WO2022037019A1 - Système, procédé et dispositif destinés à mettre en œuvre une conversation personne-machine en plusieurs étapes - Google Patents

Système, procédé et dispositif destinés à mettre en œuvre une conversation personne-machine en plusieurs étapes Download PDF

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WO2022037019A1
WO2022037019A1 PCT/CN2021/074352 CN2021074352W WO2022037019A1 WO 2022037019 A1 WO2022037019 A1 WO 2022037019A1 CN 2021074352 W CN2021074352 W CN 2021074352W WO 2022037019 A1 WO2022037019 A1 WO 2022037019A1
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user
node
intent
dialogue
configuration
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PCT/CN2021/074352
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English (en)
Chinese (zh)
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陶阔
韩燕�
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第四范式（北京）技术有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/451—Execution arrangements for user interfaces
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/008—Artificial life, i.e. computing arrangements simulating life based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods

Definitions

  • the present disclosure relates to the field of artificial intelligence, and more particularly, to a system, method and apparatus for realizing multi-round dialogue between humans and machines.
  • multi-round human-machine dialogue is becoming more and more extensive, such as intelligent dialogue robots for hotel reservations, air tickets, etc.
  • the purpose of multi-round human-machine dialogue is to obtain the necessary information through a series of questions after obtaining the user's initial intention to finally provide information and services corresponding to the user's intention.
  • the purpose of the present disclosure is to provide a system, method and device for realizing multi-turn human-machine dialogue.
  • a first aspect of the present disclosure provides a system for implementing multi-turn human-machine dialogue including at least one computing device and at least one storage device, wherein the at least one storage device stores instructions, and the instructions, when executed by the at least one computing device, cause the At least one computing device executes the following steps of a method for implementing a multi-round human-machine dialogue: providing a user configuration interface, wherein multiple types of intent nodes are provided in the user configuration interface; selecting an intent node on the user configuration interface based on the first user, Configure the intent node and the operation of connecting the intent node, and construct the intent unit; realize the multi-round dialogue with the second user based on the intent unit, so as to obtain the key intention of the second user in the multi-round dialogue between the human and the computer, and realize the judgment and prediction of the dialogue .
  • a second aspect of the present disclosure provides a method for implementing a multi-turn human-machine dialogue, the method comprising: providing a user configuration interface, wherein multiple types of intent nodes are provided in the user configuration interface; based on the first user On the user configuration interface, select the intent node, configure the intent node, and connect the intent node to construct an intent unit; based on the intent unit, implement multiple rounds of human-machine dialogue with the second user to obtain the second user's human-computer Key intentions in multiple rounds of dialogue to realize judgment and prediction of dialogue.
  • a third aspect of the present disclosure provides an apparatus for implementing a multi-turn human-machine dialogue, the apparatus comprising: a user configuration interface providing unit for providing a user configuration interface, wherein the user configuration interface providing unit provides in the user configuration interface multiple types of intent nodes; an intent unit construction unit, based on the operation of the first user to select an intent node, configure an intent node, and connect an intent node on the user configuration interface, construct an intent unit; a man-machine multi-round dialogue implementation unit, Based on the intention unit, a multi-round dialogue with the second user is implemented, so as to obtain the key intention of the second user in the multi-round dialogue between the human and the computer, so as to realize the judgment and prediction of the dialogue.
  • a fourth aspect of the present disclosure provides a computer-readable storage medium having stored thereon a computer program that, when executed by one or more computing devices, causes the one or more computing devices
  • the apparatus implements any of the methods described above.
  • the present disclosure can flexibly select intent nodes, configure intent nodes, and connect intent nodes on the user configuration interface according to the first user's own business needs and business experience, so as to construct the second user-oriented intent for the dialog robot program. unit. Therefore, the dialog robot program can flexibly respond to the user's complex dialog situation based on the intent unit oriented to the second user, and effectively acquire the user's key intent, thereby providing accurate information and services.
  • FIG. 1 shows a flowchart of a method for implementing a multi-round dialogue between humans and machines according to an embodiment of the present disclosure
  • FIG. 3 shows a schematic diagram of a configuration of an input node according to an embodiment of the present disclosure
  • FIG. 4 shows a schematic diagram of a configuration of a judgment node according to an embodiment of the present disclosure
  • FIG. 5 shows a schematic diagram of the configuration of an input node according to an embodiment of the present disclosure
  • FIG. 6 shows a schematic diagram of the configuration of an assignment node according to an embodiment of the present disclosure
  • FIG. 7 shows a schematic diagram of the configuration of an interface node according to an embodiment of the present disclosure
  • FIG. 8 shows an apparatus for realizing multi-round dialogue between humans and machines according to an embodiment of the present disclosure
  • 10B shows the configuration of the input node and the configuration of the judgment node of the construction intent unit shown in 10A;
  • 10C shows the configuration of the output node corresponding to parameter logic 1 and the configuration of the output node corresponding to parameter logic 2 and the configuration of adding task parameters of the build intent unit shown in 10A;
  • FIG. 10D illustrates a configuration interface for adding task parameters according to an embodiment of the present disclosure
  • FIG. 11A shows a further constructed intent unit for the second-round dialogue of the example of the man-machine multi-round dialogue shown in FIG. 9;
  • 12B shows the configuration of the input node and the configuration of the judgment node of the construction intent unit shown in 12A;
  • 12C shows the configuration of the output node corresponding to parameter logic 1 and the configuration of the output node corresponding to parameter logic 2 of the build intent unit shown in 12A;
  • FIG. 13A shows a further constructed intent unit for the fourth round of the example of the man-machine multi-round dialogue shown in FIG. 9;
  • 13B shows the configuration of the input node and the configuration of the judgment node of the construction intent unit shown in 13A;
  • 13C shows the configuration of the output node corresponding to parameter logic 1 and the configuration of the output node corresponding to parameter logic 2 of the build intent unit shown in 13A;
  • Figure 14B shows the configuration of the fifth-round dialogue-based input node, the assignment node, and the judgment node with the construction intent unit shown in 14A;
  • Fig. 14E shows the configuration of the output node corresponding to parameter logic 1 and the configuration of the output node corresponding to parameter logic 2 based on the sixth round of dialogue of the construction intent unit shown in 14A;
  • 16B shows the configuration of the input node and the configuration of the judgment node of the construction intent unit shown in 16A;
  • FIG. 1 shows a flowchart of a method for implementing a multi-turn human-machine dialogue according to an embodiment of the present disclosure.
  • step S110 a user configuration interface is provided, wherein the user configuration interface provides multiple types of intent nodes.
  • the various types of intent nodes include one or more of the following: an input node, a judgment node, an output node, an assignment node, and an interface node. These nodes will be described in more detail later.
  • step S120 an intent unit is constructed based on the first user's operations of selecting an intent node, configuring an intent node, and connecting an intent node on the user configuration interface.
  • the first user may be the user who builds the intent unit.
  • the first user may be a service provider that provides information or services (eg, hotel reservation, bus ticket reservation, air ticket reservation, information consultation, etc.).
  • the first user can flexibly choose to select intent nodes, configure intent nodes, and connect intent nodes on the user configuration interface according to their own business needs and business experience, so as to build a flexible second-user-oriented dialog robot program.
  • Intent unit the first user can flexibly choose to select intent nodes, configure intent nodes, and connect intent nodes on the user configuration interface according to their own business needs and business experience, so as to build a flexible second-user-oriented dialog robot program.
  • the first user may be based on historical data (eg, related to needs, habits, and/or preferences, etc.) based on business context (eg, its target users (eg, second users using information or services provided by the first user) data)) to select intent nodes, configure intent nodes, and connect intent nodes on the user configuration interface, thereby constructing a flexible intent unit for the second user.
  • business context eg, its target users (eg, second users using information or services provided by the first user) data
  • the present disclosure is not limited thereto, and the first user may also select intent nodes, configure intent nodes, and connect intent nodes on the user configuration interface according to any other method, thereby constructing a flexible intent unit for the second user.
  • a single intent unit can execute multiple rounds of a single-intent human-machine dialogue.
  • step S130 based on the intention unit, the human-machine multi-round dialogue with the second user is realized, so as to obtain the key intention of the second user in the human-machine multi-round dialogue, so as to realize the judgment and prediction of the dialogue.
  • the conversational robot program can flexibly and effectively implement multi-turn human-machine conversations with the second user based on the intent unit, so as to Obtain explicit instructions from the second user.
  • the method of implementing a multi-turn dialogue between humans and machines may be performed by a dialogue robot program that provides services or information.
  • FIG. 2 shows a schematic diagram of constructing an intent unit in a user configuration interface according to an embodiment of the present disclosure.
  • a user configuration interface 200 may include a first area 210 in which various types of intent nodes are arranged and a second area 220 for constructing an intent unit.
  • the sizes and positions of the first area 210 and the second area 220 may be arbitrarily set, and are not limited to the example in FIG. 2 .
  • FIG. 2 shows five types of intent nodes (ie, input nodes, judgment nodes, output nodes, assignment nodes, and interface nodes), the intent nodes of the present disclosure are not limited to the above-mentioned nodes, or may include input nodes , one or more of a judgment node, an output node, an assignment node, and an interface node.
  • all the intent nodes here can be configured by the first user, so personalized services or functions can be provided according to the needs of the first user.
  • the first user may select (eg, drag, click, etc.) an intent node from the first area, so that the selected corresponding intent node appears in the second area.
  • the first user can flexibly configure the selected intent node, so that the intent node can perform respective functions or operations according to the flexible configuration, so that the key intent of the second user can be acquired and the usage requirements or intent requirements of the second user can be met. .
  • the first user can also connect the selected intent nodes, so that the connected intent nodes can perform operations corresponding to the intent units according to the connected logical relationship.
  • FIG. 3 shows a schematic diagram of the configuration of an input node according to an embodiment of the present disclosure.
  • the configuration item of the input node may include a trigger method for triggering the task "hotel reservation” (eg, the second user talks to the dialog robot program “please book hotel A for me” and “book hotel for me”) and similar questions to trigger questions (eg, the second user talks to the conversational bot “I want to book a hotel” and "help me book a hotel”).
  • a trigger method for triggering the task "hotel reservation” eg, the second user talks to the dialog robot program "please book hotel A for me” and “book hotel for me”
  • similar questions to trigger questions eg, the second user talks to the conversational bot "I want to book a hotel” and "help me book a hotel”).
  • configuration items of the input node may also include task parameters (eg, hotel name, check-in time, etc.) that are set based on the trigger method and/or a method similar to the trigger method.
  • task parameters eg, hotel name, check-in time, etc.
  • the symbol of the pen may indicate that information can be entered, and the trash can indicate that it can be deleted.
  • the configuration of the judgment node shown in FIG. 4 is schematic, and the present disclosure is not limited thereto.
  • the judgment node of the present disclosure may include one or more of the configuration items shown in FIG. 4 , or may include other configuration items.
  • the configuration item of the judgment node includes parameter logic, wherein the parameter logic performs logical condition judgment on the value obtained by the previous node and the known value or the user-defined value, and determines the judgment node based on the mutually exclusive judgment results the next node.
  • the parameter logic may include parameter logic corresponding to an empty slot. Therefore, when the slot of the second user is empty in the multi-round man-machine dialogue, the dialogue robot program can also provide a corresponding logical judgment mechanism, so that the multi-round man-machine dialogue can proceed smoothly.
  • the configuration items of the judgment node include parameter logic 1 and parameter logic 2 .
  • parameter logic 1 may correspond to the case where "hotel name” is empty
  • parameter logic 2 may correspond to the case where "hotel name” is A hotel.
  • the first user can save the configured parameter logic through the button "Save Logic”.
  • the task of the judgment node can be configured as "hotel”.
  • parameter logic 1 and parameter logic 2 are parallel parameter logics.
  • the judgment node can judge that parameter logic 2 (ie, the hotel name is empty) is established, and then judge the next node according to parameter logic 2.
  • the configuration items of the parameter logic may include a user-defined judgment value, a user-defined logical relationship, and a user-defined reference value, wherein the parameter logic is configured to determine whether the user-defined judgment value and the user-defined reference value satisfy the user-defined logic relationship , and determine the next node of the judgment node based on the determined result.
  • FIG. 5 shows a schematic diagram of a configuration of an input node according to an embodiment of the present disclosure.
  • the configuration of the output nodes shown in FIG. 5 is schematic, and the present disclosure is not limited thereto.
  • the output node of the present disclosure may include one or more of the configuration items shown in FIG. 5 , or may include other configuration items.
  • the output node is configured to perform the task "Robot asks for hotel name".
  • the first user can configure multiple reply contents.
  • the first user can configure the reply content "Which hotel would you like to book?”.
  • the first user may configure the reply content based on the second user's intent and the context of the conversation.
  • the predetermined form of outputting the reply content to the second user may include pictures, voices, links, menus and rich texts.
  • the output node can be configured to provide multi-form replies based on task parameters and interface return values to meet various needs of the second user.
  • the configuration of the assignment node shown in FIG. 6 is schematic, and the present disclosure is not limited thereto.
  • the value node of the present disclosure may include one or more of the configuration items shown in FIG. 6 , or may include other configuration items.
  • a custom assignment may be configured as a customer type of the second user, wherein the customer type is shown to include intended users, potential users, and invalid customers. Therefore, in the multi-round man-machine dialogue of the second user, the effective classification of customers can be realized.
  • FIG. 7 shows a schematic diagram of the configuration of an interface node according to an embodiment of the present disclosure.
  • the configuration of the interface node shown in FIG. 7 is schematic, and the present disclosure is not limited thereto.
  • the interface node of the present disclosure may include one or more of the configuration items shown in FIG. 7 , or may include other configuration items.
  • the configuration item of the interface node includes a configuration item configured to support interface information retrieval configuration.
  • the interface node may be configured to correspond to the task "vacancy query".
  • the configuration item "interface name” of the interface node can be configured to call the interface corresponding to the "interface name”
  • the configuration item "URL” of the interface node can be configured to call the uniform resource locator corresponding to the "URL” .
  • the configuration item "request type” of the interface node can be selected as different types according to the configuration of the first user. Currently, HTTP_GET and HTTP_POST are provided.
  • the first user can better provide the interface return value by setting input parameters and output parameters according to the regulations corresponding to the intention of the second user.
  • the first user can configure the parameter values obtained from the user (for example, information about hotel name, check-in time, room type, etc.), and the configuration items about the output parameters can be based on Enter the configuration item of the parameter to configure. (For example, based on the hotel name, check-in time, check-in room type and other information, the vacancy information that meets the corresponding conditions is called from the interface)
  • the apparatus 800 for implementing a multi-turn human-machine dialogue may include a user configuration interface providing unit 810 , an intention unit constructing unit 820 and a human-machine multi-turn dialogue implementing unit 830 .
  • the user configuration interface providing unit 810 may provide a user configuration interface, wherein the user configuration interface providing unit 810 provides various types of intent nodes in the user configuration interface.
  • the intent unit construction unit 820 may construct the intent unit based on the operations of the first user to select the intent node, configure the intent node, and connect the intent node on the user configuration interface.
  • the man-machine multi-turn dialogue realization unit 830 may implement the man-machine multi-turn dialogue with the second user based on the intention unit, so as to obtain explicit instructions of the second user.
  • USER may represent a second user who conducts multiple rounds of man-machine dialogue with the dialogue robot program ROBT.
  • the dialogue content of the second user in the first round of dialogue in the example of the man-machine multi-round dialogue shown in FIG. 9 is "please book a flight ticket for me”.
  • the first user can construct the intent unit shown in FIG. 10A based on the dialogue content of the second user "please book a flight ticket for me”.
  • the decision node may be configured to perform the task "vote count decision".
  • the second user can configure the parameter logic to include parameter logic 1 and parameter logic 2, where parameter logic 1 is configured to indicate the "votes are empty" condition, and parameter logic 2 is configured to indicate "the votes belong to (parameter dictionary) numbers. Dictionary" case.
  • a digital dictionary as an example of a parameter dictionary may record information on the number of votes.
  • the output node corresponding to parameter logic 1 may be configured to perform the task "parameter logic 1 votes”.
  • the output node corresponding to parameter logic 1 may be configured to output "Please confirm the number of votes you need" to the second user.
  • the reply content may be output using one or more of the output forms shown in FIG. 10C.
  • the output node corresponding to parameter logic 2 may be configured to perform the task "parameter logic 2 origin”.
  • the output node corresponding to parameter logic 2 may be configured to output "Where is your origin?" to the second user.
  • the dialogue robot program can output the content to the first user based on the intent units configured in FIGS. 10A to 10C , “May I ask your departure Where is it?".
  • FIG. 10D illustrates a configuration interface for adding task parameters according to an embodiment of the present disclosure.
  • “Add Task Parameters” may pop up.
  • parameter names can be configured, and parameter dictionaries (eg, system numbers) can be configured from built-in dictionary 1, built-in dictionary 2, user dictionary 1, and user dictionary 2.
  • parameter dictionaries can be added via "Parameter Dictionary+”.
  • the dialogue content of the second user in the second round of dialogue in the example of the man-machine multi-round dialogue shown in FIG. 9 is "Beijing".
  • the first user may construct the intent unit shown in FIG. 11A based on the conversation content "Beijing" of the second user.
  • the portion of the newly constructed intent unit of FIG. 11A compared to FIG. 10A may correspond to the portion in the block in FIG. 11A .
  • the input node is configured to perform the task "departure city”.
  • the second user can configure the configuration item "trigger question method” of the input node to include “Beijing” and “book air tickets for me”, and configure the configuration item "similar question method” of the input node to include “book air tickets”.
  • the second user can also configure the "departure place” of the slot, and the information of the slot can be the system location (eg, Beijing).
  • the slot may further include the number of tickets, and the information of the slot may be "one ticket”.
  • the decision node may be configured to perform the task "judgment at origin".
  • the second user can configure the parameter logic to include parameter logic 1 and parameter logic 2, where parameter logic 1 is configured to indicate the "Origin is empty" condition, and parameter logic 2 is configured to indicate "The departure belongs to (parameter dictionary) ) dictionary of the place of departure".
  • the departure place dictionary may record information on the departure place.
  • the intent unit may be configured to include two output nodes (ie, an output node corresponding to parameter logic 1 and an output node corresponding to parameter logic 2 ).
  • the output node corresponding to parameter logic 1 may be configured to perform the task "parameter logic 1 output".
  • the output node corresponding to the parameter logic 1 may be configured to output "Please confirm your origin and tell me again" to the second user.
  • the reply content may be output using one or more of the output forms shown in FIG. 11C.
  • the output node corresponding to parameter logic 2 may be configured to perform the task "parameter logic 2 output”.
  • the output node corresponding to parameter logic 2 may be configured to output "Which airport are you departing from, Beijing, please?" to the second user.
  • the dialogue robot program can output the content to the first user based on the intent unit configured in FIG. 11A to FIG. Departing from the airport?".
  • Fig. 12A shows a further constructed intent unit for the third round of the dialogue example shown in Fig. 9; 12C shows the configuration of the output node corresponding to the parameter logic 1 and the configuration of the output node corresponding to the parameter logic 2 of the build intent unit shown in 12A.
  • the dialogue content of the second user in the third round of dialogue of the man-machine multi-round dialogue example shown in FIG. 9 is "Capital International Airport".
  • the first user may construct the intent unit shown in FIG. 12A based on the dialogue content "capital international airport" of the second user.
  • the portion of the intent unit newly constructed in FIG. 12A compared to FIG. 11A may correspond to the portion in the block in FIG. 12A .
  • the input node is configured to perform the task "Departure Airport”.
  • the second user can configure the configuration item "trigger question method” of the input node to include “capital international airport” and "I want to go to the capital international airport”, and configure the configuration item "similar question method” of the input node to include "I The departure airport is the Capital International Airport”.
  • the second user can also configure the slot "Beijing Airport”.
  • the information of the slot may be Capital International Airport.
  • the jumping question method is triggered, and jumps to the previous input node corresponding to the flight booking or related to the departure city input node.
  • the first user can click OK to keep the corresponding configuration.
  • the decision node may be configured to perform the task "departure airport decision".
  • the second user may configure the parameter logic to include parameter logic 1 and parameter logic 2, wherein parameter logic 1 is configured to indicate a "departure is empty” situation or a "Beijing airport does not belong to the Beijing airport dictionary” situation.
  • Parameter logic 2 is configured to indicate the case of "Beijing airport belongs to Beijing airport dictionary".
  • the Beijing airport dictionary may record information on airports in Beijing.
  • the intent unit may be configured to include two output nodes (ie, an output node corresponding to parameter logic 1 and an output node corresponding to parameter logic 2).
  • the output node corresponding to parameter logic 1 may be configured to perform the task "parameter logic 1 output".
  • the output node corresponding to parameter logic 1 may be configured to output "Please confirm your departure airport and tell me again" to the second user.
  • the reply content may be output in one or more of the output forms shown in Figure 12C.
  • the output node corresponding to parameter logic 2 may be configured to perform the task "parameter logic 2 output”.
  • the output node corresponding to parameter logic 2 may be configured to output "What is your destination?" to the second user.
  • the dialogue robot program can output the content “May I ask your What is the destination?”.
  • Fig. 13A shows a further constructed intent unit for the fourth round of the dialogue example shown in Fig. 9; 13C shows the configuration of the output node corresponding to the parameter logic 1 and the configuration of the output node corresponding to the parameter logic 2 of the build intent unit shown in 13A.
  • the dialogue content of the second user in the fourth round of dialogue in the example of the man-machine multi-round dialogue shown in FIG. 9 is "Hangzhou".
  • the first user may construct the intent unit shown in FIG. 13A based on the dialogue content "Hangzhou" of the second user.
  • the portion of the newly constructed intent unit of FIG. 13A compared to FIG. 12A may correspond to the portion in the block in FIG. 13A .
  • the input node is configured to perform the task "Destination City".
  • the second user can configure the configuration item "trigger question method” of the input node to include “Hangzhou” and “I want to go to Hangzhou”, and configure the configuration item "similar question method” of the input node to include "my destination is Hangzhou”.
  • the second user can also configure the slot "destination”.
  • the information of the slot may be Hangzhou.
  • the content of the dialogue of the second user is the content related to the flight booking, the content related to the departure city or the content related to the departure airport, the jumping question method is triggered, and jumps to the previous corresponding to the flight booking.
  • the first user can click OK to keep the corresponding configuration.
  • the decision node may be configured to perform the task "Destination City Decision".
  • the second user may configure the parameter logic to include parameter logic 1 and parameter logic 2, where parameter logic 1 is configured to indicate a "destination is empty” condition or a "destination does not belong to the destination dictionary” condition.
  • Parameter logic 2 is configured to indicate the "destination belongs to the destination dictionary" case.
  • the destination dictionary may record information on the destination.
  • the intent unit may be configured to include two output nodes (ie, an output node corresponding to parameter logic 1 and an output node corresponding to parameter logic 2).
  • the output node corresponding to parameter logic 1 may be configured to perform the task "parameter logic 1 output".
  • the output node corresponding to parameter logic 1 may be configured to output "Please confirm your destination and tell me again" to the second user.
  • the reply content may be output using one or more of the output forms shown in Figure 13C.
  • the output node corresponding to parameter logic 2 may be configured to perform the task "parameter logic 2 output”.
  • the output node corresponding to parameter logic 2 may be configured to output "Which airport in Hangzhou are you going to?” to the second user.
  • FIG. 14A shows a further constructed intent unit for the fifth round of dialogue and sixth round of the example of the man-machine multi-round dialogue shown in Fig. 9;
  • FIG. 14C shows the configuration of the output node corresponding to the parameter logic 1 based on the fifth round of dialogue with the construction intent unit shown in 14A, and the parameter The configuration of the output node corresponding to logic 2.
  • the dialogue content of the second user in the fifth round of dialogue in the example of the multi-round dialogue between humans and machines shown in FIG. 9 is "I remembered it wrongly, instead of going to Hangzhou, I will go to Shanghai instead”.
  • the first user may construct the intent unit shown in FIG. 14A based on the dialogue content of the second user, "I remembered wrong, I will not go to Hangzhou, but go to Shanghai instead.”
  • the intent node is reset, and processing proceeds to the input node in FIG. 14B that is connected to the reset intent.
  • the input node is configured to perform the task "Destination City”.
  • the second user can configure the configuration item "triggering method” of the input node to include “go to Shanghai instead of Hangzhou”, and configure the configuration item "similar method” of the input node to include "my destination is Shanghai” ".
  • the second user can also configure the slot "destination”.
  • the information of the slot may be Shanghai.
  • the content of the dialogue of the second user is the content related to the flight booking, the content related to the departure city or the content related to the departure airport, the jumping question method is triggered, and jumps to the previous corresponding to the flight booking.
  • the first user can click OK to keep the corresponding configuration.
  • the value node after the input node may be configured to perform the task "parameter reset".
  • the first user can reset the parameter to the destination based on the dialogue content of the second user, "I remembered it wrong, I will not go to Hangzhou, but go to Shanghai instead.”
  • the conversation content of the second user it can be determined by selecting which of the intended customers, potential users and invalid users the second user belongs to in the "customer type”. Since the user's classification function can be implemented by configuring the assignment node, more refined services can be provided to the user.
  • Fig. 14D shows the configuration of the sixth-round dialogue-based input nodes and judgment nodes of the construction intent unit shown in 14A
  • Fig. 14E illustrates the sixth-round dialogue-based AND parameter logic 1 of the construction intent unit shown in 14A The configuration of the corresponding output node and the configuration of the output node corresponding to parameter logic 2.
  • the jump query method is triggered, and the jump to The previous input node corresponding to the flight booking, the input node related to the departure city, the input node related to the departure airport, or the input node related to the destination.
  • the first user can click OK to keep the corresponding configuration.
  • the output node corresponding to parameter logic 1 may be configured to perform the task "parameter logic 1 output".
  • the output node corresponding to the parameter logic 1 may be configured to output "Sorry, please select among optional flights, reconfirm your flight” to the second user.
  • the reply content may be output using one or more of the output forms shown in Figure 16C.
  • the output node corresponding to parameter logic 2 may be configured to perform the task "parameter logic 2 output”.
  • the output node corresponding to parameter logic 2 can be configured to output to the second user "Ok, China Southern Airlines AH123456 from Capital International Airport to Shanghai Hongqiao Airport has been booked for you on July 14, 2020, at 10:32 a.m.” .
  • the computer program when executed by one or more computing devices, causes the one or more computing devices to perform the steps of: providing a user configuration interface in which multiple types of intent nodes are provided ; Build an intent unit based on the first user's operations of selecting an intent node, configuring an intent node, and connecting an intent node on the user configuration interface; based on the intent unit, implement multiple rounds of human-machine dialogue with the second user to obtain the first Second, the key intentions of users in multi-round human-machine dialogues to realize the judgment and prediction of dialogues.
  • the computer program in the above-mentioned computer-readable storage medium can be executed in an environment deployed in computer equipment such as a client, a host, an agent device, a server, etc. It should be noted that the computer program, when executed, can also be used to perform steps other than those described above. Additional steps other than those described above are performed or more specific processing is performed when the above steps are performed. The contents of these additional steps and further processing have been mentioned in the description of the related methods and apparatuses with reference to FIG. 1 to FIG. 8 , so to avoid repetitions here No further description will be given.

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Abstract

L'invention concerne un système, un procédé et un dispositif destinés à mettre en œuvre une conversation personne-machine en plusieurs étapes. Le procédé consiste : à présenter une interface de configuration d'utilisateur, une pluralité de types de nœuds d'intention étant présentées dans l'interface de configuration d'utilisateur ; à construire une unité d'intention sur la base d'opérations, consistant à sélectionner les nœuds d'intention, à configurer les nœuds d'intention et à connecter les nœuds d'intention, d'un premier utilisateur sur l'interface de configuration d'utilisateur ; et à mettre en œuvre une conversation personne-machine en plusieurs étapes avec un deuxième utilisateur sur la base de l'unité d'intention, afin d'acquérir une intention clé du deuxième utilisateur dans la conversation personne-machine en plusieurs étapes et de parvenir à la détermination et à la prédiction de la conversation.
PCT/CN2021/074352 2020-08-20 2021-01-29 Système, procédé et dispositif destinés à mettre en œuvre une conversation personne-machine en plusieurs étapes WO2022037019A1 (fr)

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CN115793914A (zh) * 2023-02-08 2023-03-14 广州市玄武无线科技股份有限公司 多轮场景交互流程图生成方法、电子设备及其存储介质

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