such as a read-only memory (ROM) 302, a random access memory (RAM) 303, etc., wherein the memory stores a computer program that can be executed by the at least one processor, and the processor 301 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 302 or the computer program loaded from the storage unit 308 to the random access memory (RAM) 303. Various programs and data required for the operation of the electronic device 300 can also be stored in the RAM 303. The processor 301, ROM 302 and RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0099] Multiple components in the electronic device 300 are connected to the I / O interface 305, including an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a magnetic disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0100] Processor 301 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 301 executes the various methods and processes described above, such as the method for playing music in a vehicle.

[0101] In some embodiments, the method for playing music in a vehicle may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the processor 301, one or more steps of the method for playing music in a vehicle described above may be performed. Alternatively, in other embodiments, the processor 301 may be configured to execute the method for playing music in a vehicle by any other appropriate means (e.g., by means of firmware).

[0102] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0103] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0104] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0105] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0106] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0107] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0108] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0109] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for playing music in a vehicle, characterized in that: include: Collect real-time driving behavior data of the current vehicle during the current driving process; Inputting the real-time driving behavior data into a pre-trained music generation model, and outputting a current music clip matching the real-time driving behavior data for the current vehicle; The current music clip is combined with the current basic music to achieve music playback.

2. The method according to claim 1, characterized in that Before collecting the real-time driving behavior data of the current vehicle during the current driving process, it also includes: When the current vehicle starts to travel, the current basic music is determined for the current vehicle.

3. The method according to claim 2, characterized in that Determining the current basic music for the current vehicle includes: In response to a first user instruction, determining the current basic music from a basic music library, each basic music in the basic music library being pre-generated by the pre-trained music generation model; or In response to a second user instruction, the current basic music is generated in real time for the current vehicle through the pre-trained music generation model.

4. The method according to claim 1, wherein The pre-trained music generation model includes a basic music generation sub-model and a music clip generation sub-model.

5. The method according to claim 4, characterized in that The basic music generation sub-model is obtained by training basic music sample data for at least one round, wherein the basic music sample data includes music clips of different styles and emotions; The music clip generation sub-model is pre-trained in the following way: Acquire driving behavior sample data, music clip sample data, driving behavior verification data, and music clip verification data; Training an initial music clip generation sub-model based on the driving behavior sample data and the music clip sample data to optimize parameters of the initial music clip generation sub-model to obtain an optimized music clip generation sub-model; The performance of the optimized music clip generation sub-model is evaluated based on the driving behavior verification data and the music clip verification data, and the optimized music clip generation sub-model is fine-tuned based on the evaluation results to obtain the music clip generation sub-model.

6. The method according to claim 5, characterized in that Training an initial music clip generation sub-model based on the driving behavior sample data and the music clip sample data to optimize parameters of the initial music clip generation sub-model to obtain an optimized music clip generation sub-model, including: extracting a first feature of the driving behavior sample data and a second feature of the music segment sample data using an initial music segment generation sub-model; Training the initial music clip generation sub-model according to the first feature and the second feature to map the first feature to the second feature and generate a music clip matching the first feature; According to the music clip that matches the first feature, the parameters of the initial music clip generation sub-model are optimized by a back propagation algorithm to obtain an optimized music clip generation sub-model.

7. The method according to claim 5, characterized in that Also includes: Obtaining user feedback on generating a sub-model for the music clip; The music clip generation sub-model is iteratively improved according to the user feedback.

8. A vehicle music playing device, characterized in that: include: Driving behavior data collection module, used to collect real-time driving behavior data of the current vehicle during the current driving process; a music clip output module, configured to input the real-time driving behavior data into a pre-trained music generation model and output a current music clip for the current vehicle that matches the real-time driving behavior data; The music playing module is used to combine the current music clip with the current basic music to achieve music playing.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the vehicle music playing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle music playing method according to any one of claims 1 to 7 when executed.

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