CN112100338B - Dialog theme extension method, device and system for intelligent robot - Google Patents
Dialog theme extension method, device and system for intelligent robot Download PDFInfo
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Abstract
The invention belongs to the technical field of computers, and provides a method, a device and a system for expanding a conversation theme of an intelligent robot. The method comprises the following steps: presetting a theme expansion library, wherein an expansion theme and a corpus corresponding to the expansion theme are stored in the theme expansion library; setting a plurality of nodes for carrying out conversation with a user, and generating a theme conversation strategy of the intelligent robot comprising the nodes; and the intelligent robot carries out conversation with the user according to the theme conversation strategy, monitors the input of the user in real time, and calls the corpus corresponding to the expansion theme to carry out conversation with the user when the input of the user triggers the expansion theme in the theme expansion library. By adopting the technical scheme, the theme extension library is arranged, so that the theme in conversation with the user can be fully extended, the existing rigid one-question one-answer conversation mode is avoided, the intelligent robot and the user conversation are more humanized, and the user experience is improved.
Description
Technical Field
The invention relates to the field of computer information processing, in particular to a method, a device and a system for expanding a conversation theme of an intelligent robot.
Background
The customer service center is a main bridge for communication between enterprises and users, and a main channel for improving the satisfaction degree of the users. In the past, a customer service center mainly takes manual customer service as a main part and professional customer service personnel serve users.
With the development of computer information processing technology, more and more customer service centers begin to adopt intelligent robots to serve users, and the problem of overlong waiting time of manual customer service is solved.
Although the intelligent robot is very close to real customer service in voice tone, the intelligent robot usually has a question-and-answer mode in the process of conversation with a user at present. The intelligent robot asks questions and then the user answers the questions, or the user asks questions and then the intelligent robot answers the questions, so that the user feels stiff and experiences poor experience.
Disclosure of Invention
The invention aims to solve the problems that the existing intelligent robot only has a question-answer mode in the conversation process, so that the feeling of a user is hard and the user experience is not good.
In order to solve the above technical problem, a first aspect of the present invention provides a method for extending a dialog theme of an intelligent robot, including:
presetting a theme expansion library, wherein an expansion theme and a corpus corresponding to the expansion theme are stored in the theme expansion library;
setting a plurality of nodes for carrying out conversation with a user, and generating a theme conversation strategy of the intelligent robot comprising the nodes;
and the intelligent robot carries out conversation with the user according to the theme conversation strategy, monitors the input of the user in real time, and calls the corpus corresponding to the expansion theme to carry out conversation with the user when the input of the user triggers the expansion theme in the theme expansion library.
According to a preferred embodiment of the present invention, the corpus corresponding to the extension topic is a guided dialog corpus.
According to a preferred embodiment of the present invention, a plurality of nodes for performing a dialog with a user are provided, and the generating of the theme dialog strategy of the intelligent robot including the plurality of nodes further comprises:
setting a theme description of the theme dialogue;
setting node corpora of a plurality of nodes which have conversation with a user, and calculating the importance relation between the node corpora of the plurality of nodes and the theme description;
and sequencing the nodes according to the importance relation to generate the topic conversation strategy.
According to a preferred embodiment of the present invention, calculating the importance relationship between the node corpus of the plurality of nodes and the topic specification specifically includes:
and inputting the node linguistic data of the nodes and the theme description into an importance judgment model, and outputting an importance reference value by the importance judgment model.
According to a preferred embodiment of the present invention, the intelligent robot invoking the corpus corresponding to the extension topic to have a conversation with the user further includes:
and the intelligent robot returns the conversation strategy after completing the conversation of the extension theme.
According to a preferred embodiment of the present invention, the returning the dialog policy after the intelligent robot completes the dialog of the extension topic further includes:
and deleting the called expansion theme from the theme expansion library.
The second aspect of the present invention provides a dialog theme extension apparatus for an intelligent robot, the apparatus comprising:
the theme extension library setting module is used for presetting a theme extension library, and the theme extension library stores an extension theme and a corpus corresponding to the extension theme;
the system comprises a conversation strategy generation module, a conversation strategy generation module and a conversation strategy generation module, wherein the conversation strategy generation module is used for setting a plurality of nodes for carrying out conversation with a user and generating a theme conversation strategy of the intelligent robot comprising the nodes;
and the intelligent robot carries out conversation with the user according to the theme conversation strategy, monitors the input of the user in real time, and calls the corpus corresponding to the expansion theme to carry out conversation with the user when the input of the user triggers the expansion theme in the theme expansion library.
According to a preferred embodiment of the present invention, the corpus corresponding to the extension topic is a guided dialog corpus.
According to a preferred embodiment of the present invention, a plurality of nodes for performing a dialog with a user are provided, and the generating of the theme dialog strategy of the intelligent robot including the plurality of nodes further comprises:
setting a theme description of the theme dialogue;
setting node corpora of a plurality of nodes which have conversation with a user, and calculating the importance relation between the node corpora of the plurality of nodes and the theme description;
and sequencing the nodes according to the importance relation to generate the topic conversation strategy.
According to a preferred embodiment of the present invention, calculating the importance relationship between the node corpus of the plurality of nodes and the topic specification specifically includes:
and inputting the node linguistic data of the nodes and the theme description into an importance judgment model, and outputting an importance reference value by the importance judgment model.
According to a preferred embodiment of the present invention, the intelligent robot invoking the corpus corresponding to the extension topic to have a conversation with the user further includes:
and the intelligent robot returns the conversation strategy after completing the conversation of the extension theme.
According to a preferred embodiment of the present invention, the returning the dialog policy after the intelligent robot completes the dialog of the extension topic further includes:
and deleting the called expansion theme from the theme expansion library.
The third aspect of the present invention provides a dialog theme extension system for an intelligent robot, including:
a storage unit for storing a computer executable program;
and the processing unit is used for reading the computer executable program in the storage unit so as to execute the conversation theme extension method of the intelligent robot.
A fourth aspect of the present invention provides a computer-readable medium storing a computer-readable program, wherein the computer-readable program is configured to execute the method for extending a dialog theme of an intelligent robot.
By adopting the technical scheme, the theme extension library is arranged, so that the theme in conversation with the user can be fully extended, the existing rigid one-question one-answer conversation mode is avoided, the intelligent robot and the user conversation are more humanized, and the user experience is improved.
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In order to make the technical problems solved by the present invention, the technical means adopted and the technical effects obtained more clear, the following will describe in detail the embodiments of the present invention with reference to the accompanying drawings. It should be noted, however, that the drawings described below are only illustrations of exemplary embodiments of the invention, from which other embodiments can be derived by those skilled in the art without inventive step.
FIG. 1 is a flow chart of a dialog topic expansion method of an intelligent robot in an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a dialog theme extension apparatus of an intelligent robot in an embodiment of the present invention;
FIG. 3 is a schematic structural framework diagram of the dialog topic extension system of the intelligent robot in the embodiment of the invention;
fig. 4 is a schematic structural diagram of a computer-readable storage medium in an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the invention may be embodied in many specific forms, and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art.
The structures, properties, effects or other characteristics described in a certain embodiment may be combined in any suitable manner in one or more other embodiments, while still complying with the technical idea of the invention.
In describing particular embodiments, specific details of structures, properties, effects, or other features are set forth in order to provide a thorough understanding of the embodiments by one skilled in the art. However, it is not excluded that a person skilled in the art may implement the invention in a specific case without the above-described structures, performances, effects or other features.
The flow chart in the drawings is only an exemplary flow demonstration, and does not represent that all the contents, operations and steps in the flow chart are necessarily included in the scheme of the invention, nor does it represent that the execution is necessarily performed in the order shown in the drawings. For example, some operations/steps in the flowcharts may be divided, some operations/steps may be combined or partially combined, and the like, and the execution order shown in the flowcharts may be changed according to actual situations without departing from the gist of the present invention.
The block diagrams in the figures generally represent functional entities and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and/or processing unit devices and/or microcontroller devices.
The same reference numerals denote the same or similar elements, components, or parts throughout the drawings, and thus, a repetitive description thereof may be omitted hereinafter. It will be further understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these elements, components, or sections should not be limited by these terms. That is, these phrases are used only to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention. Furthermore, the term "and/or", "and/or" is intended to include all combinations of any one or more of the listed items.
Fig. 1 is a schematic flow chart of a dialog theme extension method of an intelligent robot according to the present invention, and as shown in fig. 1, the method of the present invention has the following steps:
s101, presetting a theme expansion library, wherein an expansion theme and a corpus corresponding to the expansion theme are stored in the theme expansion library.
On the basis of the technical scheme, furthermore, the corpus corresponding to the extension theme is a guided dialog corpus.
In this embodiment, a topic extension library is provided, and topics stored in the topic extension library are extension topics that are often involved in a conversation and corpora corresponding to the extension topics. The extension theme is a general theme which is often involved in the usual conversation process, such as identity card uploading, weather discussion, movie discussion and the like, and the corpus corresponding to the extension theme is not a question-answer corpus which is commonly used, and a guidance-type conversation corpus is used.
In the embodiment, the customer service center and the user communicate with each other at the beginning, which is real customer service personnel, and a large amount of historical corpora are accumulated. And the topic expansion library classifies the historical linguistic data by performing cluster analysis on the historical linguistic data, and the linguistic data is used for constructing the topic expansion library when the real customer service personnel are selected to perform topic expansion when communicating with the user. The operator can also update the theme extension library regularly, and the latest social, entertainment, science and technology and other contents are added, so that the distance between the operator and the user is convenient to pull.
By setting the theme expansion library, the conversation theme is expanded in the process of communicating with the user, so that the conversation theme is richer and more popular.
S102, setting a plurality of nodes for carrying out conversation with a user, and generating a theme conversation strategy of the intelligent robot comprising the nodes.
On the basis of the technical scheme, further setting a plurality of nodes for carrying out conversation with a user, and generating a theme conversation strategy of the intelligent robot comprising the plurality of nodes further comprises:
setting a theme description of the theme dialogue;
setting node corpora of a plurality of nodes which have conversation with a user, and calculating the importance relation between the node corpora of the plurality of nodes and the theme description;
and sequencing the nodes according to the importance relation to generate the topic conversation strategy.
In the present embodiment, a conversation policy is constructed, and the purpose of the present conversation is first determined, and a conversation topic is determined according to the purpose, and a simple text description is performed on the conversation topic. For example, if the purpose is to promote a notebook to the user, the topic of the conversation is to promote a product, and the topic description states "promote XX brand notebook to the user, currently there is a lower price for the activity than other sales platforms, etc.
The conversation theme and the theme description in the application can be manually input by an operator, or can be selected from a preset conversation theme library by the operator and edited and modified.
In this embodiment, a specific dialog node is also required to be set in the dialog policy, the dialog node is a more specific dialog content, and the dialog node corpus is a text content used in the dialog. For example, in a conversation strategy with a conversation subject of promotion, four conversation nodes are set, N1 is product introduction, N2 is product hardware, N3 is product software, N4 is product price, the conversation node corpus of N1 is "dimension XXX, total amount XXX, duration XXX", the conversation node corpus of N2 is "processor XXX, memory XXX, hard disk is fixed hard disk with XXX capacity", the conversation node corpus of N3 is "software pre-installed windows 10 and OFFICE", the conversation node corpus of N4 is "promotion activity, and price is lower than that of other sales platforms".
The conversation nodes and the conversation node linguistic data in the application can be manually input by an operator, and can also be selected by the operator from a preset conversation node library and edited and modified.
On the basis of the above technical solution, further, calculating the importance relationship between the node corpus of the plurality of nodes and the topic specification specifically includes:
and inputting the node linguistic data of the nodes and the theme description into an importance judgment model, and outputting an importance reference value by the importance judgment model.
In the prior art, in order to ensure the conversation effect, the node sequence in the conversation strategy is set by experienced operators, but after all, the experienced operators have high training cost and limited quantity, and the client service center needs to set a plurality of conversation strategies, so that the requirements are difficult to meet. Therefore, in the present embodiment, in order to determine the order of each node in the conversation policy, it is necessary to determine the importance degree of each conversation node and the conversation topic.
In the present embodiment, the importance degree of each conversation node and the conversation topic is determined by the importance judgment model. The importance judgment model comprises a coding layer and a matching layer, wherein the coding layer is used for converting the dialogue node linguistic data and the theme description into sentence vectors, and the matching layer is used for calculating the importance degree of the dialogue node linguistic data sentence vectors and the theme description sentence vectors. The coding layer adopts a bidirectional long-short term memory network, and the matching layer adopts a cosine algorithm.
In this embodiment, since the number of the dialog nodes is set to 4, the number of the input interfaces of the coding layer is 5, the first one is a topic description related to the input dialog topic, and the following four inputs dialog corpora corresponding to the 4 dialog nodes. Through the operation of the bidirectional long-term and short-term memory network model, the coding layer outputs 5 corresponding sentence vectors.
And calculating the importance degree of the dialog corpus of the 4 nodes and the topic description of the dialog topic by a cosine algorithm at the matching layer, wherein the importance reference value of N1 is 0.65, the importance reference value of N2 is 0.33, the importance reference value of N3 is 0.21, and the importance reference value of N4 is 0.57.
The importance reference for N1 is greatest due to the computation through the matching layers, followed by N4, N2, and N3. Thus, the order of the conversation nodes in the conversation strategy is N1 → N4 → N2 → N3, i.e., introduction of the product, then the promotional program, the price of the product, then the hardware and software.
S103, the intelligent robot carries out conversation with the user according to the theme conversation strategy, the input of the user is monitored in real time, and when the input of the user triggers an expansion theme in the theme expansion library, the intelligent robot calls the corpus corresponding to the expansion theme to carry out conversation with the user.
In this embodiment, the intelligent robot communicates with the user, and the theme strategy of the conversation is to promote the XX brand notebook to the user.
The user may be required to upload the identification card during the purchase process, and the user mentions that the identification card always fails to be uploaded. Through real-time monitoring, the 'identity card uploading failure' input by the user triggers an 'identity card uploading' extended theme in the theme extended library. At this time, the intelligent robot stops the theme strategy of ' marketing XX brand notebook to the user ', calls an extended theme ' identity card uploading ' from the theme extension library to have a conversation with the user, ' father, you try again, and the identity card is placed in an environment with sufficient light to take a picture … … with the mobile phone.
It is also possible that the user sees a blue-sky white cloud of wallpaper for product display, the exclamation picture weather is really good, and at this time, the 'discussion weather' extension theme in the theme extension library is triggered. The intelligent robot stops the theme strategy of 'marketing XX brand notebook to the user', calls the expansion theme 'discuss weather' from the theme expansion library to have a conversation with the user, 'feel how the weather is today, and do not go out and go away … …'.
It is also possible that the user exclamates the use of a notebook for movies when the audiovisual capabilities of the notebook are powerful for the user. At this point, the "discuss movie" extension theme in the theme extension library is triggered. The intelligent robot stops the theme strategy of 'marketing XX brand notebook to the user', calls the expansion theme 'discuss movie' from the theme expansion library to have a conversation with the user, 'recently there is a new showing movie public praise, and you see how … …'.
Through the expansion themes, the problems frequently encountered by user groups are solved on one hand, and on the other hand, the distance between the user groups and the user is shortened like the family pulling in real person conversation, so that the use experience of the user is improved.
On the basis of the technical scheme, further, the intelligent robot calls the corpus corresponding to the extension theme to have a conversation with the user further comprises:
and the intelligent robot returns the conversation strategy after completing the conversation of the extension theme.
In the embodiment, after the intelligent robot and the user complete the theme extension conversation, the original theme strategy is returned, and the original theme strategy is continuously executed.
On the basis of the above technical solution, further, returning the conversation policy after the intelligent robot completes the conversation of the extension topic further includes:
and deleting the called expansion theme from the theme expansion library.
In the embodiment, in order to avoid that individual users prefer chatting, the input of the user may frequently trigger the expansion of the same theme in the theme base, which leads to a problem of verbose feeling brought to the user by frequently calling the same or similar linguistic data. If the expansion theme in the expansion theme library is called once, the expansion theme is deleted from the expansion theme library, and the problem that the user experience is not good due to repeated calling is solved.
Fig. 2 is a schematic structural diagram of a dialog theme extension apparatus of an intelligent robot according to an embodiment of the present invention, and as shown in fig. 2, the present invention provides a dialog theme extension apparatus 200 of an intelligent robot, where the apparatus 200 includes:
the theme extension library setting module 201 is configured to preset a theme extension library, where an extension theme and a corpus corresponding to the extension theme are stored in the theme extension library.
On the basis of the technical scheme, furthermore, the corpus corresponding to the extension theme is a guided dialog corpus.
In this embodiment, a topic extension library is provided, and topics stored in the topic extension library are extension topics that are often involved in a conversation and corpora corresponding to the extension topics. The extension theme is a general theme which is often involved in the usual conversation process, such as identity card uploading, weather discussion, movie discussion and the like, and the corpus corresponding to the extension theme is not a question-answer corpus which is commonly used, and a guidance-type conversation corpus is used.
In the embodiment, the customer service center and the user communicate with each other at the beginning, which is real customer service personnel, and a large amount of historical corpora are accumulated. And the topic expansion library classifies the historical linguistic data by performing cluster analysis on the historical linguistic data, and the linguistic data is used for constructing the topic expansion library when the real customer service personnel are selected to perform topic expansion when communicating with the user. The operator can also update the theme extension library regularly, and the latest social, entertainment, science and technology and other contents are added, so that the distance between the operator and the user is convenient to pull.
By setting the theme expansion library, the conversation theme is expanded in the process of communicating with the user, so that the conversation theme is richer and more popular.
The conversation strategy generating module 202 is configured to set a plurality of nodes for conversation with a user, and generate a topic conversation strategy of the intelligent robot including the plurality of nodes.
On the basis of the technical scheme, further setting a plurality of nodes for carrying out conversation with a user, and generating a theme conversation strategy of the intelligent robot comprising the plurality of nodes further comprises:
setting a theme description of the theme dialogue;
setting node corpora of a plurality of nodes which have conversation with a user, and calculating the importance relation between the node corpora of the plurality of nodes and the theme description;
and sequencing the nodes according to the importance relation to generate the topic conversation strategy.
In the present embodiment, a conversation policy is constructed, and the purpose of the present conversation is first determined, and a conversation topic is determined according to the purpose, and a simple text description is performed on the conversation topic. For example, if the purpose is to promote a notebook to the user, the topic of the conversation is to promote a product, and the topic description states "promote XX brand notebook to the user, currently there is a lower price for the activity than other sales platforms, etc.
The conversation theme and the theme description in the application can be manually input by an operator, or can be selected from a preset conversation theme library by the operator and edited and modified.
In this embodiment, a specific dialog node is also required to be set in the dialog policy, the dialog node is a more specific dialog content, and the dialog node corpus is a text content used in the dialog. For example, in a conversation strategy with a conversation subject of promotion, four conversation nodes are set, N1 is product introduction, N2 is product hardware, N3 is product software, N4 is product price, the conversation node corpus of N1 is "dimension XXX, total amount XXX, duration XXX", the conversation node corpus of N2 is "processor XXX, memory XXX, hard disk is fixed hard disk with XXX capacity", the conversation node corpus of N3 is "software pre-installed windows 10 and OFFICE", the conversation node corpus of N4 is "promotion activity, and price is lower than that of other sales platforms".
The conversation nodes and the conversation node linguistic data in the application can be manually input by an operator, and can also be selected by the operator from a preset conversation node library and edited and modified.
On the basis of the above technical solution, further, calculating the importance relationship between the node corpus of the plurality of nodes and the topic specification specifically includes:
and inputting the node linguistic data of the nodes and the theme description into an importance judgment model, and outputting an importance reference value by the importance judgment model.
In the prior art, in order to ensure the conversation effect, the node sequence in the conversation strategy is set by experienced operators, but after all, the experienced operators have high training cost and limited quantity, and the client service center needs to set a plurality of conversation strategies, so that the requirements are difficult to meet. Therefore, in the present embodiment, in order to determine the order of each node in the conversation policy, it is necessary to determine the importance degree of each conversation node and the conversation topic.
In the present embodiment, the importance degree of each conversation node and the conversation topic is determined by the importance judgment model. The importance judgment model comprises a coding layer and a matching layer, wherein the coding layer is used for converting the dialogue node linguistic data and the theme description into sentence vectors, and the matching layer is used for calculating the importance degree of the dialogue node linguistic data sentence vectors and the theme description sentence vectors. The coding layer adopts a bidirectional long-short term memory network, and the matching layer adopts a cosine algorithm.
In this embodiment, since the number of the dialog nodes is set to 4, the number of the input interfaces of the coding layer is 5, the first one is a topic description related to the input dialog topic, and the following four inputs dialog corpora corresponding to the 4 dialog nodes. Through the operation of the bidirectional long-term and short-term memory network model, the coding layer outputs 5 corresponding sentence vectors.
And calculating the importance degree of the dialog corpus of the 4 nodes and the topic description of the dialog topic by a cosine algorithm at the matching layer, wherein the importance reference value of N1 is 0.65, the importance reference value of N2 is 0.33, the importance reference value of N3 is 0.21, and the importance reference value of N4 is 0.57.
The importance reference for N1 is greatest due to the computation through the matching layers, followed by N4, N2, and N3. Thus, the order of the conversation nodes in the conversation strategy is N1 → N4 → N2 → N3, i.e., introduction of the product, then the promotional program, the price of the product, then the hardware and software.
And the theme extension library calling module 203 is used for carrying out conversation with the user by the intelligent robot according to the theme conversation strategy, monitoring the input of the user in real time, and calling the corpus corresponding to the extension theme to carry out conversation with the user when the input of the user triggers the extension theme in the theme extension library.
In this embodiment, the intelligent robot communicates with the user, and the theme strategy of the conversation is to promote the XX brand notebook to the user.
The user may be required to upload the identification card during the purchase process, and the user mentions that the identification card always fails to be uploaded. Through real-time monitoring, the 'identity card uploading failure' input by the user triggers an 'identity card uploading' extended theme in the theme extended library. At this time, the intelligent robot stops the theme strategy of ' marketing XX brand notebook to the user ', calls an extended theme ' identity card uploading ' from the theme extension library to have a conversation with the user, ' father, you try again, and the identity card is placed in an environment with sufficient light to take a picture … … with the mobile phone.
It is also possible that the user sees a blue-sky white cloud of wallpaper for product display, the exclamation picture weather is really good, and at this time, the 'discussion weather' extension theme in the theme extension library is triggered. The intelligent robot stops the theme strategy of 'marketing XX brand notebook to the user', calls the expansion theme 'discuss weather' from the theme expansion library to have a conversation with the user, 'feel how the weather is today, and do not go out and go away … …'.
It is also possible that the user exclamates the use of a notebook for movies when the audiovisual capabilities of the notebook are powerful for the user. At this point, the "discuss movie" extension theme in the theme extension library is triggered. The intelligent robot stops the theme strategy of 'marketing XX brand notebook to the user', calls the expansion theme 'discuss movie' from the theme expansion library to have a conversation with the user, 'recently there is a new showing movie public praise, and you see how … …'.
Through the expansion themes, the problems frequently encountered by user groups are solved on one hand, and on the other hand, the distance between the user groups and the user is shortened like the family pulling in real person conversation, so that the use experience of the user is improved.
On the basis of the technical scheme, further, the intelligent robot calls the corpus corresponding to the extension theme to have a conversation with the user further comprises:
and the intelligent robot returns the conversation strategy after completing the conversation of the extension theme.
In the embodiment, after the intelligent robot and the user complete the theme extension conversation, the original theme strategy is returned, and the original theme strategy is continuously executed.
On the basis of the above technical solution, further, returning the conversation policy after the intelligent robot completes the conversation of the extension topic further includes:
and deleting the called expansion theme from the theme expansion library.
In the embodiment, in order to avoid that individual users prefer chatting, the input of the user may frequently trigger the expansion of the same theme in the theme base, which leads to a problem of verbose feeling brought to the user by frequently calling the same or similar linguistic data. If the expansion theme in the expansion theme library is called once, the expansion theme is deleted from the expansion theme library, and the problem that the user experience is not good due to repeated calling is solved.
As shown in fig. 3, in an embodiment of the present invention, a dialog theme extension system for an intelligent robot is further disclosed, the dialog policy is applicable to a specific task-based application scenario, and the dialog theme extension system for an intelligent robot shown in fig. 3 is only an example and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.
The dialog theme extension system 300 of the intelligent robot includes a storage unit 320 for storing a computer executable program; a processing unit 310 for reading the computer executable program in the storage unit to execute the steps of various embodiments of the present invention.
The dialog theme extension system 300 of the intelligent robot in this embodiment further includes a bus 330 connecting different system components (including the storage unit 320 and the processing unit 310), a display unit 340, and the like.
The storage unit 320 stores a computer readable program, which may be a code of a source program or a read-only program. The program may be executed by the processing unit 310 such that the processing unit 310 performs the steps of various embodiments of the present invention. For example, the processing unit 310 may perform the steps as shown in fig. 1.
The storage unit 320 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM) 3201 and/or a cache storage unit 3202, and may further include a read only memory unit (ROM) 3203. The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The intelligent robotic conversation topic extension system 300 can also communicate with one or more external devices 370 (e.g., keyboard, display, network device, Bluetooth device, etc.) such that a user can interact with the processing unit 310 via these external devices 370 via an input/output (I/O) interface 350, and can also interact with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via a network adapter 360. The network adapter 360 may communicate with the other modules of the intelligent robot's conversation topic extension system 300 via the bus 330. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in the intelligent robot's conversation topic extension system 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
FIG. 4 is a schematic diagram of one computer-readable medium embodiment of the present invention. As shown in fig. 4, the computer program may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory unit (RAM), a read-only memory unit (ROM), an erasable programmable read-only memory unit (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory unit (CD-ROM), an optical storage unit, a magnetic storage unit, or any suitable combination of the foregoing. The computer program, when executed by one or more data processing devices, enables the computer-readable medium to implement the above-described method of the invention, namely:
s101, presetting a theme expansion library, wherein an expansion theme and a corpus corresponding to the expansion theme are stored in the theme expansion library;
s102, setting a plurality of nodes for carrying out conversation with a user, and generating a theme conversation strategy of the intelligent robot comprising the nodes;
s103, the intelligent robot carries out conversation with the user according to the theme conversation strategy, the input of the user is monitored in real time, and when the input of the user triggers an expansion theme in the theme expansion library, the intelligent robot calls the corpus corresponding to the expansion theme to carry out conversation with the user.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a data processing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the present invention can be implemented as a method, an apparatus, an electronic device, or a computer-readable medium executing a computer program. Some or all of the functions of the present invention may be implemented in practice using general purpose data processing equipment such as a micro-processing unit or a digital signal processing unit (DSP).
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
Claims (7)
1. A conversation theme extension method of an intelligent robot is characterized by comprising the following steps:
presetting a theme expansion library, wherein an expansion theme and a corpus corresponding to the expansion theme are stored in the theme expansion library;
setting a plurality of nodes for carrying out conversation with a user, and generating a theme conversation strategy of the intelligent robot comprising the nodes, wherein the theme conversation strategy specifically comprises setting a theme description of theme conversation; setting node corpora of a plurality of nodes which have a conversation with a user, and inputting the node corpora of the plurality of nodes and the theme description into an importance judgment model, wherein the importance judgment model outputs an importance reference value, and the importance reference value represents the importance relationship between the node corpora of the plurality of nodes and the theme description; sequencing the nodes according to the importance relation to generate the topic conversation strategy; the importance judgment model comprises a coding layer and a matching layer, wherein the coding layer is used for converting the dialogue node corpus and the topic description into sentence vectors, and the matching layer is used for calculating importance reference values of the dialogue node corpus sentence vectors and the topic description sentence vectors; the coding layer adopts a bidirectional long-short term memory network, and the matching layer adopts a cosine algorithm;
and the intelligent robot carries out conversation with the user according to the theme conversation strategy, monitors the input of the user in real time, and calls the corpus corresponding to the expansion theme to carry out conversation with the user when the input of the user triggers the expansion theme in the theme expansion library.
2. The conversation topic expansion method of claim 1 wherein the corpus corresponding to the expansion topic is a guided conversation corpus.
3. The conversation theme extension method according to claim 1, wherein the intelligent robot calls the corpus corresponding to the extension theme to have a conversation with the user further comprises:
and the intelligent robot returns the conversation strategy after completing the conversation of the extension theme.
4. The conversation topic extension method of claim 3 wherein returning to the conversation strategy after completion of the conversation for the extension topic by the intelligent robot further comprises:
and deleting the called expansion theme from the theme expansion library.
5. A dialog theme extension device of an intelligent robot is characterized by comprising:
the theme extension library setting module is used for presetting a theme extension library, and the theme extension library stores an extension theme and a corpus corresponding to the extension theme;
the system comprises a conversation strategy generation module, a conversation strategy generation module and a conversation strategy generation module, wherein the conversation strategy generation module is used for setting a plurality of nodes for carrying out conversation with a user and generating a theme conversation strategy of the intelligent robot comprising the nodes, and the conversation strategy generation module specifically comprises the step of setting a theme description of theme conversation; setting node corpora of a plurality of nodes which have a conversation with a user, and inputting the node corpora of the plurality of nodes and the theme description into an importance judgment model, wherein the importance judgment model outputs an importance reference value, and the importance reference value represents the importance relationship between the node corpora of the plurality of nodes and the theme description; sequencing the nodes according to the importance relation to generate the topic conversation strategy; the importance judgment model comprises a coding layer and a matching layer, wherein the coding layer is used for converting the dialogue node corpus and the topic description into sentence vectors, and the matching layer is used for calculating importance reference values of the dialogue node corpus sentence vectors and the topic description sentence vectors; the coding layer adopts a bidirectional long-short term memory network, and the matching layer adopts a cosine algorithm;
and the intelligent robot carries out conversation with the user according to the theme conversation strategy, monitors the input of the user in real time, and calls the corpus corresponding to the expansion theme to carry out conversation with the user when the input of the user triggers the expansion theme in the theme expansion library.
6. A dialog topic expansion system of an intelligent robot, comprising:
a storage unit for storing a computer executable program;
a processing unit for reading the computer executable program in the storage unit to execute the conversation theme extension method of the intelligent robot of any one of claims 1 to 4.
7. A computer-readable medium storing a computer-readable program for executing the conversation topic extension method for an intelligent robot according to any one of claims 1 to 4.
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| CN106056207A (en) * | 2016-05-09 | 2016-10-26 | 武汉科技大学 | Natural language-based robot deep interacting and reasoning method and device |
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| CN101075435A (en) * | 2007-04-19 | 2007-11-21 | 深圳先进技术研究院 | Intelligent chatting system and its realizing method |
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