Dialogue processing method and device based on offline intervention module, equipment and storage medium

Abstract

The invention discloses a dialogue processing method and device based on an offline intervention module, equipment and a storage medium, and relates to the technical field of intelligent automobiles, and the method comprises the steps: obtaining a voice signal inputted by a user; performing intervention rule matching on a local intervention rule by using a text converted from the voice signal, and determining a target intervention rule; the target intervention rule is analyzed to generate the target response instruction, and the target response instruction is sent to the language processing unit to reply the voice signal, so that the user request can be quickly responded, and the processing efficiency of the system and the user experience are remarkably improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent vehicle technology, and in particular to a dialogue processing method, device, equipment and storage medium based on an offline intervention module. Background Art

[0002] With the popularity of smart cars, in-vehicle voice interaction has become an important part of the vehicle system. In the voice dialogue system, the NLU module is responsible for converting user instructions into executable operations. Traditional offline NLU models often cause misunderstandings due to environmental noise, context changes, etc., and are difficult to quickly adapt to the diverse needs of users.

[0003] However, the current solutions have problems such as untimely response, strong network dependence, large resource consumption, and affected stability in the intervention rule matching.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a dialogue processing method, device, equipment and storage medium based on an offline intervention module, aiming to solve the technical problem that the vehicle does not respond to the user's voice commands in a timely manner.

[0006] To achieve the above objectives, the present application proposes a dialogue processing method based on an offline intervention module, and the dialogue processing method based on the offline intervention module includes:

[0007] Obtaining the voice signal input by the user;

[0008] Matching the text converted from the speech signal to the local intervention rule to determine the target intervention rule;

[0009] The target intervention rule is parsed to generate a target response instruction, and the target response instruction is sent to a language processing unit to reply to the speech signal.

[0010] In one embodiment, the step of matching the text converted from the speech signal to a local intervention rule to determine a target intervention rule includes:

[0011] Preprocessing the text converted from the speech signal to obtain a preset number of processable text units;

[0012] Determining user intent and entity information based on the text unit;

[0013] Intervention rules are matched according to the user intention, the entity information and the local intervention rules to determine the target intervention rule.

[0014] In one embodiment, the step of matching intervention rules according to the user intention and the entity information with the local intervention rules to determine the target intervention rule further includes:

[0015] Perform intervention rule matching according to the user intention, the entity information and the local intervention rule, and when a preset number of intervention rules are matched, determine the priority of the preset number of intervention rules;

[0016] A target intervention rule among the preset number of intervention rules is determined according to the priority.

[0017] In one embodiment, the step of analyzing the target intervention rule to generate a target response instruction, and sending the target response instruction to the language processing unit to reply to the voice signal includes:

[0018] Parsing the target intervention rule to obtain extraction parameter information;

[0019] Constructing a target response instruction according to the parameter information;

[0020] The target response instruction is sent to the language processing unit to reply to the voice signal, and the vehicle is controlled to perform corresponding operations according to the target response instruction.

[0021] In one embodiment, before the step of obtaining a voice signal input by a user, the method further includes:

[0022] In response to a vehicle computer start signal, detecting historical update information;

[0023] When it is determined according to the historical update information that the update interval is greater than a preset time period, determining the network status;

[0024] When the network status meets the update condition, the local intervention rule is updated.

[0025] In one embodiment, when the network status satisfies the update condition, the step of updating the local intervention rule includes:

[0026] Get the cloud version information;

[0027] Compare the cloud version information with the local version information to determine whether there is data to be updated;

[0028] When it is determined that there is data to be updated, the incremental update package is downloaded;

[0029] The incremental update package is verified for integrity and legality. After the verification is completed, the local rules are updated based on the incremental update package to obtain updated local intervention rules.

[0030] In one embodiment, the method further includes:

[0031] When it is detected that the network state is abnormal or the incremental update package download fails, returning to the step of updating the local intervention rule when the network state meets the update condition;

[0032] When the result of the update processing is failure, the local intervention rule is controlled to roll back to the latest version in the local version information, and an update log is generated to record the update.

[0033] In addition, to achieve the above purpose, the present application also proposes a dialogue processing device based on an offline intervention module, the device comprising:

[0034] An acquisition module, used to acquire a voice signal input by a user;

[0035] A matching module, used for matching the text converted from the speech signal with the local intervention rule to determine the target intervention rule;

[0036] The processing module is used to parse the target intervention rule to generate a target response instruction, and send the target response instruction to the language processing unit to reply to the voice signal.

[0037] In addition, to achieve the above-mentioned purpose, the present application also proposes a dialogue processing device based on an offline intervention module, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the dialogue processing method based on the offline intervention module as described above.

[0038] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the dialogue processing method based on the offline intervention module as described above are implemented.

[0039] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the dialogue processing method based on the offline intervention module as described above are implemented.

[0040] One or more technical solutions proposed in this application have at least the following technical effects:

[0041] Acquire the voice signal input by the user; match the text converted from the voice signal to the local intervention rules to determine the target intervention rule; parse the target intervention rule to generate a target response instruction, and send the target response instruction to the language processing unit to reply to the voice signal, so as to quickly respond to user requests and significantly improve the system's processing efficiency and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0044] Figure 1 A flowchart of the first embodiment of the conversation processing method based on the offline intervention module of the present application is provided;

[0045] Figure 2 A flowchart of the second embodiment of the conversation processing method based on the offline intervention module of the present application is provided;

[0046] Figure 3 An intervention resource update flow chart provided for Embodiment 2 of the dialogue processing method based on the offline intervention module of this application;

[0047] Figure 4 A flowchart of the third embodiment of the dialogue processing method based on the offline intervention module of the present application is provided;

[0048] Figure 5 This is a schematic diagram of the module structure of a conversation processing device based on an offline intervention module according to an embodiment of the present application;

[0049] Figure 6 Schematic diagram of the device structure of the hardware operating environment involved in the dialogue processing method based on the offline intervention module in the embodiment of the present application.

[0050] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0052] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0053] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a conversation processing device based on an offline intervention module, etc. The following takes a conversation processing device based on an offline intervention module as an example to illustrate this embodiment and the following embodiments.

[0054] Based on this, the embodiment of the present application provides a dialogue processing method based on an offline intervention module, referring to Figure 1 , Figure 1 This is a flowchart of the first embodiment of the conversation processing device method based on the offline intervention module of the present application.

[0055] In this embodiment, the conversation processing device method based on the offline intervention module includes steps S10 to S30:

[0056] Step S10, obtaining a voice signal input by a user;

[0057] It should be noted that the offline intervention module consists of a local intervention engine, an intervention rule manager, an update manager, and a cache management module:

[0058] Local intervention engine: matches the user's dialogue input according to the intervention rules and outputs appropriate response content.

[0059] Intervention Rule Manager: Independently maintains the storage, loading, and caching mechanisms of rules to ensure fast call and stability of rule updates.

[0060] Incremental Update Manager: Gets rule files from the cloud regularly (once a day) and replaces them only when there are updates, reducing unnecessary download frequency and saving bandwidth.

[0061] Cache management module: implements offline caching to ensure the availability of the latest resources when there is no network connection and to ensure the accuracy of intervention in offline state.

[0062] In a specific implementation, the user speaks to the microphone of the vehicle-mounted system, and the system captures the user's voice signal through the microphone.

[0063] Step S20, matching the text converted from the speech signal with the local intervention rule to determine the target intervention rule;

[0064] It should be noted that the system uses speech recognition technology to convert the user's voice signal into readable text. Text is a written language form consisting of characters, words and sentences. In speech recognition, text refers to the text form converted from voice signals that can be read and understood by computers.

[0065] It should be understood that local intervention rules are a set of preset instructions stored on the device for recognizing and responding to specific user inputs. These rules help the system decide what to do when it hears a specific utterance;

[0066] The intervention rule matching process is the process in which the system converts the user's speech into text and compares it with the preset intervention rules to find the most appropriate rule to respond to the user's instructions;

[0067] The target intervention rule refers to the specific rule selected during the intervention rule matching process. It best matches the user's input, and the system will generate response instructions based on this rule.

[0068] In a specific implementation, the system searches for a rule that matches the user input text in the locally stored intervention rules. If a matching rule is found, the system determines this rule as the target intervention rule.

[0069] Step S30, parsing the target intervention rule to generate a target response instruction, and sending the target response instruction to the language processing unit to reply to the voice signal.

[0070] It should be noted that, according to the determined intervention rules, specific operation instructions that the system should execute are generated, and the user's voice instructions are responded to.

[0071] The language processing unit, or NLU module, is a key component in the field of dialogue systems and artificial intelligence. It is used to process and understand human language and convert the user's natural language input into structured data or commands that the computer can understand and execute.

[0072] In the specific implementation, the intervention module parses the parameters in the rule and outputs the corresponding instructions, which are fed back to the NLU module for immediate response.

[0073] In a feasible implementation, step S30 may include steps A11 to A13:

[0074] A11: Analyze the target intervention rules and obtain the extraction parameter information;

[0075] In the specific implementation, the key information required to perform the operation is extracted from the target intervention rule; the system analyzes the target intervention rule and finds out the parameters defined in the rule, such as temperature value, switch status, etc.

[0076] A12: Construct a target response instruction based on the parameter information;

[0077] In the specific implementation, the specific instructions that the system needs to execute are constructed according to the extracted parameter information; the system generates a clear operation instruction based on the parameter information, such as "set the air conditioning temperature to 24 degrees."

[0078] A13: Send the target response instruction to the language processing unit to reply to the voice signal, and control the vehicle to perform corresponding operations according to the target response instruction.

[0079] It should be noted that controlling the vehicle to perform a corresponding operation means that the system adjusts a function or setting of the vehicle according to the target response instruction, such as adjusting the volume, changing the temperature, or navigating to a certain location.

[0080] In the specific implementation, the system sends the target response instruction to the language processing unit; the language processing unit converts the text instruction into voice reply to the user; at the same time, the system controls the vehicle to perform corresponding operations according to the response instruction, such as adjusting the air-conditioning temperature.

[0081] This embodiment provides a dialogue processing method based on an offline intervention module, which obtains a voice signal input by a user; matches the text converted from the voice signal with the local intervention rule to determine the target intervention rule; parses the target intervention rule to generate a target response instruction, and sends the target response instruction to the language processing unit to reply to the voice signal, thereby being able to quickly respond to user requests and significantly improve the system's processing efficiency and user experience.

[0082] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the above-mentioned embodiment 1 can be referred to the above introduction, and will not be repeated in the following. Figure 2 , before step S10, including steps S101 to S103:

[0083] Step S101, in response to a vehicle computer start signal, detecting historical update information;

[0084] It should be noted that the current voice dialogue system is unable to efficiently update and correct offline resources after release; the update process interferes with normal use and affects the continuous interaction effect of voice; the update process affects the normal use of voice and other problems.

[0085] In a specific implementation, when the vehicle's onboard system (vehicle computer) is started, the system will send a start signal; the system will check the time and content of the last update to determine whether there is a new update that needs to be applied.

[0086] Step S102, when it is determined according to the historical update information that the update interval is greater than a preset time length, the network status is determined;

[0087] It should be noted that the preset duration can be set, such as 24 hours, 48 ​​hours, etc.

[0088] In the specific implementation, the system will compare the current time and the time of the last update to see if it exceeds the set time interval (such as 24 hours). If the time interval meets the conditions, the system will check whether the vehicle is connected to the Internet to ensure that the update can be downloaded.

[0089] Step S103: When the network status meets the update condition, the local intervention rule is updated.

[0090] In the specific implementation, check the cloud version information; download the incremental update package and verify the integrity and legality; after success, replace the local intervention resources; after the update is completed, save the latest rule version information.

[0091] It should be noted that the intervention rule configuration file of the local intervention rule adopts JSON format, which contains the unique identifier, matching mode, priority, response parameters and other fields of the intervention rule, so as to ensure that the rule content can be efficiently queried and called in an offline state. The file format example is as follows:

[0092]

[0093] In a feasible implementation, step S103 may include steps A21 to A24:

[0094] A21: Get cloud version information;

[0095] In the specific implementation, the system will send a request to the cloud to obtain the latest intervention rule version information.

[0096] A22: Compare the cloud version information with the local version information to determine whether there is data to be updated.

[0097] In the specific implementation, the system will compare the cloud version number with the local version number. If the cloud version is newer, there is data to be updated.

[0098] A23: When it is determined that there is data to be updated, the incremental update package is downloaded;

[0099] In the specific implementation, if there is a new update in the cloud, the system will download an incremental update package, which only contains the parts that have changed since the last update to save bandwidth and time.

[0100] A24: Verify the integrity and legitimacy of the incremental update package. After the verification is completed, update the local rules based on the incremental update package to obtain updated local intervention rules.

[0101] In the specific implementation, the system will check whether the downloaded update package is complete, not damaged, and the source is legal; if the verification passes, the system will apply the update package and update the local intervention rules.

[0102] Further, when it is detected that the network status is abnormal or the incremental update package download fails, the step of returning to the step of updating the local intervention rule when the network status meets the update condition;

[0103] When the result of the update processing is failure, the local intervention rule is controlled to roll back to the latest version in the local version information, and an update log is generated to record this update.

[0104] It should be noted that if an abnormal network status is detected or the incremental update package download fails, the system will retry the update process; if the update process fails, the system will roll back the local intervention rules to the last successfully updated version to ensure system stability;

[0105] Regardless of whether the update is successful or not, the system will generate an update log that records detailed information about the update, including time, results, and any error messages.

[0106] like Figure 3 As shown, Figure 3 To intervene in the resource update flow chart, first, after the vehicle is turned on, check whether the intervention update conditions are met. If they are met, request the cloud version for version comparison. After version comparison, if it is determined that an update is needed, download the corresponding incremental intervention script and perform update verification. After the update is successful, update the local rules. If the update fails, roll back and re-download the incremental intervention script.

[0107] This embodiment provides a dialogue processing method based on an offline intervention module, which detects historical update information in response to a vehicle computer start signal; determines the network status when the update interval is greater than a preset time according to the historical update information; and updates the local intervention rules when the network status meets the update conditions. The system can ensure that the intervention rules are always kept up to date while maintaining the stability and security of the system during the update process.

[0108] Based on the first and second embodiments of the present application, in the third embodiment of the present application, the same or similar contents as those in the above embodiments can be referred to the above introduction, and will not be described in detail later. Figure 4 , step S20, including steps S201 to S203:

[0109] Step S201, preprocessing the text converted from the speech signal to obtain a preset number of processable text units;

[0110] It should be noted that the purpose is to make the text converted by the speech recognition system more standardized to facilitate subsequent processing and analysis.

[0111] In the specific implementation, it includes removing irrelevant characters in the text, such as extra spaces, punctuation marks, etc.; splitting continuous text into words or phrases so that each word can be processed separately; converting the text to a unified format, such as converting all letters to lowercase, to reduce the variables to be processed.

[0112] Step S202, determining user intention and entity information according to the text unit;

[0113] It should be noted that user intent refers to the purpose or action that the user conveys through language. For example, if the user says "navigate to the nearest coffee shop", their intention is to start navigation to the coffee shop;

[0114] Entity information refers to the specific information in the user's speech, such as name, place, time, etc.

[0115] In the specific implementation, by analyzing the text content, the user's main purpose is determined, such as "navigating to the mall" or "playing music"; key information such as location, time, name, etc. is extracted from the text, which is important for executing the user request.

[0116] Step S203: Match intervention rules according to user intention and entity information and local intervention rules to determine target intervention rules.

[0117] To be clear, the goal is to find the rules that best fit the user's request so that the system knows how to respond.

[0118] It should be understood that intervention rule matching refers to the process by which the system compares the user's intention and entity information with the preset intervention rules to find the most appropriate rule to respond to the user's instructions.

[0119] In a specific implementation, the user's intention and entity information are compared with the locally stored intervention rules to find matching rules.

[0120] In a feasible implementation, step S203 may include steps A31 to A32:

[0121] A31: Match intervention rules according to user intent and entity information and local intervention rules, and when a preset number of intervention rules are matched, determine the priority of the preset number of intervention rules;

[0122] It should be noted that the preset number of intervention rules means that multiple rule matches are determined at this time, and the most appropriate rule needs to be selected according to priority.

[0123] A32: Determine the target intervention rule among the preset number of intervention rules according to the priority.

[0124] In a specific implementation, when a user's request can match multiple rules, it is determined which rules should be given priority, and all matching rules are prioritized based on the importance or relevance of the rules.

[0125] This embodiment provides a dialogue processing method based on an offline intervention module, which can understand the user's voice instructions, extract key information, and find the most appropriate rules to respond to the user's request. This process ensures that the system can accurately understand and respond to the user's needs, improving the efficiency and accuracy of the interaction.

[0126] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the dialogue processing method based on the offline intervention module of the present application. More simple transformations based on this technical concept are all within the scope of protection of the present application.

[0127] This application also provides a dialogue processing device based on an offline intervention module, please refer to Figure 5 , the dialogue processing device based on the offline intervention module includes:

[0128] An acquisition module 10 is used to acquire a voice signal input by a user;

[0129] A matching module 20, configured to match the text converted from the speech signal with the local intervention rule to determine a target intervention rule;

[0130] The processing module 30 is used to parse the target intervention rule to generate a target response instruction, and send the target response instruction to the language processing unit to reply to the voice signal.

[0131] The dialogue processing device based on the offline intervention module provided by the present application adopts the dialogue processing method based on the offline intervention module in the above embodiment, which can solve the technical problem that the vehicle does not respond to the user's voice command in a timely manner. Compared with the prior art, the beneficial effects of the dialogue processing device based on the offline intervention module provided by the present application are the same as the beneficial effects of the dialogue processing method based on the offline intervention module provided by the above embodiment, and the other technical features of the dialogue processing device based on the offline intervention module are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0132] In one embodiment, the matching module 20 is further used to pre-process the text converted from the speech signal to obtain a preset number of processable text units;

[0133] Determine user intent and entity information based on text units;

[0134] Intervention rules are matched according to user intent, entity information and local intervention rules to determine the target intervention rules.

[0135] In one embodiment, the matching module 20 is further used to match intervention rules according to user intention and entity information and local intervention rules, and when a preset number of intervention rules are matched, determine the priority of the preset number of intervention rules;

[0136] A target intervention rule among a preset number of intervention rules is determined according to the priority.

[0137] In one embodiment, the processing module 30 is further used to parse the target intervention rule to obtain extraction parameter information;

[0138] Constructing target response instructions according to parameter information;

[0139] The target response instruction is sent to the language processing unit to reply to the voice signal, and the vehicle is controlled to perform corresponding operations according to the target response instruction.

[0140] In one embodiment, the acquisition module 10 is further used to detect the historical update information in response to the vehicle computer start signal;

[0141] When it is determined based on historical update information that the update interval is greater than a preset time, determining the network status;

[0142] When the network status meets the update conditions, the local intervention rules are updated.

[0143] In one embodiment, the acquisition module 10 is further used to obtain cloud version information;

[0144] Compare the cloud version information with the local version information to determine whether there is data to be updated;

[0145] When it is determined that there is data to be updated, the incremental update package is downloaded;

[0146] The integrity and legality of the incremental update package are verified. After the verification is completed, the local rules are updated based on the incremental update package to obtain updated local intervention rules.

[0147] In one embodiment, the acquisition module 10 is further configured to return to the step of updating the local intervention rule when the network status meets the update condition when it is detected that the network status is abnormal or the incremental update package download fails;

[0148] When the result of the update processing is failure, the local intervention rule is controlled to roll back to the latest version in the local version information, and an update log is generated to record this update.

[0149] The present application provides a dialogue processing device based on an offline intervention module, and the dialogue processing device based on the offline intervention module includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the dialogue processing method based on the offline intervention module in the above-mentioned embodiment 1.

[0150] Reference below Figure 6 , which shows a schematic diagram of the structure of a dialogue processing device based on an offline intervention module suitable for implementing the embodiment of the present application. The dialogue processing device based on the offline intervention module in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The dialogue processing device based on the offline intervention module shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0151] like Figure 6As shown, the dialogue processing device based on the offline intervention module may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. Various programs and data required for the operation of the dialogue processing device based on the offline intervention module are also stored in the RAM 1004. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the dialogue processing device based on the offline intervention module to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a dialogue processing device based on the offline intervention module with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0152] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0153] The dialogue processing device based on the offline intervention module provided by the present application adopts the dialogue processing method based on the offline intervention module in the above embodiment, which can solve the technical problem that the vehicle does not respond to the user's voice command in a timely manner. Compared with the prior art, the beneficial effects of the dialogue processing device based on the offline intervention module provided by the present application are the same as the beneficial effects of the dialogue processing device method based on the offline intervention module provided by the above embodiment, and the other technical features of the dialogue processing device based on the offline intervention module are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0154] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0155] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0156] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the dialogue processing method based on the offline intervention module in the above-mentioned embodiment.

[0157] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0158] The computer-readable storage medium may be included in the dialogue processing device based on the offline intervention module; or may exist independently without being assembled into the dialogue processing device based on the offline intervention module.

[0159] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the dialogue processing device based on the offline intervention module, the dialogue processing device based on the offline intervention module: obtains the voice signal input by the user; matches the text converted from the voice signal with the local intervention rules to determine the target intervention rule; parses the target intervention rule to generate a target response instruction, and sends the target response instruction to the language processing unit to reply to the voice signal.

[0160] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and 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's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0161] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0162] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0163] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned dialogue processing method based on the offline intervention module, and can solve the technical problem that the vehicle does not respond to the user's voice command in a timely manner. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the dialogue processing method based on the offline intervention module provided by the above-mentioned embodiment, and will not be repeated here.

[0164] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned dialogue processing method based on the offline intervention module when executed by a processor.

[0165] The computer program product provided by the present application can solve the technical problem that the vehicle does not respond to the user's voice command in a timely manner. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the dialogue processing method based on the offline intervention module provided in the above embodiment, which will not be repeated here.

[0166] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A dialogue processing method based on an offline intervention module, characterized in that: The dialogue processing method based on the offline intervention module includes: Obtaining the voice signal input by the user; Matching the text converted from the speech signal to the local intervention rule to determine the target intervention rule; The target intervention rule is parsed to generate a target response instruction, and the target response instruction is sent to a language processing unit to reply to the speech signal.

2. The dialogue processing method based on the offline intervention module according to claim 1, characterized in that: The step of matching the text converted from the speech signal with the local intervention rule to determine the target intervention rule comprises: Preprocessing the text converted from the speech signal to obtain a preset number of processable text units; Determining user intent and entity information based on the text unit; Intervention rules are matched according to the user intention, the entity information and the local intervention rules to determine the target intervention rule.

3. The dialogue processing method based on the offline intervention module according to claim 2, characterized in that: The step of matching intervention rules according to the user intention and the entity information with the local intervention rules to determine the target intervention rule also includes: Perform intervention rule matching according to the user intention, the entity information and the local intervention rule, and when a preset number of intervention rules are matched, determine the priority of the preset number of intervention rules; A target intervention rule among the preset number of intervention rules is determined according to the priority.

4. The dialogue processing method based on the offline intervention module according to claim 1, characterized in that: The step of analyzing the target intervention rule to generate a target response instruction, and sending the target response instruction to the language processing unit to reply to the voice signal includes: Parsing the target intervention rule to obtain extraction parameter information; Constructing a target response instruction according to the parameter information; The target response instruction is sent to the language processing unit to reply to the voice signal, and the vehicle is controlled to perform corresponding operations according to the target response instruction.

5. The dialogue processing method based on the offline intervention module according to claim 1, characterized in that: Before the step of obtaining the voice signal input by the user, the method further includes: In response to a vehicle computer start signal, detecting historical update information; When it is determined according to the historical update information that the update interval is greater than a preset time period, determining the network status; When the network status meets the update condition, the local intervention rule is updated.

6. The dialogue processing method based on the offline intervention module according to claim 5, characterized in that: The step of updating the local intervention rule when the network state meets the update condition includes: Get the cloud version information; Compare the cloud version information with the local version information to determine whether there is data to be updated; When it is determined that there is data to be updated, the incremental update package is downloaded; The incremental update package is verified for integrity and legality. After the verification is completed, the local rules are updated based on the incremental update package to obtain updated local intervention rules.

7. The dialogue processing method based on the offline intervention module according to claim 5, characterized in that: The method further comprises: When it is detected that the network state is abnormal or the incremental update package download fails, returning to the step of updating the local intervention rule when the network state meets the update condition; When the result of the update processing is failure, the local intervention rule is controlled to roll back to the latest version in the local version information, and an update log is generated to record the update.

8. A dialogue processing device based on an offline intervention module, characterized in that: The device comprises: An acquisition module, used to acquire a voice signal input by a user; A matching module, used for matching the text converted from the speech signal with the local intervention rule to determine the target intervention rule; The processing module is used to parse the target intervention rule to generate a target response instruction, and send the target response instruction to the language processing unit to reply to the voice signal.

9. A conversation processing device based on an offline intervention module, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the dialogue processing method based on the offline intervention module as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the dialogue processing method based on the offline intervention module as described in any one of claims 1 to 7 are implemented.

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