WO2018000259A1

WO2018000259A1 - Method and system for generating robot interaction content, and robot

Info

Publication number: WO2018000259A1
Application number: PCT/CN2016/087738
Authority: WO
Inventors: 王昊奋; 邱楠; 杨新宇
Original assignee: 深圳狗尾草智能科技有限公司
Priority date: 2016-06-29
Filing date: 2016-06-29
Publication date: 2018-01-04
Also published as: CN106537294A

Abstract

A method for generating robot interaction content, comprising: obtaining expression information of a user (S101); obtaining text emotion information of the user (S102); determining a user intention according to the expression information and the text emotion information (S103); and generating robot interaction content by combining the expression information, the text emotion information, the user intention, and a current robot life timeline (300) (S104). In the method, the life timeline of a robot is added to generation of the robot interaction content, such that the robot is more humanized when interacting with human and has a human lifestyle within the life timeline. By the method, the humanization of robot interaction content generation, the human-robot interaction experience, and the intelligence can be improved.

Description

Method, system and robot for generating robot interactive content

Technical field

The invention relates to the field of robot interaction technology, and in particular to a method, a system and a robot for generating robot interactive content.

Background technique

Usually, an expression is made in the process of human interaction. Generally, after the eye sees or the ear hears the sound, after the brain analyzes, a reasonable expression feedback is performed. In the process of interacting with the person, the language interacted by the other party is used to analyze the emotion. Feedback changes in sentiment analysis can affect feedback from human expressions. For the robot, at present, the robot wants to make the expression feedback, mainly through the pre-designed method and the deep learning training corpus. The expression feedback through the preset program and the corpus training has the following shortcomings, the expression The output depends on the human text representation, that is, similar to a question-and-answer machine, different words of the user trigger different expressions. In this case, the robot actually outputs the expression according to the human pre-designed interaction mode, which causes the robot to fail. More anthropomorphic, can not be like humans, life scenes at different time points, showing different expressions, that is, the way the robot interactive content is generated is completely passive, so the generation of expression requires a lot of human-computer interaction, resulting in the robot's The intelligence is very poor.

Therefore, how to make the robot itself have a human lifestyle in the time axis and improve the anthropomorphicity of the robot interactive content generation has become an urgent technical problem.

Summary of the invention

The object of the present invention is to provide a method, a system and a robot for generating interactive content of a robot, so that the robot itself has a human lifestyle in the time axis of life, can enhance the anthropomorphicity of the robot interactive content generation, enhance the human-computer interaction experience, and improve Intelligence.

The object of the present invention is achieved by the following technical solutions:

A method for generating robot interactive content, comprising:

Obtaining the user's expression information;

Obtaining the user's text emotional information;

Determining the user's intention based on the expression information and the textual emotion information;

Combining the current machine with the expression information, textual sentiment information, and the user's intention The human life timeline generates robot interaction content.

Preferably, the expression information is collected by video information.

Preferably, the text sentiment information is collected by voice information.

Preferably, the method for generating parameters of the life time axis of the robot includes:

Extend the robot's self-awareness;

Get the parameters of the life timeline;

The self-cognitive parameters of the robot are fitted to the parameters in the life time axis to generate a robot life time axis.

Preferably, the step of expanding the self-cognition of the robot specifically comprises: combining the life scene with the self-knowledge of the robot to form a self-cognitive curve based on the life time axis.

Preferably, the step of fitting the self-cognitive parameter of the robot to the parameter in the life time axis comprises: using a probability algorithm to calculate each parameter of the robot on the life time axis after the time axis scene parameter is changed. The probability of change forms a fitted curve.

Preferably, wherein the life time axis refers to a time axis including 24 hours a day, and the parameters in the life time axis include at least a daily life behavior performed by the user on the life time axis and parameter values representing the behavior.

A system for generating interactive content of a robot, comprising:

An expression visual processing module, configured to acquire expression information of the user;

a text analysis module, configured to obtain text emotional information of the user;

An intention identification module, configured to determine a user intention according to the expression information and the text emotion information;

The content generating module is configured to generate the robot interaction content according to the current robot life time axis according to the expression information, the text emotion information, and the user intention.

Preferably, the expression visual processing module is specifically configured to: collect expression information by using video information.

Preferably, the text analysis module is specifically configured to: collect text emotional information by using voice information.

Preferably, the system comprises an artificial intelligence cloud processing module for:

Extend the robot's self-awareness;

Get the parameters of the life timeline;

Preferably, the artificial intelligence cloud processing module is further configured to: use a life scene and a robot The combination of self-awareness forms a self-recognition curve based on the life time axis.

Preferably, the artificial intelligence cloud processing module is further configured to: use a probability algorithm to calculate a probability of each parameter change of the robot on the life time axis after the time axis scene parameter is changed, to form a fitting curve.

The invention discloses a robot comprising a system for generating interactive content of a robot as described above.

Compared with the prior art, the present invention has the following advantages: in the prior art, the generation method of the expression is generally based on the text emotion and the expression recognition, and the method for generating the robot interaction content in the present invention includes: acquiring the expression information of the user; The user's text emotion information; determining the user's intention according to the expression information and the text emotion information; and generating the robot interaction content according to the current robot life time axis according to the expression information, the text emotion information, and the user intention. In this way, the robot interaction content can be generated according to the user's expression and text emotion combined with the robot life time axis, thereby more accurately and anthropomorphic interaction and communication with the person. For people, everyday life has a certain regularity. In order to make robots communicate with people more anthropomorphic, let the robots sleep, exercise, eat, dance, read books, eat, make up, etc. in 24 hours a day. Sleep and other actions. Therefore, the present invention adds the life time axis in which the robot is located to the interactive content generation of the robot, and makes the robot more humanized when interacting with the human, so that the robot has a human lifestyle in the life time axis, and the method can enhance the robot interaction content. Generate anthropomorphic, enhance the human-computer interaction experience and improve intelligence.

DRAWINGS

1 is a flowchart of a method for generating interactive content of a robot according to Embodiment 1 of the present invention;

2 is a schematic diagram of a system for generating interactive content of a robot according to a second embodiment of the present invention.

detailed description

Although the flowcharts describe various operations as a sequential process, many of the operations can be implemented in parallel, concurrently or concurrently. The order of the operations can be rearranged. Processing may be terminated when its operation is completed, but may also have additional steps not included in the figures. Processing can correspond to methods, functions, procedures, subroutines, subroutines, and the like.

Computer devices include user devices and network devices. The user equipment or the client includes but is not limited to a computer, a smart phone, a PDA, etc.; the network device includes but is not limited to a single network server, a server group composed of multiple network servers, or a cloud computing-based computer or network server. cloud. The computer device can operate alone to carry out the invention, and can also access the network and implement the invention through interoperation with other computer devices in the network. The network in which the computer device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a VPN network, and the like.

The terms "first," "second," and the like may be used herein to describe the various elements, but the elements should not be limited by these terms, and the terms are used only to distinguish one element from another. The term "and/or" used herein includes any and all combinations of one or more of the associated listed items. When a unit is referred to as being "connected" or "coupled" to another unit, it can be directly connected or coupled to the other unit, or an intermediate unit can be present.

The terminology used herein is for the purpose of describing the particular embodiments, The singular forms "a", "an", It is also to be understood that the terms "comprising" and """ Other features, integers, steps, operations, units, components, and/or combinations thereof.

The invention will now be further described with reference to the drawings and preferred embodiments.

Embodiment 1

As shown in FIG. 1 , a method for generating interactive content of a robot is disclosed in this embodiment, including:

S101. Acquire user expression information.

S102. Acquire text emotional information of the user.

S103. Determine a user intention according to the expression information and the text emotion information.

S104. Generate robot interaction content according to the current robot life timeline 300 according to the expression information, the text emotion information, and the user intention.

In the prior art, the expression generation manner is generally based on text emotion and expression recognition, and the method for generating the robot interaction content in the present invention includes: acquiring the user's expression information; acquiring the user's text emotion information; and according to the expression information and the text emotion The information determines a user intent; and generates a robot interaction content in accordance with the current robot life time axis according to the expression information, the text emotion information, and the user intent. In this way, the robot interaction content can be generated according to the user's expression and text emotion combined with the robot life time axis, thereby more accurate, anthropomorphic and human intervention. Line interaction and communication. For people, everyday life has a certain regularity. In order to make robots communicate with people more anthropomorphic, let the robots sleep, exercise, eat, dance, read books, eat, make up, etc. in 24 hours a day. Sleep and other actions. Therefore, the present invention adds the life time axis in which the robot is located to the interactive content generation of the robot, and makes the robot more humanized when interacting with the human, so that the robot has a human lifestyle in the life time axis, and the method can enhance the robot interaction content. Generate anthropomorphic, enhance the human-computer interaction experience and improve intelligence. The interactive content can be an expression or text or voice. The robot life timeline 300 is completed and set in advance. Specifically, the robot life timeline 300 is a series of parameter collections, and this parameter is transmitted to the system to generate interactive content.

In this embodiment, the life time axis is specifically: according to the time axis of human daily life, according to the human way, the self-cognition value of the robot itself in the time axis of daily life is fitted, and the behavior of the robot is according to this The action is to get the robot's own behavior in one day, so that the robot can perform its own behavior based on the life time axis, such as generating interactive content and communicating with humans. If the robot is always awake, it will act according to the behavior on this timeline, and the robot's self-awareness will be changed according to this timeline. The life timeline and variable parameters can be used to change the attributes of self-cognition, such as mood values, fatigue values, etc., and can also automatically add new self-awareness information, such as no previous anger value, based on the life time axis and The scene of the variable factor will automatically add to the self-cognition of the robot based on the scene that previously simulated the human self-cognition.

In this embodiment, the video input captures the user's expression, and the voice input enters the text sentiment analysis engine; the user expression input and the text emotion input enter the artificial intelligence system, the system analyzes the user's intention, and then combines the life time axis of the robot to generate interactive content, for example. Expressions, etc.

For example, the text analysis emotion is unhappy, the expression visual analysis is happy, plus the robot life timeline, such as the current time is 9:00 in the morning, just got up, the robot can tease the owner happy, will reply similar to: you are joking with me Well? The expression system generates a joking expression.

Another example is that the text analysis emotion is unhappy, the expression visual analysis is sad, and the robot life time axis, such as the current time is 11 o'clock at night, the robot analysis owner may be insomnia, will reply similarly: how unhappy, I give You put a song, the expression system generates a sympathetic expression.

According to one of the examples, the expression information is collected by video information. In this way, the expression information can be obtained through the video, and the video acquisition is more accurate, thereby more accurately determining the user's expression and other information.

According to another example, the textual sentiment information is collected by voice information. This way It is convenient and fast to analyze the emotional information of the text through voice input.

According to another example, the method for generating parameters of the robot life time axis includes:

Extend the robot's self-awareness;

Get the parameters of the life timeline;

In this way, the life time axis is added to the self-cognition of the robot itself, so that the robot has an anthropomorphic life. For example, add the cognition of lunch to the robot.

According to another example, the step of expanding the self-cognition of the robot specifically includes: combining the life scene with the self-awareness of the robot to form a self-cognitive curve based on the life time axis. In this way, the life time axis can be specifically added to the parameters of the robot itself.

According to another example, the step of fitting the parameter of the self-cognition of the robot to the parameter in the life time axis comprises: using a probability algorithm to calculate the time of the robot on the life time axis after the time axis scene parameter is changed The probability of each parameter change forms a fitted curve. The probability algorithm may be a Bayesian probability algorithm.

For example, in 24 hours a day, the robot will have sleep, exercise, eat, dance, read books, eat, make up, sleep and other actions. Each action will affect the self-cognition of the robot itself, and combine the parameters on the life time axis with the self-cognition of the robot itself. After fitting, the robot's self-cognition includes, mood, fatigue value, intimacy. , goodness, number of interactions, three-dimensional cognition of the robot, age, height, weight, intimacy, game scene value, game object value, location scene value, location object value, etc. For the robot to identify the location of the scene, such as cafes, bedrooms, etc.

The machine will perform different actions in the time axis of the day, such as sleeping at night, eating at noon, exercising during the day, etc. All the scenes in the life time axis will have an impact on self-awareness. These numerical changes are modeled by the dynamic fit of the probability model, fitting the probability that all of these actions occur on the time axis. Scene Recognition: This type of scene recognition changes the value of the geographic scene in self-cognition.

For example, text analysis emotions are unhappy, user expression analysis is happy, will reply: Are you kidding me? The system generates a joke expression.

Text analysis emotions are unhappy, user expression analysis is sad, will reply: how unhappy, I will give you a song. The system generates a sympathetic expression.

Embodiment 2

As shown in FIG. 2, in this embodiment, a system for generating interactive content of a robot includes:

The expression visual processing module 201 is configured to acquire expression information of the user;

The text analysis module 202 is configured to acquire text emotional information of the user;

The intention identification module 203 is configured to determine a user intention according to the expression information and the text emotion information;

The content generating module 204 is configured to generate the robot interaction content according to the current robot life time axis sent by the robot life timeline module 301 according to the expression information, the text emotion information, and the user intention.

In this way, the robot interaction content can be generated according to the user's expression and text emotion combined with the robot life time axis, thereby more accurately and anthropomorphic interaction and communication with the person. For people, everyday life has a certain regularity. In order to make robots communicate with people more anthropomorphic, let the robots sleep, exercise, eat, dance, read books, eat, make up, etc. in 24 hours a day. Sleep and other actions. Therefore, the present invention adds the life time axis in which the robot is located to the interactive content generation of the robot, and makes the robot more humanized when interacting with the human, so that the robot has a human lifestyle in the life time axis, and the method can enhance the robot interaction content. Generate anthropomorphic, enhance the human-computer interaction experience and improve intelligence.

According to one example, the expression visual processing module is specifically configured to: collect expression information by using video information. In this way, the expression information can be obtained through the video, and the video acquisition is more accurate, thereby more accurately determining the user's expression and other information.

According to another example, the text analysis module is specifically configured to: collect text emotion information by using voice information. In this way, the emotional information of the text can be analyzed through voice input, which is convenient and fast.

According to another example, the system includes an artificial intelligence cloud processing module for:

Extend the robot's self-awareness;

Get the parameters of the life timeline;

The self-cognitive parameters of the robot are fitted to the parameters in the life time axis to generate a robot life time axis. In this way, the life time axis is added to the self-cognition of the robot itself, so that the robot has an anthropomorphic life. For example, add the cognition of lunch to the robot.

According to another example, the artificial intelligence cloud processing module is further configured to combine a life scene with a self-awareness of the robot to form a self-cognitive curve based on a life time axis. In this way, the life time axis can be specifically added to the parameters of the robot itself.

According to another example, the artificial intelligence cloud processing module is further configured to: use The rate algorithm calculates the probability of each parameter change of the robot on the life time axis after the time axis scene parameter changes, and forms a fitting curve. The probability algorithm may be a Bayesian probability algorithm.

The above is a further detailed description of the present invention in connection with the specific preferred embodiments, and the specific embodiments of the present invention are not limited to the description. It will be apparent to those skilled in the art that the present invention may be made without departing from the spirit and scope of the invention.

Claims

A method for generating interactive content of a robot, comprising:

Obtaining the user's expression information;

Obtaining the user's text emotional information;

Determining the user's intention based on the expression information and the textual emotion information;

According to the expression information, the text emotion information, and the user intention, the robot interaction content is generated in combination with the current robot life time axis.
The generating method according to claim 1, wherein the expression information is collected by video information.
The generating method according to claim 1, wherein the text emotion information is collected by voice information.
The generating method according to claim 1, wherein the generating method of the parameter of the life time axis of the robot comprises:

Extend the robot's self-awareness;

Get the parameters of the life timeline;

The self-cognitive parameters of the robot are fitted to the parameters in the life time axis to generate a robot life time axis.
The generating method according to claim 4, wherein the step of expanding the self-cognition of the robot comprises: combining the life scene with the self-awareness of the robot to form a self-cognitive curve based on the life time axis.
The generating method according to claim 4, wherein the step of fitting the parameters of the self-cognition of the robot to the parameters in the life time axis comprises: using a probability algorithm to calculate the robot on the life time axis The probability of each parameter change after the time axis scene parameter is changed forms a fitted curve.
The generating method according to claim 4, wherein the life time axis refers to a time axis including 24 hours a day, and the parameter in the life time axis includes at least a user performing on the life time axis. Daily life behavior and the values of the parameters that represent the behavior.
A system for generating interactive content of a robot, comprising:

An expression visual processing module, configured to acquire expression information of the user;

a text analysis module, configured to obtain text emotional information of the user;

An intention identification module, configured to determine a user intention according to the expression information and the text emotion information;

a content generating module, configured to: according to the expression information, text emotional information, and the user's intention Figure, combined with the current robot life timeline to generate robot interaction content.
The generating system according to claim 8, wherein the expression visual processing module is specifically configured to: collect expression information by using video information.
The generating system according to claim 8, wherein the text analysis module is specifically configured to: collect text emotional information by using voice information.
The generating system according to claim 8, wherein the system comprises an artificial intelligence cloud processing module, configured to:

Extend the robot's self-awareness;

Get the parameters of the life timeline;

The self-cognitive parameters of the robot are fitted to the parameters in the life time axis to generate a robot life time axis.
The generating system according to claim 11, wherein the artificial intelligence cloud processing module is further configured to: combine a life scene with a self-awareness of the robot to form a self-cognitive curve based on a life time axis.
The generating system according to claim 11, wherein the artificial intelligence cloud processing module is further configured to: use a probability algorithm to calculate a probability of each parameter change of the robot on the life time axis after the time axis scene parameter is changed. , forming a fitted curve.
The generating system according to claim 11, wherein said life time axis refers to a time axis including 24 hours a day, and parameters in said life time axis include at least a user on said life time axis. Daily life behavior and the values of the parameters that represent the behavior.
A robot comprising a robot interactive content generating system according to any one of claims 8 to 14.