WO2024164686A1 - 基于ai语音助手的人机交互方法、装置、设备及介质 - Google Patents

基于ai语音助手的人机交互方法、装置、设备及介质 Download PDF

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Publication number
WO2024164686A1
WO2024164686A1 PCT/CN2023/137180 CN2023137180W WO2024164686A1 WO 2024164686 A1 WO2024164686 A1 WO 2024164686A1 CN 2023137180 W CN2023137180 W CN 2023137180W WO 2024164686 A1 WO2024164686 A1 WO 2024164686A1
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Prior art keywords
interaction
user
strategy
scenario
information
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PCT/CN2023/137180
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English (en)
French (fr)
Inventor
刘永斌
吴洁
程进波
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Chery Automobile Co Ltd
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Chery Automobile Co Ltd
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Publication of WO2024164686A1 publication Critical patent/WO2024164686A1/zh
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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/332—Query formulation
    • G06F16/3329—Natural language query formulation
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3343—Query execution using phonetics
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3344—Query execution using natural language analysis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9032—Query formulation
    • G06F16/90332—Natural language query formulation or dialogue systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/16—Sound input; Sound output
    • G06F3/167—Audio in a user interface, e.g. using voice commands for navigating, audio feedback
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00—Speech recognition
    • G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue

Definitions

  • the present disclosure relates to the field of voice assistant technology, and in particular to a human-computer interaction method, device, equipment and medium based on AI (Artificial Intelligence) voice assistant.
  • AI Artificial Intelligence
  • artificial intelligence assistants have been widely used. They can meet users' information interaction, life services and other functions to a certain extent in various fields. However, in some fields of vehicle technology, the convenient services of artificial intelligence assistants have not been fully utilized. Therefore, artificial intelligence technology can be used to meet users' diverse needs in various scenarios in the vehicle field.
  • the present disclosure provides a human-computer interaction method, device, equipment and medium based on an AI voice assistant to solve the problem that when a user is trying to understand a vehicle function, there is no mobile phone APP intelligent voice assistant that is compatible with the vehicle to help the user answer questions, thereby reducing the user's intelligent experience.
  • an embodiment of the present disclosure provides a human-computer interaction method based on an AI voice assistant, the method comprising:
  • an interaction strategy corresponding to the interaction information is generated, and interaction is performed with the user according to the interaction strategy.
  • generating an interaction strategy corresponding to the interaction information based on the optimal interaction scenario includes:
  • An explanation interaction is performed with the user according to at least one purchase explanation strategy of each purchase intention.
  • generating an interaction strategy corresponding to the interaction information based on the optimal interaction scenario includes:
  • the corresponding manual explanation information is generated according to the at least one function recognition intention, and at least one manual explanation strategy for each function recognition intention is obtained according to the manual explanation information corresponding to each function recognition intention.
  • generating an interaction strategy corresponding to the interaction information based on the optimal interaction scenario includes:
  • a commuting reminder interaction is performed according to the commuting reminder strategy, and/or a schedule reminder interaction is performed according to the schedule collection reminder strategy.
  • generating an interaction strategy corresponding to the interaction information based on the optimal interaction scenario includes:
  • generating an interaction strategy corresponding to the interaction information based on the optimal interaction scenario includes:
  • Corresponding service recommendation data is generated according to the at least one functional service intent, and at least one service explanation strategy for each functional service intent is obtained according to the service recommendation data corresponding to each functional service intent.
  • the user's interaction information is received and the user's current interaction intention is identified, thereby matching the best interaction scene, thereby generating an interaction strategy corresponding to the interaction information, and interacting with the user according to the interaction strategy.
  • the problem that when the user understands the vehicle function, there is no mobile phone APP intelligent voice assistant that is matched with the vehicle to help the user answer questions, thereby reducing the user's intelligent experience, etc. is solved.
  • a multi-modal interaction method is provided for the user, thereby realizing the full-scenario intelligent service of the vehicle.
  • an embodiment of the present disclosure provides a human-computer interaction device based on an AI voice assistant, the device comprising:
  • a receiving module used for receiving interaction information from users
  • a matching module configured to identify the current interaction intention of the user according to the interaction information, and match the best interaction scenario based on the current interaction intention
  • a generation module is used to generate an interaction strategy corresponding to the interaction information based on the optimal interaction scenario, and interact with the user according to the interaction strategy.
  • the matching module is used to:
  • An explanation interaction is performed with the user according to at least one purchase explanation strategy of each purchase intention.
  • the matching module is used to:
  • the corresponding manual explanation information is generated according to the at least one function recognition intention, and at least one manual explanation strategy for each function recognition intention is obtained according to the manual explanation information corresponding to each function recognition intention.
  • the matching module is used to:
  • a commuting reminder interaction is performed according to the commuting reminder strategy, and/or a schedule reminder interaction is performed according to the schedule collection reminder strategy.
  • the matching module is used to:
  • the matching module is used to:
  • Corresponding service recommendation data is generated according to the at least one functional service intent, and at least one service explanation strategy for each functional service intent is obtained according to the service recommendation data corresponding to each functional service intent.
  • the human-computer interaction device based on AI voice assistant of the embodiment of the present disclosure the user's interaction information is received and the user's current interaction intention is identified, thereby matching the best interaction scene, thereby generating an interaction strategy corresponding to the interaction information, and interacting with the user according to the interaction strategy.
  • the problem that when the user understands the vehicle function, there is no mobile phone APP intelligent voice assistant matching the vehicle to help the user answer questions, thereby reducing the user's intelligent experience, etc. is solved.
  • a multi-modal interaction method is provided for the user, thereby realizing the full-scenario intelligent service of the vehicle.
  • an embodiment of the present disclosure provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a human-computer interaction method based on an AI voice assistant as described in any one of the above items.
  • an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement a human-computer interaction method based on an AI voice assistant as described in any one of the above items.
  • FIG1 is a flow chart of a human-computer interaction method based on an AI voice assistant provided in an embodiment of the present disclosure
  • FIG2 is a flow chart of a shopping scenario provided by an embodiment of the present disclosure.
  • FIG3 is an example diagram of a shopping scenario provided by an embodiment of the present disclosure.
  • FIG4 is a flowchart of a manual explanation scenario provided by an embodiment of the present disclosure.
  • FIG5 is an example diagram of a manual explanation scenario provided by an embodiment of the present disclosure.
  • FIG6 is a flowchart of a reminder scenario provided by an embodiment of the present disclosure.
  • FIG. 7 is an example diagram of a reminder scenario provided by an embodiment of the present disclosure.
  • FIG8 is a flowchart of a rescue scenario provided by an embodiment of the present disclosure.
  • FIG9 is a flow chart of a service scenario provided by an embodiment of the present disclosure.
  • FIG10 is an example diagram of a service scenario provided by an embodiment of the present disclosure.
  • FIG11 is a block diagram of an example of a human-computer interaction device based on an AI voice assistant provided in an embodiment of the present disclosure
  • FIG. 12 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure.
  • Words such as "connect” or “connected” and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up”, “down”, “left”, “right” and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.
  • the present disclosure provides a human-computer interaction method based on AI voice assistant, in which the user's interaction information is received and the user's current interaction intention is identified, thereby matching the best interaction scenario, thereby generating an interaction strategy corresponding to the interaction information, and interacting with the user according to the interaction strategy.
  • FIG1 is a flow chart of a human-computer interaction method based on an AI voice assistant provided in an embodiment of the present disclosure.
  • the human-computer interaction method based on the AI voice assistant includes the following steps:
  • step S101 user interaction information is received.
  • the user when the user wants to understand the relevant performance of the vehicle, he needs to use the mobile phone APP associated with the vehicle as a carrier, and the AI voice assistant installed in the vehicle will provide detailed explanations to the user so that the user can make purchases or performance choices based on his own understanding needs.
  • the mobile phone APP When users want to know about a certain performance of the vehicle, they can send an interactive information request to the mobile phone APP.
  • the interactive information can be sent to the mobile phone APP in various ways such as text, voice, video, and picture. Then, the mobile phone APP receives the interactive information sent by the user and analyzes it.
  • step S102 the user's current interaction intention is identified according to the interaction information, and the best interaction scenario is matched based on the current interaction intention.
  • the mobile phone APP of the embodiment of the present disclosure needs to identify the user's current interaction intention based on the interaction information to match the best interaction scenario, so as to meet the user's intelligent understanding needs of all scenarios.
  • the best interaction scenario may include but is not limited to the purchase scenario, manual explanation scenario, reminder scenario, rescue scenario and service scenario.
  • step S103 based on the optimal interaction scenario, an interaction strategy corresponding to the interaction information is generated, and interaction with the user is performed according to the interaction strategy.
  • the embodiment of the present disclosure can generate an interaction strategy corresponding to the interaction information based on the best interaction scenario, and interact with the user according to the interaction strategy.
  • an interaction strategy corresponding to the interaction information is generated based on the optimal interaction scenario, including: analyzing at least one shopping intention of the user according to the interaction information; generating corresponding shopping display information according to the at least one shopping intention, and obtaining at least one shopping explanation strategy for each shopping intention according to the shopping display information corresponding to each shopping intention; and performing explanation interaction with the user according to the at least one shopping explanation strategy for each shopping intention.
  • the best interaction scenario matched according to the user's current interaction intention is a shopping scenario
  • a corresponding interaction strategy in the shopping scenario is generated.
  • the embodiment of the present disclosure takes the mobile phone APP installed in the A series vehicles as an example.
  • the user starts to wake up the associated mobile phone APP when entering the vehicle, and consults the mobile phone APP for the vehicle purchase information he wants to know, for example, the configuration information, price information and reservation information of the A series vehicles;
  • the mobile phone APP analyzes the user's interaction intention, and displays to the user whether to call the relevant list of vehicle consultation information. If it needs to be called, the relevant information after the call is further displayed to the user.
  • the mobile app For example, if a user asks the mobile app for the configuration information of the A series vehicle, the user is prompted to select whether to call the vehicle. If the user wants to call the vehicle-related configuration table, the vehicle configuration table will be displayed through an H5 (HyperText Markup Language5) link, and the user will be further shown whether a recommended vehicle configuration is needed. If a recommendation is needed, the mobile APP will call the vehicle database and language library, and show the vehicle configuration table to the user through text or voice emotion broadcast.
  • H5 HyperText Markup Language5
  • the mobile APP will provide other help to the user. If the user does not want to call the vehicle-related configuration table or does not need the recommended vehicle configuration, other help will be provided to the user through the mobile APP; if the user asks the mobile APP for the price information of A series vehicles, the user will be shown whether to call the vehicle-related price list. If the user wants to call the vehicle-related price list, the mobile APP will call the price information displayed on the vehicle official website. If the vehicle price needs to be introduced, the mobile APP will call the knowledge base and voice library of the A series vehicles and introduce the vehicle price to the user in professional language. If the user does not want to call the vehicle-related price list or does not need to introduce the vehicle price, the mobile APP will provide other help to the user.
  • the user will be shown whether to call the vehicle-related test drive appointment. If the user wants to call the vehicle-related test drive appointment, the user will enter the test drive information filling interface and further show the user whether to fill in the test drive information. If it needs to be filled in, the call center and voice library will be called, and the test drive appointment information will be shown to the user, so as to complete the test drive appointment and arrange the relevant test drive specialist. If the user does not want to call the vehicle-related test drive appointment information, the mobile APP will provide other help to the user.
  • the disclosed embodiment provides potential users with an introduction to vehicle brands and related information through the above-mentioned purchasing scenarios provided to users, thereby ultimately facilitating sales orders.
  • an interaction strategy corresponding to the interaction information is generated based on the optimal interaction scenario, including: analyzing the user's at least one function recognition intention for the vehicle based on the interaction information; generating corresponding manual explanation information based on the at least one function recognition intention, and obtaining at least one manual explanation strategy for each function recognition intention based on the manual explanation information corresponding to each function recognition intention.
  • the best interaction scenario matched according to the user's current interaction intention is the manual explanation scenario
  • a corresponding interaction strategy in the manual explanation scenario is generated.
  • the user starts to wake up the mobile phone APP when entering the vehicle, and consults the mobile phone APP about the vehicle-related functions he wants to know, such as how to open the engine hood of A series vehicles, how to connect to carplay, how to recognize voice in the vehicle, and how to turn off the engine start-stop switch; secondly, after the user consults the associated mobile phone APP, the user is shown whether to open the electronic manual corresponding to the relevant function. If the user chooses to open the electronic manual, the manual explanation strategy corresponding to the vehicle function is generated through the mobile phone APP and explained to the user.
  • a user asks a mobile phone APP about the method of opening the hood of an A series vehicle
  • the user is shown whether to open the electronic manual of the method of opening the hood. If the user chooses to open the electronic manual, the electronic manual data is called, and the user is shown whether to generate a manual explanation strategy through video. If the user chooses to play the video of the method of opening the hood, the user is explained through video, otherwise, the explanation is given through voice broadcast. If the user chooses not to open the electronic manual, other help is provided to the user through the mobile phone APP.
  • a user asks a mobile phone APP about the method of connecting carplay (a vehicle-mounted system) of an A series vehicle, the user is shown whether to open the electronic manual of the method of connecting carplay. If the user chooses to open the electronic manual, the electronic manual data is called, and the user is shown whether to generate a manual explanation strategy through video. If the user chooses to play the manual explanation strategy of the method of connecting carplay through video, the user is explained through video, otherwise, the explanation is given through voice broadcast. If the user chooses not to open the electronic manual, other help is provided to the user through the mobile phone APP.
  • the mobile phone APP inquires about the in-vehicle voice recognition method of A series vehicles, the user is displayed whether to open the electronic manual of the in-vehicle voice recognition method. If the user chooses to open the electronic manual, the electronic manual data is called, and the user is displayed whether to generate the manual explanation strategy through video. If the user chooses to play the manual explanation strategy of the in-vehicle voice recognition method through video, the user is explained through video, otherwise, the explanation is given through voice broadcast.
  • the user chooses not to open the electronic manual, other help is provided to the user through the mobile phone APP; if the user asks the mobile phone APP about the method of turning off the engine start-stop switch of A series vehicles, the user is displayed whether to open the electronic manual of the method of turning off the engine start-stop switch. If the user chooses to open the electronic manual, the electronic manual data is called, and the user is displayed whether to generate the manual explanation strategy through video. If the user chooses to play the manual explanation strategy of the method of turning off the engine start-stop switch through video, the user is explained through video, otherwise, the explanation is given through voice broadcast. If the user chooses not to open the electronic manual, other help is provided to the user through the mobile phone APP.
  • the disclosed embodiment provides potential users with an introduction to vehicle functions and related information through the manual explanation scenario provided to users, thereby satisfying users' needs for understanding vehicle functions.
  • an interaction strategy corresponding to the interaction information is generated based on the optimal interaction scenario, including: analyzing the user's commuting reminder strategy and/or schedule collection reminder strategy based on the interaction information; performing commuting reminder interaction according to the commuting reminder strategy, and/or performing schedule reminder interaction according to the schedule collection reminder strategy.
  • the best interaction scenario matched according to the user's current interaction intention is a reminder scenario
  • a corresponding interaction strategy under the reminder scenario is generated.
  • the user starts to wake up the mobile phone APP when entering the vehicle, and the mobile phone APP shows the user whether he agrees to collect daily commuting information and/or schedule collection information.
  • the user's commuting reminder strategy and/or schedule collection reminder strategy is analyzed, and commuting reminder interaction is performed according to the commuting reminder strategy, and/or schedule reminder interaction is performed according to the schedule collection reminder strategy.
  • the user's daily commuting information will be uploaded to the big data platform where the vehicle is located.
  • the platform will analyze the user's daily commuting information received to generate a commuting reminder strategy and show the user whether the commuting reminder strategy needs to be broadcast.
  • the mobile phone APP will broadcast to the user through voice or video based on the road conditions of the current driving route. For example, information such as "an accident has occurred ahead of your current commuting route" can be used. At this time, the user can choose whether to recommend a safe route through the mobile phone APP.
  • the map data in the current driving environment will be called to recommend a reasonable route to the user based on the map data. If the user chooses not to recommend a safe route, the vehicle will also call the map data in the current driving environment and recommend a reasonable route to the user based on the map data. Continue driving along the original route according to the map data. If the user does not agree to collect his/her daily commuting information, the mobile APP will not display the user's daily commuting information; if the user agrees to collect his/her schedule collection information, the user's schedule collection information will be uploaded to the big data platform where the vehicle is located.
  • the platform will analyze the received schedule collection information of the user to generate a schedule collection reminder strategy and display to the user whether the schedule collection reminder strategy needs to be broadcast, for example, whether it is necessary to broadcast today's weather conditions. If the user chooses to broadcast, the mobile APP will call weather data according to today's weather forecast, for example, "Today there will be heavy rain in the city, please drive carefully and turn off the energy-saving start-stop function" and other information. If the user does not agree to collect his/her schedule collection information, the mobile APP will not display the user's schedule collection information;
  • the embodiments of the present disclosure maintain commuting destinations for users through the reminder scenarios provided to users, and provide travel suggestions based on the weather conditions and traffic information of the day, thereby ensuring the driving safety of users.
  • an interaction strategy corresponding to the interaction information is generated based on the optimal interaction scenario, including: analyzing the user's rescue guidance strategy based on the interaction information; and performing rescue interaction based on the rescue guidance strategy.
  • the best interaction scenario matched according to the user's current interaction intention is a rescue scenario
  • a corresponding interaction strategy in the rescue scenario is generated.
  • the mobile phone APP first, the user starts to wake up the mobile phone APP when entering the vehicle. If the current vehicle is rear-ended, the mobile phone APP will display a request to the user whether it is necessary to take photos inside the vehicle. If the user needs to take photos inside the vehicle, the driving recorder in the vehicle will be called, and the photos will be uploaded to the big data platform where the vehicle is located; then, the mobile phone APP retrieves the photos taken by the driving recorder and confirms the location of the accident.
  • the map data of the area where the current vehicle is located is called, the vehicle location information is obtained through the cloud system, the current location is displayed, and the user is shown whether rescue is needed, or when the location of the accident cannot be confirmed, the same The user is shown whether rescue is needed. If the user chooses that rescue is needed, the mobile phone APP will further call the emergency rescue system and arrange for a rescue trailer and rescue personnel to go to the scene of the vehicle accident for emergency rescue. While the user is waiting for rescue, the user is required to keep the phone open to avoid missing the rescue personnel. Finally, while waiting for rescue, the user also needs to move the vehicle to a safe location, place warning signs around the vehicle and set up double flash lights to alert other drivers. If the user does not need to take pictures in the vehicle, the user can get off the vehicle to take pictures by himself, and move the vehicle to a safe location, place warning signs around the vehicle and set up double flash lights to alert other drivers.
  • the embodiments of the present disclosure provide users with rescue scenarios as described above, thereby providing users with accident handling guidance when they encounter traffic accidents, and helping users report accidents and handle rescue.
  • an interaction strategy corresponding to the interaction information is generated based on the optimal interaction scenario, including: analyzing at least one functional service intention of the user for the vehicle based on the interaction information; generating corresponding service recommendation data based on the at least one functional service intention, and obtaining at least one service explanation strategy for each functional service intention based on the service recommendation data corresponding to each functional service intention.
  • the best interaction scenario matched according to the user's current interaction intention is a service scenario
  • a corresponding interaction strategy in the service scenario is generated.
  • the mobile phone APP starts to wake up the mobile phone APP, and the mobile phone APP shows the user whether to agree to collect vehicle maintenance information. If the user agrees to collect vehicle maintenance information, the vehicle maintenance information is uploaded to the big data platform where the vehicle is located. The platform analyzes the received vehicle maintenance information of the user to generate a service explanation strategy, and shows the user whether the service explanation strategy needs to be broadcast. If the user chooses to broadcast, the mobile phone APP broadcasts according to the maintenance information of the current vehicle, for example, "It has been 8 months since your vehicle was last maintained.
  • the mobile phone APP calls the maintenance shop information in the area where the vehicle is located, and recommends the user the vehicle maintenance shop closest to the vehicle and with a suitable price according to the current target location of the vehicle, and shows the user whether to make an appointment at the shop. If the user makes an appointment with the maintenance shop, the user fills in the appointment information and calls the CRM (Customer Relationship Management) of the data platform where the vehicle is located. The user completes the reservation through the vehicle maintenance system and generates order information and reservation information. The user goes to the vehicle maintenance shop for vehicle maintenance according to the reservation information, and calls the order information after the vehicle maintenance is completed, and selects the order payment method. For example, the user can choose to call the payment system to pay or pay by cash.
  • CRM Customer Relationship Management
  • the mobile APP continues to select the vehicle maintenance shop based on the distance between the user and the vehicle.
  • the system recommends other vehicle maintenance shops to users based on their distance and price discounts, and shows users whether to make an appointment at the shop. If the user makes an appointment at the maintenance shop, the above appointment steps are repeated. If the user chooses not to make an appointment at the maintenance shop, the vehicle temporarily closes the appointment function and continues to drive according to the current driving status.
  • the embodiments of the present disclosure provide users with the above-mentioned service scenarios, so that when users want to clean, refuel, charge and maintain their vehicles, etc., they can be provided with intelligent recommendations, realize one-to-one service functions, and thus improve the user's driving experience.
  • the user's interaction information is received and the user's current interaction intention is identified, thereby matching the best interaction scene, thereby generating an interaction strategy corresponding to the interaction information, and interacting with the user according to the interaction strategy.
  • the problem that when the user understands the vehicle function, there is no mobile phone APP intelligent voice assistant that is matched with the vehicle to help the user answer questions, thereby reducing the user's intelligent experience, etc. is solved.
  • a multi-modal interaction method is provided for the user, thereby realizing the full-scenario intelligent service of the vehicle.
  • FIG11 is a block diagram of a human-computer interaction device based on an AI voice assistant according to an embodiment of the present disclosure.
  • the human-computer interaction device 10 based on the AI voice assistant includes: a receiving module 100 , a matching module 200 and a generating module 300 .
  • the receiving module 100 is used to receive the user's interactive information
  • a matching module 200 configured to identify the user's current interaction intention according to the interaction information, and match the best interaction scenario based on the current interaction intention;
  • the generation module 300 is used to generate an interaction strategy corresponding to the interaction information based on the optimal interaction scenario, and interact with the user according to the interaction strategy.
  • the matching module 200 is configured to:
  • An explanation interaction is performed with the user according to at least one purchase explanation strategy for each purchase intention.
  • the matching module 200 is configured to:
  • Corresponding manual explanation information is generated according to at least one function recognition intention, and at least one manual explanation strategy for each function recognition intention is obtained according to the manual explanation information corresponding to each function recognition intention.
  • the matching module 200 is configured to:
  • a commuting reminder interaction is performed according to a commuting reminder strategy, and/or a schedule reminder interaction is performed according to a schedule collection reminder strategy.
  • the matching module 200 is configured to:
  • the matching module 200 is configured to:
  • Corresponding service recommendation data is generated according to at least one functional service intent, and at least one service explanation strategy for each functional service intent is obtained according to the service recommendation data corresponding to each functional service intent.
  • the human-computer interaction device based on AI voice assistant of the embodiment of the present disclosure the user's interaction information is received and the user's current interaction intention is identified, thereby matching the best interaction scene, thereby generating an interaction strategy corresponding to the interaction information, and interacting with the user according to the interaction strategy.
  • the problem that when the user understands the vehicle function, there is no mobile phone APP intelligent voice assistant matching the vehicle to help the user answer questions, thereby reducing the user's intelligent experience, etc. is solved.
  • a multi-modal interaction method is provided for the user, thereby realizing the full-scenario intelligent service of the vehicle.
  • FIG12 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure.
  • the electronic device may include:
  • a memory 1201 a processor 1202 , and a computer program stored in the memory 1201 and executable on the processor 1202 .
  • the processor 1202 executes the program, the human-computer interaction method based on the AI voice assistant provided in the above embodiment is implemented.
  • the electronic device further comprises:
  • the communication interface 1203 is used for communication between the memory 1201 and the processor 1202 .
  • the memory 1201 is used to store computer programs that can be executed on the processor 1202 .
  • Memory 1201 may include high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk storage.
  • the communication interface 1203, the memory 1201 and the processor 1202 can be connected to each other through a bus and communicate with each other.
  • the bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus.
  • ISA Industry Standard Architecture
  • PCI Peripheral Component
  • EISA Extended Industry Standard Architecture
  • the bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in FIG12, but it does not mean that there is only one bus or one type of bus.
  • the memory 1201, the processor 1202 and the communication interface 1203 are integrated on a chip, the memory 1201, the processor 1202 and the communication interface 1203 can communicate with each other through an internal interface.
  • Processor 1202 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present disclosure.
  • CPU central processing unit
  • ASIC application specific integrated circuit
  • the embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored.
  • the program is executed by a processor, the human-computer interaction method based on the AI voice assistant is implemented as above.
  • first and second are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as “first” or “second” may explicitly or implicitly include at least one of the features.
  • N means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.
  • Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present disclosure includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present disclosure belong.
  • the logic and/or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses.
  • "computer-readable medium” can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses.
  • Non-exhaustive list of computer-readable media include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM).
  • the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.
  • the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof.
  • the N steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.
  • each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module.
  • the above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.
  • the storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc.

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Abstract

本公开涉及语音助手技术领域，特别涉及一种基于AI语音助手的人机交互方法、装置、设备及介质，其中，方法包括：接收用户的交互信息并识别用户的当前交互意图，由此匹配最佳交互场景，从而生成交互信息对应的交互策略，根据交互策略与用户进行交互。由此，解决了用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验等问题，通过为车辆搭载第三方AI语音助手，并对后台知识文档进行管理、交互，为用户提供了多模交互方式，从而实现车辆的全场景智能服务。

Description

基于AI语音助手的人机交互方法、装置、设备及介质
本公开要求于2023年02月09日提交的申请号为202310135807.5、发明名称为“基于AI语音助手的人机交互方法、装置、设备及介质”的中国专利申请的优先权，其全部内容通过引用结合在本公开中。
技术领域
本公开涉及语音助手技术领域，特别涉及一种基于AI(Artificial Intelligence，人工智能)语音助手的人机交互方法、装置、设备及介质。
背景技术
随着信息技术的发展，人工智能助手得到了广泛应用，其在各领域在一定程度上可以满足用户的信息交互、生活服务等功能，但在一些车辆技术领域还没有充分利用人工智能助手的便捷服务，因此，可以借助人工智能技术，满足用户的在车辆领域各个场景下的多样化需求。
相关技术中，存在车辆未安装智能语音助手，且与该车辆的经销商关联弱化，需通过用户自行查询相关服务功能。
然而，若车辆中未安装与车辆型号配套的手机APP(Application，应用软件)智能语音助手，在用户使用车辆时就没有相关的线上技术专家帮助答疑解惑，也无法为用户分析购车意向，从而降低用户的智能体验，亟需解决。
发明内容
本公开提供一种基于AI语音助手的人机交互方法、装置、设备及介质，以解决用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验等问题。
第一方面，本公开实施例提供一种基于AI语音助手的人机交互方法，所述方法包括：
接收用户的交互信息；
根据所述交互信息识别所述用户的当前交互意图，并基于所述当前交互意图匹配最佳交互场景；以及
基于所述最佳交互场景，生成所述交互信息对应的交互策略，根据所述交互策略与所述用户进行交互。
在一种可能的实现方式中，若所述最佳交互场景为选购场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
根据所述交互信息分析所述用户的至少一个选购意图；
根据所述至少一个选购意图生成对应的选购展示信息，并根据每个选购意图对应的选购 展示信息得到每个选购意图的至少一个选购讲解策略；
根据所述每个选购意图的至少一个选购讲解策略与所述用户进行讲解交互。
在一种可能的实现方式中，若所述最佳交互场景为手册讲解场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
根据所述交互信息分析所述用户对于车辆的至少一个功能识别意图；
根据所述至少一个功能识别意图生成对应的手册讲解信息，并根据每个功能识别意图对应的手册讲解信息得到每个功能识别意图的至少一个手册讲解策略。
在一种可能的实现方式中，若所述最佳交互场景为提醒场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
根据所述交互信息分析所述用户的通勤提醒策略和/或日程收集提醒策略；
根据所述通勤提醒策略进行通勤提醒交互，和/或根据日程收集提醒策略进行日程提醒交互。
在一种可能的实现方式中，若所述最佳交互场景为救援场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
根据所述交互信息分析所述用户的救援指导策略；
根据所述救援指导策略进行救援交互。
在一种可能的实现方式中，若所述最佳交互场景为服务场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
根据所述交互信息分析所述用户对于所述车辆的至少一个功能服务意图；
根据所述至少一个功能服务意图生成对应的服务推荐数据，并根据每个功能服务意图对应的服务推荐数据得到每个功能服务意图的至少一个服务讲解策略。
根据本公开实施例的基于AI语音助手的人机交互方法，接收用户的交互信息并识别用户的当前交互意图，由此匹配最佳交互场景，从而生成交互信息对应的交互策略，根据交互策略与用户进行交互。由此，解决了用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验等问题，通过为车辆搭载第三方AI语音助手，并对后台知识文档进行管理、交互，为用户提供了多模交互方式，从而实现车辆的全场景智能服务。
第二方面，本公开实施例提供一种基于AI语音助手的人机交互装置，所述装置包括：
接收模块，用于接收用户的交互信息；
匹配模块，用于根据所述交互信息识别所述用户的当前交互意图，并基于所述当前交互意图匹配最佳交互场景；以及
生成模块，用于基于所述最佳交互场景，生成所述交互信息对应的交互策略，根据所述交互策略与所述用户进行交互。
在一种可能的实现方式中，所述匹配模块，用于：
根据所述交互信息分析所述用户的至少一个选购意图；
根据所述至少一个选购意图生成对应的选购展示信息，并根据每个选购意图对应的选购展示信息得到每个选购意图的至少一个选购讲解策略；
根据所述每个选购意图的至少一个选购讲解策略与所述用户进行讲解交互。
在一种可能的实现方式中，所述匹配模块，用于：
根据所述交互信息分析所述用户对于车辆的至少一个功能识别意图；
根据所述至少一个功能识别意图生成对应的手册讲解信息，并根据每个功能识别意图对应的手册讲解信息得到每个功能识别意图的至少一个手册讲解策略。
在一种可能的实现方式中，所述匹配模块，用于：
根据所述交互信息分析所述用户的通勤提醒策略和/或日程收集提醒策略；
根据所述通勤提醒策略进行通勤提醒交互，和/或根据日程收集提醒策略进行日程提醒交互。
在一种可能的实现方式中，所述匹配模块，用于：
根据所述交互信息分析所述用户的救援指导策略；
根据所述救援指导策略进行救援交互。
在一种可能的实现方式中，所述匹配模块，用于：
根据所述交互信息分析所述用户对于所述车辆的至少一个功能服务意图；
根据所述至少一个功能服务意图生成对应的服务推荐数据，并根据每个功能服务意图对应的服务推荐数据得到每个功能服务意图的至少一个服务讲解策略。
根据本公开实施例的基于AI语音助手的人机交互装置，接收用户的交互信息并识别用户的当前交互意图，由此匹配最佳交互场景，从而生成交互信息对应的交互策略，根据交互策略与用户进行交互。由此，解决了用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验等问题，通过为车辆搭载第三方AI语音助手，并对后台知识文档进行管理、交互，为用户提供了多模交互方式，从而实现车辆的全场景智能服务。
第三方面，本公开实施例提供一种电子设备，包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述处理器执行所述程序，以实现如上述任一项所述的基于AI语音助手的人机交互方法。
第四方面，本公开实施例提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行，以用于实现如上述任一项所述的基于AI语音助手的人机交互方法。
本公开附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本公开的实践了解到。
附图说明
为了更清楚地说明本公开实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本公开的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本公开实施例提供的一种基于AI语音助手的人机交互方法的流程图；
图2为本公开实施例提供的一种选购场景流程图；
图3为本公开实施例提供的一种选购场景示例图；
图4为本公开实施例提供的一种手册讲解场景流程图；
图5为本公开实施例提供的一种手册讲解场景示例图；
图6为本公开实施例提供的一种提醒场景流程图；
图7为本公开实施例提供的一种提醒场景示例图；
图8为本公开实施例提供的一种救援场景流程图；
图9为本公开实施例提供的一种服务场景流程图；
图10为本公开实施例提供的一种服务场景示例图；
图11为本公开实施例提供的一种基于AI语音助手的人机交互装置的方框示例图；
图12为本公开实施例提供的一种电子设备的结构示意图。
具体实施方式
除非另作定义，此处使用的技术术语或者科学术语应当为本公开所属领域内具有一般技能的人士所理解的通常意义。本公开专利公开说明书以及权利要求书中使用的“第一”、“第二”、“第三”以及类似的词语并不表示任何顺序、数量或者重要性，而只是用来区分不同的组成部分。同样，“一个”或者“一”等类似词语也不表示数量限制，而是表示存在至少一个。“包括”或者“包含”等类似的词语意指出现在“包括”或者“包含”前面的元件或者物件涵盖出现在“包括”或者“包含”后面列举的元件或者物件及其等同，并不排除其他元件或者物件。“连接”或者“相连”等类似的词语并非限定于物理的或者机械的连接，而是可以包括电性的连接，不管是直接的还是间接的。“上”、“下”、“左”、“右”等仅用于表示相对位置关系，当被描述对象的绝对位置改变后，则所述相对位置关系也可能相应地改变。
为使本公开的目的、技术方案和优点更加清楚，下面将结合附图对本公开实施方式作进一步地详细描述。
下面详细描述本公开的实施例，实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本公开，而不能理解为对本公开的限制。
下面参考附图描述本公开实施例的基于AI语音助手的人机交互方法、装置、设备及介质。针对上述背景技术中提到的用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验的问题，本公开提供了一种基于AI语音助手的人机交互方法，在该方法中，接收用户的交互信息并识别用户的当前交互意图，由此匹配最佳交互场景，从而生成交互信息对应的交互策略，根据交互策略与用户进行交互。由此，解决了 用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验等问题，通过为车辆搭载第三方AI语音助手，并对后台知识文档进行管理、交互，为用户提供了多模交互方式，从而实现车辆的全场景智能服务。
图1为本公开实施例提供的一种基于AI语音助手的人机交互方法的流程示意图。
如图1所示，该基于AI语音助手的人机交互方法包括以下步骤：
在步骤S101中，接收用户的交互信息。
在本公开实施例中，用户在了解车辆的相关性能时，需要借助与车辆相关联的手机APP为载体，并且通过搭载于该车辆的AI语音助手对用户进行详细的讲解，以便用户根据自己的了解需求进行选购或者性能选择。
用户在了解车辆的某一性能时，可以向手机APP发送交互信息请求，该交互信息可以通过文字、语音、视频、图片等多种方式发送至手机APP，然后，手机APP接收用户发出的交互信息并对其进行分析。
在步骤S102中，根据交互信息识别用户的当前交互意图，并基于当前交互意图匹配最佳交互场景。
本公开实施例的手机APP在接收到用户的交互信息时，需要根据交互信息识别用户的当前交互意图从而匹配最佳交互场景，以便满足用户全场景的智能了解需求。其中，在本公开实施例中，最佳交互场景可以包括但不限于选购场景、手册讲解场景、提醒场景、救援场景以及服务场景。
在步骤S103中，基于最佳交互场景，生成交互信息对应的交互策略，根据交互策略与用户进行交互。
本公开实施例在根据用户的当前交互意图匹配到最佳交互场景后，可以基于最佳交互场景生成交互信息对应的交互策略，并根据交互策略与用户进行交互。
在一种可能的实现方式中，若最佳交互场景为选购场景，基于最佳交互场景，生成交互信息对应的交互策略，包括：根据交互信息分析用户的至少一个选购意图；根据至少一个选购意图生成对应的选购展示信息，并根据每个选购意图对应的选购展示信息得到每个选购意图的至少一个选购讲解策略；根据每个选购意图的至少一个选购讲解策略与用户进行讲解交互。
在本公开实施例中，若根据用户的当前交互意图匹配到的最佳交互场景为选购场景时，则生成在选购场景下对应的交互策略。
如图2和图3所示，本公开实施例以A系列车辆所搭载的手机APP为例，首先，用户在进入车辆时开始唤醒关联手机APP，并且向手机APP咨询想要了解的车辆选购信息，例如，A系列车辆的配置信息、价格信息以及预约信息等；其次，在用户向关联的手机APP咨询后，手机APP根据用户的交互意图进行分析，并且向用户显示是否调用车辆咨询信息的相关列表，若需要调用，则进一步向用户展示调用后的相关信息。
举例而言，若用户向手机APP询问A系列车辆的配置信息时，向用户显示是否调用车辆 相关的配置表，若用户想要调用车辆相关的配置表，则通过H5(HyperText Markup Language5，超文本标记语言5)链接显示车辆的配置表，并且进一步向用户展示是否需要推荐车型配置，若需要推荐，则手机APP调用车型数据库、语言库，并向用户通过文字或者语音情感播报展示车型配置表，若用户不想要调用车辆相关的配置表或者不需要推荐车型配置，则通过手机APP为用户提供其他帮助；若用户向手机APP询问A系列车辆的价格信息时，向用户显示是否调用车辆相关的售价表，若用户想要调用车辆相关的售价表，则手机APP调用车辆官网显示的售价信息，并且进一步向用户展示是否需要介绍车辆售价，若需要介绍，则手机APP调用A系列车辆的知识库、语音库，并通过专业语言向用户介绍车辆售价，若用户不想要调用车辆相关的售价表或者不需要介绍车辆价格，则通过手机APP为用户提供其他帮助；若用户向手机APP询问A系列车辆的试驾预约信息时，向用户显示是否调用车辆相关的试驾预约，若用户想要调用车辆相关的试驾预约，则进入试驾信息填写界面，并且进一步向用户展示是否需要填写试驾信息，若需要填写，则调用call center中心、语音库，并用户展示试驾预约信息，从而完成预约试驾并安排相关试驾专员，若用户不想要调用车辆相关的试驾预约信息，则通过手机APP为用户提供其他帮助。
进一步地，本公开实施例通过上述为用户提供的选购场景，实现了为潜在用户提供车辆品牌及相关信息介绍，从而最终促成销售订单。
在一种可能的实现方式中，若最佳交互场景为手册讲解场景，基于最佳交互场景，生成交互信息对应的交互策略，包括：根据交互信息分析用户对于车辆的至少一个功能识别意图；根据至少一个功能识别意图生成对应的手册讲解信息，并根据每个功能识别意图对应的手册讲解信息得到每个功能识别意图的至少一个手册讲解策略。
在本公开实施例中，若根据用户的当前交互意图匹配到的最佳交互场景为手册讲解场景时，则生成在手册讲解场景下对应的交互策略。
如图4和图5所示，首先，用户在进入车辆时开始唤醒手机APP，并且向手机APP咨询想要了解的车辆相关功能，例如，A系列车辆的发动机盖开启方法、carplay连接方法、车辆内语音识别方法以及发动机启停开关的关闭方法等；其次，在用户向关联的手机APP咨询后，向用户显示是否打开相关功能对应的电子手册，若用户选择打开电子手册，则通过手机APP生成该车辆功能对应的手册讲解策略，并向用户进行讲解。
举例而言，若用户向手机APP询问A系列车辆的发动机盖开启方法时，向用户显示是否打开发动机盖开启方法的电子手册，若用户选择打开电子手册，则调用该电子手册数据，并向用户显示是否通过视频生成手册讲解策略，若用户选择视频播放发动机盖开启方法，则通过视频为用户进行讲解，否则，通过语音播报进行讲解，若用户选择不打开电子手册，则通过手机APP为用户提供其他帮助；若用户向手机APP询问A系列车辆的carplay(一种车载系统)连接方法时，向用户显示是否打开carplay连接方法的电子手册，若用户选择打开电子手册，则调用该电子手册数据，并向用户显示是否通过视频生成手册讲解策略，若用户选择视频播放carplay连接方法的手册讲解策略，则通过视频为用户进行讲解，否则，通过语音播报进行讲解，若用户选择不打开电子手册，则通过手机APP为用户提供其他帮助；若用户向 手机APP询问A系列车辆的车辆内语音识别方法时，向用户显示是否打开车辆内语音识别方法的电子手册，若用户选择打开电子手册，则调用该电子手册数据，并向用户显示是否通过视频生成手册讲解策略，若用户选择视频播放车辆内语音识别方法的手册讲解策略，则通过视频为用户进行讲解，否则，通过语音播报进行讲解，若用户选择不打开电子手册，则通过手机APP为用户提供其他帮助；若用户向手机APP询问A系列车辆的发动机启停开关的关闭方法时，向用户显示是否打开发动机启停开关的关闭方法的电子手册，若用户选择打开电子手册，则调用该电子手册数据，并向用户显示是否通过视频生成手册讲解策略，若用户选择视频播放发动机启停开关的关闭方法的手册讲解策略，则通过视频为用户进行讲解，否则，通过语音播报进行讲解，若用户选择不打开电子手册，则通过手机APP为用户提供其他帮助。
进一步地，本公开实施例通过上述为用户提供的手册讲解场景，实现了为潜在用户提供车辆功能及相关信息介绍，满足了用户对车辆的功能了解需求。
在一种可能的实现方式中，若最佳交互场景为提醒场景，基于最佳交互场景，生成交互信息对应的交互策略，包括：根据交互信息分析用户的通勤提醒策略和/或日程收集提醒策略；根据通勤提醒策略进行通勤提醒交互，和/或根据日程收集提醒策略进行日程提醒交互。
在本公开实施例中，若根据用户的当前交互意图匹配到的最佳交互场景为提醒场景时，则生成在提醒场景下对应的交互策略。
如图6和图7所示，首先，用户在进入车辆时开始唤醒手机APP，通过手机APP向用户显示是否同意收集日常通勤信息和/或日程收集信息，在用户同意收集自己的日常通勤信息和/或日程收集信息时，分析用户的通勤提醒策略和/或日程收集提醒策略，并根据通勤提醒策略进行通勤提醒交互，和/或根据日程收集提醒策略进行日程提醒交互。
举例而言，若用户同意收集自己的日常通勤信息，则将用户的日常通勤信息上传至车辆所在的大数据平台，平台根据接收到的用户的日常通勤信息进行分析，从而生成通勤提醒策略，并向用户显示该通勤提醒策略是否需要进行播报，若用户选择播报，则手机APP根据当前行驶路线的路况向用户通过语音或者视频进行播报，例如，“您的当前通勤路线前方发生事故”等信息，此时用户可以通过手机APP选择是否推荐安全路线，若用户选择推荐安全路线，则调用当前行驶环境中的地图数据，根据地图数据向用户推荐合理路线，若用户选择不推荐安全路线，则车辆同样调用当前行驶环境中的地图数据，并根据地图数据按照原定路线继续行驶，若用户不同意收集自己的日常通勤信息，则手机APP不显示用户的日常通勤信息；若用户同意收集自己的日程收集信息，则将用户的日程收集信息上传至车辆所在的大数据平台，平台根据接收到的用户的日程收集信息进行分析，从而生成日程收集提醒策略，并向用户显示该日程收集提醒策略是否需要进行播报，例如，是否需要播报今日的天气情况，若用户选择播报，则手机APP根据今日天气预报调用天气数据，例如，“今日本市将有暴雨，请小心驾驶，关闭节能启停功能”等信息，若用户不同意收集自己的日程收集信息，则手机APP不显示用户的日程收集信息；
进一步地，本公开实施例通过上述为用户提供的提醒场景，实现了为用户维护通勤目的地，并且基于当日的天气情况、交通信息等提供出行建议，保证了用户的行车安全。
根据本公开的一个实施例，若最佳交互场景为救援场景，基于最佳交互场景，生成交互信息对应的交互策略，包括：根据交互信息分析用户的救援指导策略；根据救援指导策略进行救援交互。
在本公开实施例中，若根据用户的当前交互意图匹配到的最佳交互场景为救援场景时，则生成在救援场景下对应的交互策略。
如图7和图8所示，首先，用户在进入车辆时开始唤醒手机APP，若当前车辆发生追尾情况，则手机APP向用户显示是否需要在车辆内拍照的请求，若用户需要在车辆内拍照，则调用车辆内的行车记录仪，并拍照上传至车辆所在的大数据平台；然后，手机APP调取行车记录仪拍摄的照片，并确认事故发生地点，在确认事故发生位置后，调用当前车辆所在区域的地图数据，通过云端系统获取车辆位置信息，显示当前位置，并向用户显示是否需要救援，或者在无法确认事故发生地点时，同样向用户显示是否需要救援，若用户选择需要救援，则手机APP进一步调用紧急救援系统，并安排救援拖车及救援人员到车辆事故发生地点进行紧急救援，在用户等待救援过程中，需要用户保持电话畅通，以免错过救援人员；最后，用户在等待救援时，还需要将车辆移动到安全位置，并在车辆周围放置警示牌及设置双闪灯光以警示其他行车人员；若用户不需要在车辆内拍照，则用户可以自行下车进行拍照，并将车辆移动到安全位置，并在车辆周围放置警示牌及设置双闪灯光以警示其他行车人员。
进一步地，本公开实施例通过上述为用户提供的救援场景，实现了当用户遇到交通事故时，能够为用户提供事故处理指导，并帮助用户报案和处理救援。
根据本公开的一个实施例，若最佳交互场景为服务场景，基于最佳交互场景，生成交互信息对应的交互策略，包括：根据交互信息分析用户对于车辆的至少一个功能服务意图；根据至少一个功能服务意图生成对应的服务推荐数据，并根据每个功能服务意图对应的服务推荐数据得到每个功能服务意图的至少一个服务讲解策略。
在本公开实施例中，若根据用户的当前交互意图匹配到的最佳交互场景为服务场景时，则生成在服务场景下对应的交互策略。
如图9和图10所示，首先，用户在进入车辆时开始唤醒手机APP，通过手机APP向用户显示是否同意收集车辆保养信息，若用户同意收集车辆保养信息，则将车辆保养信息上传至车辆所在的大数据平台，平台根据接收到的用户的车辆保养信息进行分析，从而生成服务讲解策略，并向用户显示该服务讲解策略是否需要进行播报，若用户选择播报，则手机APP根据当前车辆的保养信息进行播报，例如，“您的车辆距离上次保养已经8个月了，可以对车辆进行相关保养”，此时，手机APP调用车辆所在地区的保养店信息，并根据当前车辆的目标位置为用户推荐距离车辆最近且价格适宜的车辆保养店，并向用户显示是否在该店进行预约，若用户预约该保养店，则用户填写预约信息，并调用车辆所在数据平台的CRM(Customer Relationship Management，客户关系管理)系统完成预约，并生成订单信息和预约信息，用户根据预约信息到预约的车辆保养店进行车辆的保养，并在车辆保养完成后调用订单信息，并选择订单支付方式，例如，用户可以选择调用支付系统进行支付或者通过现金进行支付；若用户不选择手机APP当前为车辆推荐的车辆保养店，则手机APP继续根据与车辆之间的距 离以及价格优惠力度为用户推荐其他车辆保养店，并向用户显示是否在该店进行预约，若用户预约该保养店，则重复上述预约步骤，若用户选择不预约该保养店，则车辆暂时关闭预约功能，并继续按照当前行驶状态行驶。
进一步地，本公开实施例通过上述为用户提供的服务场景，实现了当用户想要对车辆进行清洗、加油、充电以及保养等服务时，能够为用户提供智能推荐，实现一对一的服务功能，从而提高用户的驾乘体验。
根据本公开实施例的基于AI语音助手的人机交互方法，接收用户的交互信息并识别用户的当前交互意图，由此匹配最佳交互场景，从而生成交互信息对应的交互策略，根据交互策略与用户进行交互。由此，解决了用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验等问题，通过为车辆搭载第三方AI语音助手，并对后台知识文档进行管理、交互，为用户提供了多模交互方式，从而实现车辆的全场景智能服务。
其次参照附图描述根据本公开实施例提出的基于AI语音助手的人机交互装置。
图11是本公开实施例的基于AI语音助手的人机交互装置的方框示意图。
如图11所示，该基于AI语音助手的人机交互装置10包括：接收模块100、匹配模块200和生成模块300。
其中，接收模块100，用于接收用户的交互信息；
匹配模块200，用于根据交互信息识别用户的当前交互意图，并基于当前交互意图匹配最佳交互场景；以及
生成模块300，用于基于最佳交互场景，生成交互信息对应的交互策略，根据交互策略与用户进行交互。
在一种可能的实现方式中，匹配模块200，用于：
根据交互信息分析用户的至少一个选购意图；
根据至少一个选购意图生成对应的选购展示信息，并根据每个选购意图对应的选购展示信息得到每个选购意图的至少一个选购讲解策略；
根据每个选购意图的至少一个选购讲解策略与用户进行讲解交互。
在一种可能的实现方式中，匹配模块200，用于：
根据交互信息分析用户对于车辆的至少一个功能识别意图；
根据至少一个功能识别意图生成对应的手册讲解信息，并根据每个功能识别意图对应的手册讲解信息得到每个功能识别意图的至少一个手册讲解策略。
在一种可能的实现方式中，匹配模块200，用于：
根据交互信息分析用户的通勤提醒策略和/或日程收集提醒策略；
根据通勤提醒策略进行通勤提醒交互，和/或根据日程收集提醒策略进行日程提醒交互。
在一种可能的实现方式中，匹配模块200，用于：
根据交互信息分析用户的救援指导策略；
根据救援指导策略进行救援交互。
在一种可能的实现方式中，匹配模块200，用于：
根据交互信息分析用户对于车辆的至少一个功能服务意图；
根据至少一个功能服务意图生成对应的服务推荐数据，并根据每个功能服务意图对应的服务推荐数据得到每个功能服务意图的至少一个服务讲解策略。
根据本公开实施例的基于AI语音助手的人机交互装置，接收用户的交互信息并识别用户的当前交互意图，由此匹配最佳交互场景，从而生成交互信息对应的交互策略，根据交互策略与用户进行交互。由此，解决了用户在了解车辆功能时没有与车辆配套的手机APP智能语音助手帮助用户答疑，从而降低用户的智能体验等问题，通过为车辆搭载第三方AI语音助手，并对后台知识文档进行管理、交互，为用户提供了多模交互方式，从而实现车辆的全场景智能服务。
图12为本公开实施例提供的电子设备的结构示意图。该电子设备可以包括：
存储器1201、处理器1202及存储在存储器1201上并可在处理器1202上运行的计算机程序。
处理器1202执行程序时实现上述实施例中提供的基于AI语音助手的人机交互方法。
进一步地，电子设备还包括：
通信接口1203，用于存储器1201和处理器1202之间的通信。
存储器1201，用于存放可在处理器1202上运行的计算机程序。
存储器1201可能包含高速RAM存储器，也可能还包括非易失性存储器(non-volatile memory)，例如至少一个磁盘存储器。
如果存储器1201、处理器1202和通信接口1203独立实现，则通信接口1203、存储器1201和处理器1202可以通过总线相互连接并完成相互间的通信。总线可以是工业标准体系结构(Industry Standard Architecture，简称为ISA)总线、外部设备互连(Peripheral Component，简称为PCI)总线或扩展工业标准体系结构(Extended Industry Standard Architecture，简称为EISA)总线等。总线可以分为地址总线、数据总线、控制总线等。为便于表示，图12中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。
可选的，在具体实现上，如果存储器1201、处理器1202及通信接口1203，集成在一块芯片上实现，则存储器1201、处理器1202及通信接口1203可以通过内部接口完成相互间的通信。
处理器1202可能是一个中央处理器(Central Processing Unit，简称为CPU)，或者是特定集成电路(Application Specific Integrated Circuit，简称为ASIC)，或者是被配置成实施本公开实施例的一个或多个集成电路。
本公开实施例还提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现如上的基于AI语音助手的人机交互方法。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本公开的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或N个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本公开的描述中，“N个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更N个用于实现定制逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本公开的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本公开的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或N个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得程序，然后将其存储在计算机存储器中。
应当理解，本公开的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，N个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。如，如果用硬件来实现和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，的程序可以存储于一种计算机可读存储介质中，该程序在 执行时，包括方法实施例的步骤之一或其组合。
此外，在本公开各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本公开的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本公开的限制，本领域的普通技术人员在本公开的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (10)

  1. 一种基于AI语音助手的人机交互方法，其特征在于，所述方法包括：
    接收用户的交互信息；
    根据所述交互信息识别所述用户的当前交互意图，并基于所述当前交互意图匹配最佳交互场景；以及
    基于所述最佳交互场景，生成所述交互信息对应的交互策略，根据所述交互策略与所述用户进行交互。
  2. 根据权利要求1所述的方法，其特征在于，若所述最佳交互场景为选购场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
    根据所述交互信息分析所述用户的至少一个选购意图；
    根据所述至少一个选购意图生成对应的选购展示信息，并根据每个选购意图对应的选购展示信息得到每个选购意图的至少一个选购讲解策略；
    根据所述每个选购意图的至少一个选购讲解策略与所述用户进行讲解交互。
  3. 根据权利要求1所述的方法，其特征在于，若所述最佳交互场景为手册讲解场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
    根据所述交互信息分析所述用户对于车辆的至少一个功能识别意图；
    根据所述至少一个功能识别意图生成对应的手册讲解信息，并根据每个功能识别意图对应的手册讲解信息得到每个功能识别意图的至少一个手册讲解策略。
  4. 根据权利要求1所述的方法，其特征在于，若所述最佳交互场景为提醒场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
    根据所述交互信息分析所述用户的通勤提醒策略和/或日程收集提醒策略；
    根据所述通勤提醒策略进行通勤提醒交互，和/或根据日程收集提醒策略进行日程提醒交互。
  5. 根据权利要求1所述的方法，其特征在于，若所述最佳交互场景为救援场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
    根据所述交互信息分析所述用户的救援指导策略；
    根据所述救援指导策略进行救援交互。
  6. 根据权利要求1所述的方法，其特征在于，若所述最佳交互场景为服务场景，所述基于所述最佳交互场景，生成所述交互信息对应的交互策略，包括：
    根据所述交互信息分析所述用户对于所述车辆的至少一个功能服务意图；
    根据所述至少一个功能服务意图生成对应的服务推荐数据，并根据每个功能服务意图对应的服务推荐数据得到每个功能服务意图的至少一个服务讲解策略。
  7. 一种基于AI语音助手的人机交互装置，其特征在于，所述装置包括：
    接收模块，用于接收用户的交互信息；
    匹配模块，用于根据所述交互信息识别所述用户的当前交互意图，并基于所述当前交互意图匹配最佳交互场景；以及
    生成模块，用于基于所述最佳交互场景，生成所述交互信息对应的交互策略，根据所述交互策略与所述用户进行交互。
  8. 根据权利要求7所述的装置，其特征在于，所述匹配模块，用于：
    根据所述交互信息分析所述用户的至少一个选购意图；
    根据所述至少一个选购意图生成对应的选购展示信息，并根据每个选购意图对应的选购展示信息得到每个选购意图的至少一个选购讲解策略；
    根据所述每个选购意图的至少一个选购讲解策略与所述用户进行讲解交互。
  9. 一种电子设备，其特征在于，包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述处理器执行所述程序，以实现如权利要求1-6任一项所述的基于AI语音助手的人机交互方法。
  10. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，该程序被处理器执行，以用于实现如权利要求1-6任一项所述的基于AI语音助手的人机交互方法。
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