Method for generating in-car music, electronic device, computer-readable storage medium, and computer program

Abstract

This provides a method for generating in-car music. [Solution] This method includes collecting scene data during the vehicle driving process 202. This method further includes generating vehicle scene prompt words 204 based on the scene data, and generating in-car music 206 based on the vehicle scene prompt words. By using this method, it is possible to automatically generate and play music for scenes corresponding to environmental changes during the driving process, thereby improving the driver's driving experience.

Description

Technical Field

[0001] Embodiments of the present disclosure generally relate to the field of vehicles, and more specifically to a method, an electronic device, a medium, and a program product for generating in-vehicle music.

Background Art

[0002] With the development of technology, in-vehicle entertainment functions have emerged one after another, and the in-vehicle entertainment system has already become an important component for enhancing the driving experience. By means of the computing power and ecosystem of in-vehicle resources or mobile phones, hardware resources or software resources such as in-vehicle displays and audio systems in vehicle devices are called to provide users with visual and auditory entertainment experiences.

[0003] Through intelligent music playback, the in-vehicle music system can reduce driving fatigue, improve the mood stability of drivers, and provide better entertainment support for long-distance driving. With the in-vehicle entertainment function, the vehicle is transformed from a mere means of transportation into a mobile music entertainment space, enabling users to enhance their user experience while driving a smart car.

Summary of the Invention

Problems to be Solved by the Invention

[0004] Embodiments of the present disclosure are used in a method, an electronic device, a medium, and a computer program product for generating in-vehicle music.

Means for Solving the Problems

[0005] According to a first aspect of the present disclosure, a method for generating in-vehicle music is provided, the method including collecting scene data during a vehicle driving process. The method further includes generating a vehicle scene prompt word based on the scene data, and generating the in-vehicle music based on the vehicle scene prompt word.

[0006] According to a second aspect of the present disclosure, an electronic device for generating in-car music is provided, the electronic device comprising a processor and a memory coupled to the processor and storing instructions, wherein when these instructions are executed by the processor, the device is made to perform steps of the method for generating in-car music according to an embodiment of the present disclosure.

[0007] According to a third aspect of the present disclosure, a computer-readable storage medium is provided which stores computer-executable instructions, and when these computer-executable instructions are executed, the computer is caused to perform steps of a method for generating in-car music according to an embodiment of the present disclosure.

[0008] A fourth aspect of the present disclosure provides a computer program product which is substantially stored on a non-volatile computer-readable medium and includes machine-executable instructions which, when executed, cause a machine to perform steps of a method for generating in-vehicle music according to an embodiment of the present disclosure.

[0009] It should be noted that the summary of the invention is provided in a simplified form to introduce some concepts, which are further described in the specific embodiments below. The summary portion of the invention is not intended to identify any important or necessary features of the disclosure, nor is it intended to limit the scope of the disclosure. [Brief explanation of the drawing]

[0010] The exemplary embodiments of this disclosure will be described in more detail with reference to the drawings, and the above and other purposes, features and advantages of this disclosure will be made clearer, as shown in the drawings. [Figure 1] Figure 1 is a schematic diagram illustrating an exemplary application scene of the method for in-car music according to an embodiment of the present disclosure. [Figure 2] Figure 2 shows a flowchart of a method for generating in-car music according to an embodiment of the present disclosure. [Figure 3]Figure 3 shows a schematic diagram of a method for generating in-car music according to an embodiment of the present disclosure. [Figure 4] Figure 4 shows a schematic block diagram of equipment that may be used to carry out an embodiment of the present disclosure. [Modes for carrying out the invention]

[0011] Currently, the exemplary embodiments are described more comprehensively with reference to the drawings. However, the exemplary embodiments can be carried out in various forms and should not be understood as being limited to the embodiments described herein. On the contrary, the provision of these embodiments makes this application comprehensive and complete and fully communicates the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings represent the same or similar parts, and their repeated descriptions are omitted.

[0012] Furthermore, the described features, structures, or characteristics can be combined in one or more embodiments in any suitable manner. The following description provides numerous specific details to give a thorough understanding of the embodiments of this application. However, those skilled in the art will be aware that the technical proposal of this application can be implemented without one or more of the specific details, or that other methods, assemblies, apparatus, steps, etc., can be employed. In other cases, known methods, apparatus, implementations, or operations are not illustrated or described in detail to avoid obscuring the embodiments of this application.

[0013] In the descriptions of the embodiments of this disclosure, the term “including” and its variations should be understood as open inclusion, i.e., “including, but not limited to.” The term “based on” should be understood as “based at least partially.” The term “one embodiment” or “this embodiment” should be understood as “at least one embodiment.” While various assemblies may be described using the terms first, second, third, etc., these assemblies should not be limited by these terms. These terms are used to distinguish one assembly from another. Thus, the first assembly discussed below may be called the second assembly without departing from the teaching of the concepts of this application. As used herein, the terms “and / or” and similar terms include all combinations of any one, more, and all of the related items listed.

[0014] The block diagrams shown in the drawings represent only functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0015] The flowchart shown in the diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor is it necessarily executed in the order described. For example, some operations / steps can be broken down, while others can be combined or partially combined, so the actual execution order may change depending on the actual situation.

[0016] With the proliferation of smart in-car systems, users have higher demands for their driving experience. Traditional music playback methods often fail to meet users' musical needs in specific driving scenarios. For example, a user might want to listen to soft music when driving in the rain, or prefer dynamic music while driving on the highway. Currently, most in-car music systems play music either on a fixed, pre-set playlist loop or based on user selection. Such methods cannot respond in real time to changes in the external environment or the driver's mood, lacking personalization and real-time responsiveness to scene-specific playback.

[0017] To address at least the above and other potential problems, embodiments of the present disclosure provide a method for generating in-vehicle music. This method includes collecting scene data during a vehicle driving process. This method further includes generating vehicle scene prompt words based on the scene data and generating in-vehicle music based on the vehicle scene prompt words. By using this method, it is possible to automatically generate and play music for scenes corresponding to environmental changes during the driving process, thereby improving the driver's driving experience.

[0018] The basic principles and several exemplary implementations of this disclosure will be described below with reference to the following drawings. It should be understood that these exemplary embodiments are provided solely to enable those skilled in the art to better understand and further implement embodiments of this disclosure and are not intended to limit the scope of this disclosure in any way.

[0019] Figure 1 is a schematic diagram of an exemplary application scene of a method for generating in-vehicle music according to an embodiment of the present disclosure. As shown in Figure 1, the exemplary environment 100 includes a vehicle 110 on which elements or assemblies such as an in-vehicle equipment controller display 120, a smart speaker 130, vehicle lights 140, and seats 150 are arranged. It should be understood that the elements shown in Figure 1 are exemplary, and the vehicle 110 may include more or fewer elements or assemblies, and the present disclosure is not limited thereto.

[0020] The vehicle's display 120 can display and control each function of the in-car music system in real time. By touching the display 120, the driver can select a music playback mode, view the currently playing track, adjust the volume, and set music preferences. The display 120 is also connected to in-car sensors and an AI analysis module, and can present music recommendations related to the vehicle's driving data in real time.

[0021] In some embodiments, the in-vehicle device controller may include an AIGC (Artificial Intelligence Generated Content) music generation model for generating and adjusting music. For example, the music generation model may be a deep learning-based music generation model (e.g., based on a recurrent neural network (RNN), a transformer model, a generative adversarial network (GAN), or a variational autoencoder (VAE)) that can generate music segments with a time-series structure by learning from a large amount of music sample data, ensuring that the generated music has consistency and rhythm.

[0022] In some embodiments, the music generation model in the in-vehicle device controller may be a music generation model based on style transfer, which can transfer the characteristics of a certain music style (e.g., rhythm, timbre) to another music content. For example, the music generation model can select to apply the music style registered by the driver as a favorite to the currently playing in-vehicle music, so as to make the generated music more personalized and conform to the driver's current mood.

[0023] In some embodiments, the music generation model in the in-vehicle device controller may be based on a lyric generation model, which can generate lyric content matching the music style. In some embodiments, the music generation model in the in-vehicle device controller may be a personalized recommendation model based on user preferences. By analyzing the user's music preferences, playback history records and behavioral data, personalized music content is recommended. Additionally or alternatively, the music generation model in the in-vehicle device controller may be a combination of one or more of the music generation models described above, and the present disclosure places no restrictions thereon.

[0024] Inside the vehicle 110, the smart speaker 130 can support high-quality music playback, and the in-vehicle device controller can also dynamically adjust the acoustic effects based on the vehicle's environmental data through the smart speaker 130. For example, the smart speaker 130 can automatically optimize the volume and acoustic effect settings according to the vehicle's driving speed, the number of passengers in the vehicle, and the currently playing music type, so as to ensure the user experience of each passenger in the vehicle 110.

[0025] For example, in some embodiments, when it is detected that the vehicle 110 is driving on a highway, the in-vehicle device controller can reinforce the low-frequency and mid-frequency acoustic effects through the smart speaker 130, and make the rhythm of the music stronger and clearer, so as to keep the driver awake and focused on driving.

[0026] Additionally or alternatively, in some embodiments, when the driver is detected to be in a conference call or interacting with passengers in the vehicle, the in-vehicle equipment controller can control the smart speaker 130 to emphasize human voices and high-frequency components, providing a more pleasant auditory experience. In some embodiments, the in-vehicle equipment controller can provide adaptive functionality via the smart speaker 130, adjusting the volume distribution based on the number and location of passengers in the vehicle to ensure that all passengers have a balanced sound experience.

[0027] According to some embodiments of this disclosure, the vehicle 110 may further include various sensors and / or monitors (not shown) for collecting scene data during the vehicle's operation. The integration of these sensors and monitors allows the vehicle 110 to provide fundamental information for the analysis, generation, and adjustment of in-vehicle music by acquiring multidimensional data related to driving in real time. For example, in some embodiments, the vehicle 110 may have one or more camera sensors (internal cameras and / or external cameras) mounted inside the cabin and outside the vehicle body. The internal cameras may be used to capture driver motion and facial expression data.

[0028] For example, an interior camera in the vehicle 110 can detect the driver's facial expressions, eye opening, and head movements via the in-vehicle camera, analyze the driver's mood (e.g., driver's concentration, fatigue, tension, etc.), and match music content to the driver's mood. An external camera may be used to determine environmental images outside the vehicle, such as the road ahead, surrounding vehicles and pedestrians, and provide visualization information about the driving environment of the vehicle 110.

[0029] In some embodiments, the vehicle 110 may have audio sensors that can capture audio data from inside and outside the vehicle. For example, in-vehicle audio sensors may be used to detect voice commands from the driver and passengers, changes in tone, and background noise inside the vehicle. By analyzing this audio data, the in-vehicle equipment controller can dynamically adjust the type of music to play by analyzing the content of conversations and mood expressions inside the vehicle.

[0030] For example, in some embodiments, if the volume of conversation inside the vehicle increases and the tone of voice becomes tense, the in-vehicle equipment controller may select to play or generate pleasant background music to alleviate the tense atmosphere. In some embodiments, an external sound sensor may be used to help the system adjust the music volume based on the external noise level by determining external ambient noise, such as traffic noise or alarm sounds, to ensure that passengers inside the vehicle can hear the music clearly.

[0031] In some embodiments, the vehicle 110 may include a speed sensor for recording the vehicle's speed in real time. For example, if the speed sensor detects that the vehicle is traveling at high speed, the in-vehicle device controller may select to play or generate more rhythmic music, and if the speed sensor detects that the vehicle is traveling at low speed or in traffic, the in-vehicle device controller may play calmer music to soothe the driver. In some embodiments, the in-vehicle device controller may analyze the driver's driving style based on the speed sensor data and generate personalized music content that suits the driving style.

[0032] In some embodiments, the vehicle 110 may have a GPS positioning sensor for providing geographic location information. The in-vehicle device controller can generate music adapted to the current geographic location based on the GPS positioning sensor. For example, when the vehicle enters a rural road area, the in-vehicle device controller can play or generate matching rural music. When some of the vehicles 110 according to this disclosure are traveling on urban roads, the in-vehicle device controller can play or generate urban-themed music. Furthermore, the in-vehicle device controller can predict future driving scenes using GPS data and generate music in advance that is suitable for the driving scene that is about to be entered.

[0033] Additionally or alternatively, in some embodiments, the vehicle 110 may have (multiple) weather sensors, including a temperature sensor, a humidity sensor, a rain sensor, and a light sensor. These sensors allow the in-vehicle equipment controller to detect current weather conditions in real time, such as sunny, cloudy, rainy, or snowy, and to determine the type of music and sound effects based on this weather data. For example, in some embodiments, on a rainy day, the in-vehicle equipment controller may play or generate a pleasant piano piece or jazz, while on a sunny day, it may play or generate a brighter type of music to enhance the driver's enjoyment.

[0034] In some embodiments, the vehicle lights 140 can be synchronized with in-car music. For example, an in-car equipment controller can control the vehicle lights 140 to dynamically flash or change color based on the rhythm of the music currently being played, thereby enhancing the visual effect of the music. For instance, when playing fast-paced electronic music, the vehicle lights 140 can be made to flash in sync. On the other hand, when playing soothing background music, the vehicle lights 140 can be converted to a soft light.

[0035] Additionally or alternatively, in some embodiments, the in-vehicle equipment controller can control the seat 150 to generate synchronous vibration feedback based on the rhythm and frequency of the music currently being played. For example, when the smart speaker 130 plays music with a strong rhythm, the seat 150 can generate synchronous vibrations to enhance the passenger's musical experience.

[0036] The above diagram illustrates how the method for generating in-car music, as implemented in the embodiments of this disclosure, creates an immersive experience for the user. It should be understood that the above examples are not restrictive but are provided illustratively for the purpose of aiding understanding, and the embodiments of this disclosure are not limited to the above examples. Below, a flowchart of the method 200 for generating in-car music according to the embodiments of this disclosure will be described with reference to Figure 2.

[0037] In block 202, scene data is collected during the vehicle's driving process. According to embodiments of this disclosure, the vehicle's onboard equipment controller can detect scene data during the vehicle's driving process via its own sensors or monitors. For example, the vehicle's camera sensor can collect data such as image data captured by the vehicle's camera, the driver's movements and facial expressions, etc.

[0038] For example, a vehicle's voice sensor can collect relevant audio data, such as human voices or ambient sounds. In some embodiments, a vehicle's speed sensor can collect vehicle speed data, and a GPS positioning sensor can collect vehicle location data. According to embodiments of this disclosure, a vehicle's weather sensor can also collect weather data from the external environment.

[0039] In block 204, vehicle scene prompt words are generated based on scene data. According to embodiments of this disclosure, the music generation model in the vehicle's in-vehicle equipment controller can construct a music scene and automatically generate scene description text or prompt words by capturing or collecting changes in factors such as vehicle speed, external weather temperature, climate, driving destination, driving route, festivals, and changes in the driving's geographical location in real time during the driving process.

[0040] For example, the generated prompt words might be: "Driving through a summer wheat field, with a light rain outside, the destination is the small town of Weihai, generate music and corresponding lyrics applicable to this scene, with the song type being 'R&B'." In some embodiments, the generated prompt words might also be: "Driving through a city at night, with a gentle breeze outside, the destination is the city center, generate music and lyrics suitable for nighttime city driving, with the song type being electronic music."

[0041] In some embodiments, the generated prompt words may be: "You are driving at high speed on a highway, it is a cold winter day outside the window, the roadside is covered with snow, your destination is a hot spring deep in the mountains, generate music and lyrics suitable for driving in a cold winter, the song type is 'classical music', and the composition style is 'Beethoven'." In some embodiments, the generated prompt words may be: "You are driving on an autumn forest road, leaves are fluttering in the wind, your destination is a wooden house in the forest, generate country music suitable for autumn, the song type is 'folk song'." These prompt words help the music generation model better understand the current driving scene, thereby assisting in the generation of music style suggestion prompt words and / or lyric creation style prompt words that match the scene, improving the driver's emotional experience and immersion during the driving process.

[0042] In some embodiments, the music style suggestion prompt words and lyric writing style prompt words may be generated and updated based on the user's music preferences, historical data, and feedback data. For example, the music generation model can establish a user music preference profile based on the music types manually selected by the user, frequently played tracks, favorite artists and lyricists, etc. This user music preference profile may include the music styles that the user most frequently selects and plays, favorite lyric writing styles, and how those preferences change in different contexts.

[0043] For example, in some embodiments, this user's music preference profile may include the fact that the user generally likes to listen to rock music when driving long distances, but tends to listen to pop music when driving short to medium distances in urban areas. Based on this user's music preference profile, the music generation model can dynamically adjust the music style suggestion prompt words and lyric creation style prompt words related to scene transitions during subsequent driving processes.

[0044] In some embodiments, the music generation model can also update and generate prompt words based on real-time user feedback data. For example, the user can provide feedback via the in-car device controller, such as "like," "dislike," skip tracks, or express preferences through voice commands. For instance, during a long-distance drive, the user might "like" "relaxing music" and give a positive rating to the light music being played.

[0045] The music generation model can immediately record this feedback and prioritize the user's "light music" needs in subsequent music recommendations or generation. Based on this feedback, the music generation model can generate prompt words such as, for example, "Play more light music, with a compositional style of 'Debussy' and a lyrical style of 'calm'."

[0046] In block 206, in-car music is generated based on vehicle scene prompt words. For example, in some embodiments, the music generation model can analyze the vehicle scene prompt words and break them down into several important factors, such as music type, emotional tone, ambient atmosphere, lyrical theme, etc. These factors may be used to guide the subsequent music generation process. In some embodiments, the music generation model can select a suitable music generation algorithm or a pre-configured style module.

[0047] Additionally or alternatively, in some embodiments, the music generation model may propose applying a specific composition mode or template based on the composition style in the prompt word, for example, by using similar chord processes, melodic structures, or instrumental arrangements that mimic the style of a target composer.

[0048] In some implementations, the music generation model may include a lyrics generation module that can generate lyrics that match the music based on a large-scale language model. After generating the lyrics, the music generation model can combine them with the generated musical melody to create a complete song. In some embodiments, the music generation model can also collect the user's historical music preferences, such as the most played music categories, the most preferred musicians' song styles, or songwriting styles, and automatically generate a personalized music or song library for the user.

[0049] Figure 3 illustrates a schematic diagram of a method 300 for generating in-vehicle music according to an embodiment of the present disclosure. As shown in Figure 3, the vehicle 110 may include a vehicle data acquisition module 310. The vehicle data acquisition module 310 can acquire or collect scene data during the vehicle's operation. For example, an in-vehicle camera 302 in the vehicle data acquisition module 310 can capture in-vehicle image data, particularly the driver's movements and facial expressions. This image data may be used to analyze the driver's state, for example, whether they are tired, distracted, or experiencing emotional changes.

[0050] In some embodiments, the in-vehicle microphone 304 in the vehicle data acquisition module 310 can collect in-vehicle audio data, including the driver's voice and in-vehicle noise. The collected audio data may be used for emotion recognition, voice command processing, and environmental noise detection.

[0051] According to embodiments of this disclosure, the audio sensor 306 in the vehicle data acquisition module 310 can collect the audio environment inside the vehicle, including music volume and the intrusion of external noise, and this data helps to understand the audio environment inside the vehicle and make appropriate music adjustments.

[0052] In some embodiments, the speed sensor 308 in the vehicle data acquisition module 310 can record the vehicle's speed. For example, during high-speed driving, the music generation model implemented by the embodiments of this disclosure can generate fast-paced music. According to embodiments of this disclosure, the GPS sensor 312 can provide the vehicle's real-time location and geographic location information. This data may be used to generate music content related to the current driving route and destination.

[0053] In some embodiments, the weather sensor 314 in the vehicle data acquisition module 310 may be used to collect weather data of the external environment, including temperature, humidity, and rainfall. This data may be used to select and generate music that is appropriate for the weather conditions. According to embodiments of this disclosure, the data collected by the vehicle data acquisition module 310 through various sensors is distributed to the basic data acquisition and processing module 320 for further analysis and processing.

[0054] According to embodiments of this disclosure, the driver motion and facial expression capture module 322 in the basic data acquisition and processing module 320 processes image data from the in-vehicle camera 302 and analyzes the driver's motion and facial expressions to determine the driver's current mood state or level of fatigue, thereby adjusting the music content.

[0055] In some embodiments, the vehicle speed and location module 324 in the basic data collection and processing module 320 processes and integrates data from the speed sensor 308 and the GPS sensor 312 to determine the vehicle's current speed and geographical location, which can then be used for scene generation and music selection. In some embodiments, the weather module 326 in the basic data collection and processing module 320 processes data from the weather sensor 314 to analyze the current weather conditions and can influence the music generation module's decision-making, for example, by selecting more pleasant music on a rainy day.

[0056] In some embodiments, the driving mode module 328 can determine the current driving mode, such as highway driving, city commuting, or country road driving, based on the vehicle's speed, location, weather, and driver's condition. The results analyzed by the driving mode module 328 may be passed as input to the scene engine 330 and used to generate the corresponding music scene prompt words.

[0057] In some embodiments, the scene analysis module 332 in the scene engine 330 can analyze the current driving environment and conditions based on data provided by the basic data collection and processing module 320. The scene analysis module 332 can determine the music style, composition style, and lyric style that best suit the current driving situation. In some embodiments, the scene mode 334 in the scene engine 330 can determine a mode to be generated after the scene analysis, which includes a specific description of the driving scene and corresponding music prompts. These scene modes may be used to guide the subsequent music generation process.

[0058] According to embodiments of this disclosure, the scene generation module 336 can construct detailed vehicle scene prompt words based on the results of scene analysis. These prompt words may include suggested music types, emotional tones, compositional styles, and lyrical themes. The generated prompt words are passed to the AIGC music generation engine 340 or music generation model and used for music creation.

[0059] According to embodiments of this disclosure, the AIGC music generation engine 340 or music generation model may include a music generation module 342 that can generate music that conforms to prompt word requests using artificial intelligence techniques (e.g., deep learning, generative adversarial network, etc.) based on vehicle scene prompt words provided by the scene engine 330. The generated music may include melody, arrangement, harmony and corresponding lyrics content.

[0060] In some embodiments, the user preference mode module 344 in the AIGC music generation engine 340 can integrate the user's historical music preferences, feedback data, and current mood state to ensure that the generated music is tailored to the user's personal taste and current needs. The user preference mode module 344 and the user feedback module 346 can also provide a more personalized music service by continuously learning and updating.

[0061] In some embodiments, a user feedback module 346 in the AIGC music generation engine 340 can collect user feedback after generating and playing music. This feedback may be manual input via an in-vehicle display, voice commands, or implicit feedback obtained through driving behavior analysis, such as frequently skipping certain types of music. The feedback data may be passed to a user preference mode module 344 and used to optimize subsequent music generation.

[0062] In some embodiments, music playback and user feedback can interact with the user via the head unit 350. For example, the user can view information about the currently playing music, control music playback, select music types, and receive immediate feedback via the music playback interface 352 in the head unit 350. The playback interface 352 may be one of the main ways in which the user interacts with the system.

[0063] In some embodiments, the preference settings 354 in the head unit 350 may allow the user to set and adjust their musical preferences, including the selection of preferred music types, composers, and lyric styles. The user can then directly influence the system's music generation decisions.

[0064] According to embodiments of this disclosure, the music style library 356 can store samples and models of various music styles for the AIGC music generation engine 340 to invoke. The music style library 356 may also include feature data of various music types to ensure that the generated music has high quality and diversity. In some embodiments, a music favorites module 358 in the head unit 350 can store the user's favorite music segments or generated music. These favorites can be accessed via the playback interface, and the user can also play these songs again during subsequent driving.

[0065] Additionally or alternatively, in some embodiments, biosensors mounted in the vehicle detect the driver's heart rate, respiratory rate, and stress level in real time. The sensors may include wearable devices, such as smartwatches, or sensors directly integrated into the vehicle seat or steering wheel. These devices can continuously collect and analyze the driver's physiological data. For example, if phenomena such as a significant increase in the driver's heart rate and an accelerated respiratory rate are detected, it can be determined that the driver may be in a state of tension or fatigue. Based on the analysis, music that can help the driver relax can be generated or selected. Such music generally has soothing melodies and low-frequency sound effects, thereby reducing the driver's stress and anxiety.

[0066] Additionally or alternatively, in some embodiments, after multiple users enter the vehicle, the system identifies each user by in-vehicle identification technology, such as user device connectivity, and retrieves their music preferences and history data from a database. This preference data may include information such as the types of music each user listens to most frequently, their favorite artists, composers, and lyrical styles.

[0067] Subsequently, the musical preferences of all users can be integrated. For example, if one user prefers pop music and another prefers rock music, rhythmically driven pop music or pop-rock music can be generated to satisfy everyone's needs while avoiding playback of types that some users dislike. In some embodiments, user feedback (e.g., voice commands, manual volume adjustments, or song switching actions) can be continuously collected, and the music content and style can be dynamically adjusted based on the feedback to better suit the immediate needs of the majority of passengers in the vehicle.

[0068] Additionally or alternatively, in some embodiments, vehicle navigation data, such as the current route, destination, and estimated time of arrival, can be acquired. Based on the navigation data and traffic conditions, the system predicts driving scenarios that may be encountered within the next few minutes. For example, if congestion is detected on a road section ahead and the vehicle is expected to enter this section within 10 minutes, music suitable for the congestion scene can be generated. For example, when approaching a congested road section, calm, slow-rhythm background music can be generated to help the driver stay calm. Before entering an open highway, upbeat music can be generated to enhance the driving experience.

[0069] Thus, the method realized by this disclosure responds in real time to changes in the driving scene, generates background music that suits the current environment and mood for the driver, enhances the driving experience, promotes the creation of original background music, allows anyone to become a composer on the road, and comprehensively considers the driver's mood, external environment and past preferences to get closer to user needs.

[0070] Figure 4 shows a schematic block diagram of an exemplary device 400 available for carrying out embodiments of the present disclosure. The vehicle device in Figure 1 can be realized using device 400. As shown in the figure, device 400 includes a central processing unit (CPU) 401 which can perform various appropriate operations and processes based on computer program instructions stored in read-only memory (ROM) 402 or computer program instructions loaded from storage unit 408 into random access memory (RAM) 403. RAM 403 may further store various programs and data necessary for the operation of device 400. The CPU 401, ROM 402 and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0071] Multiple components in the device 400 are connected to the I / O interface 405 and include, for example, an input unit 406 such as a keyboard or mouse, an output unit 407 such as various types of displays or speakers, a memory 407 such as a magnetic disk or optical disk, and a communication unit 409 such as a network card, modem, or wireless communication transceiver. The communication unit 409 allows the device 400 to exchange information / data with other devices via computer networks such as the Internet and / or various telegraph networks.

[0072] Each of the processes and operations described above, for example, method 200, can be executed by the processing unit 401. For example, in some embodiments, method 200 can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, for example, a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via ROM 402 and / or communication unit 409. Once the computer program is loaded into RAM 403 and executed by CPU 401, one or more operations of method 200 and process 300 described above can be performed.

[0073] This disclosure may include methods, apparatus, systems, and / or computer program products. A computer program product may include a computer-readable storage medium on which computer-readable program instructions for performing each aspect of this disclosure are loaded.

[0074] A computer-readable storage medium may be a tangible device capable of maintaining and storing instructions used by an instruction execution device. A computer-readable storage medium may be, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (non-exclusive list) of computer-readable storage media include portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital multifunction disks (DVDs), memory sticks, floppy disks, and mechanical coding devices, for example, on which instruction puncture cards or recessed projection structures, and any suitable combination of the above, are stored. The computer-readable storage medium used herein is not interpreted as an instantaneous signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagated through a waveguide or other transmission medium (e.g., an optical pulse via an optical fiber cable), or an electrical signal transmitted via an electric wire.

[0075] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives computer-readable program instructions from the network and transfers these computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0076] Computer program instructions for performing the operations of the Disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or target code written in any combination of one or more programming languages, wherein the programming languages ​​include object-oriented programming languages—e.g., Smalltalk, C++, etc.—and general procedural programming languages—e.g., the "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user computer, partially on a user computer, as a single standalone software package, partially on a user computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it may be connected to an external computer (e.g., connected via the Internet using an Internet service provider). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), can be customized by utilizing state information of computer-readable program instructions, and this electronic circuit can realize each aspect of the present disclosure by executing computer-readable program instructions.

[0077] Herein, each aspect of the present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, apparatus (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and each combination of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0078] By providing these computer-readable program instructions to the processing unit of a general-purpose computer, a dedicated computer, or other programmable data processing device, a machine can be generated, thereby generating a device that, when these instructions are executed by the processing unit of the computer or other programmable data processing device, realizes the functions / operations defined in one or more blocks in a flowchart and / or block diagram. These computer-readable program instructions may be stored in a computer-readable storage medium, and by using these instructions to operate a computer, programmable data processing device, and / or other device in a specific manner, the computer-readable medium storing the instructions will contain a product containing instructions that realize various modes of the functions / operations defined in one or more blocks in a flowchart and / or block diagram.

[0079] Computer-readable program instructions may be loaded into a computer, other programmable data processing device, or other device, thereby generating a process implemented by the computer by executing a series of operational steps on the computer, other programmable data processing device, or other device, and thereby the instructions executed on the computer, other programmable data processing device, or other device implement the functions / operations defined in one or more blocks in a flowchart and / or block diagram.

[0080] The flowcharts and block diagrams in the drawings illustrate the implementable system architectures, functions, and operations of systems, methods, and computer program products according to several embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or part of an instruction, which includes one or more executable instructions for implementing a defined logical function. In some implementations as alternatives, the functions described in a block may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed essentially in parallel, or in reverse order depending on the function. Note that each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the defined function or operation, or by a combination of dedicated hardware and computer instructions.

[0081] While the embodiments of this disclosure have been described above, the above descriptions are illustrative, not exhaustive, and are not limited to the embodiments disclosed. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the embodiments described. The choice of terms used herein is intended to best interpret the principles, practical applications, or technological advancements of the technology in the market of each embodiment, or to enable other those skilled in the art to understand each embodiment disclosed herein.

Claims

1. A method for generating in-car music, Collecting scene data during the vehicle's driving process, The process involves generating vehicle scene prompt words based on the aforementioned scene data, A method comprising generating in-vehicle music based on the vehicle scene prompt word.

2. Collecting the scene data during the aforementioned vehicle driving process means To collect image data captured by the vehicle's camera, as well as driver's movements and facial expression data. To collect audio data collected by the vehicle's audio sensor, To collect vehicle speed data recorded by the vehicle's speed sensor, To collect location data provided by the GPS positioning system of the vehicle, or The method according to claim 1, comprising one or more of the following: collecting weather data from the external environment.

3. Determining the vehicle scene prompt word based on the aforementioned scene data means that The method according to claim 1, comprising generating a music style suggestion prompt word and / or lyric creation style prompt word that match the scene data.

4. The method according to claim 3, wherein the music style suggestion prompt word and the lyrics creation style prompt word are further generated and updated based on the user's music preferences, history data, and feedback data.

5. Generating the in-car music based on the aforementioned vehicle scene prompt word means that The method according to claim 1, comprising generating in-vehicle music based on the vehicle scene prompt word using a smart music generation engine.

6. The method according to claim 1, further comprising creating a personalized user music library for the user based on the generated in-car music.

7. The above-mentioned in-car music generation is, Detecting the user's physiological health status, including one or more of heart rate, respiratory rate, and stress level, The invention further includes generating the in-car music based on the aforementioned physiological health condition, and The method according to claim 1, further comprising generating in-car music that relaxes the user in response to an increase in one or more of the following data: heart rate, respiratory rate, and stress level.

8. The above-mentioned in-car music generation is, The method according to claim 1, further comprising generating in-car music that suits the musical preferences of multiple users based on the musical preferences, history data and settings of each of the multiple users, in response to the presence of multiple users in the vehicle.

9. The above-mentioned in-car music generation is, Predicting vehicle scene prompt words based on the vehicle's navigation data, traffic conditions, and driving habits, The method according to claim 1, further comprising generating the in-car music based on the predicted vehicle scene prompt word.

10. An electronic device for generating in-car music, Processor and An electronic device comprising a memory coupled to the processor and storing instructions, wherein when an instruction is executed by the processor, the device is caused to perform the method according to any one of claims 1 to 9.

11. A computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed, it causes a computer to execute the method according to any one of claims 1 to 9.

12. A computer program that causes a computer to perform the method described in any one of claims 1 to 9.

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