WO2019184103A1 - Person ip-based human-computer interaction method and system, medium and device - Google Patents
Person ip-based human-computer interaction method and system, medium and device Download PDFInfo
- Publication number
- WO2019184103A1 WO2019184103A1 PCT/CN2018/091636 CN2018091636W WO2019184103A1 WO 2019184103 A1 WO2019184103 A1 WO 2019184103A1 CN 2018091636 W CN2018091636 W CN 2018091636W WO 2019184103 A1 WO2019184103 A1 WO 2019184103A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- user
- character
- person
- knowledge map
- information
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
- G06F16/367—Ontology
Definitions
- An information acquisition module configured to acquire input information of a user
- the knowledge map comprises: a knowledge map and/or a general knowledge map with the person name of the default person IP as a core node.
- the information generating unit includes: an original information generating subunit, configured to generate original reply information corresponding to the input information according to the knowledge map subgraph and grammar rules; and a confidence calculation subunit for storing according to the The weight of the historical data and the user intent, calculating a confidence level of the default character IP in the current scene, each character habit; the habit determining subunit is configured to determine a reasonable character habit of the current scene according to the confidence level; The information generating subunit is configured to process the original reply information according to the reasonable character habit and grammar rules, and generate reply information with a preset default person IP as an image.
- the reply information includes: voice response information and/or action response information.
- FIG. 1 is a flowchart of a human-computer interaction method based on a character IP according to the present invention
- FIG. 2 is a schematic diagram of a human-computer interaction system based on a person IP according to the present invention.
- FIG. 1 is a flowchart of a human-computer interaction method based on a person IP according to a specific embodiment of the present invention.
- the human-computer interaction method based on a person IP provided by this embodiment includes:
- Step S101 Acquire input information of the user.
- the input information of the user may be one or more of voice input information, text input information, key operation input information, and the like, which are all within the protection scope of the present invention.
- the input information After the input information is obtained, the input information needs to be converted into text input information; if the input information obtained is text input information, no conversion is required.
- the input entity can be accurately extracted, thereby generating more reasonable reply information and better interacting with the user.
- the knowledge map is established, including: establishing a knowledge map with a character name of the character IP as a core node and a general knowledge map.
- the knowledge map of the established person IP may include a knowledge map of a plurality of characters IP.
- For each character IP multiple knowledge maps can be created, or a knowledge map can be created.
- the execution subject that establishes the knowledge map may be the server.
- the character knowledge map architecture refers to the knowledge map structure with the character name as the core node.
- the robot After the robot receives the character IP change command input by the user, according to the change instruction, the person IP is set from the default character IP to the new person IP, and the new knowledge map corresponding to the new person IP is retrieved from the database, and then according to the new knowledge map.
- Human-computer interaction with the user, the interaction process is the same as the interaction process of the default character IP.
- Example 1 The current character IP of the robot is character A, and the user input information obtained is “What is your age this year?”
- the robot searches for the triples related to the character A and the age from the knowledge map and the general knowledge map of the established character B.
- the character A and the character B have no social relationship, and finally the general knowledge map.
- the age information of the character A was found.
- Example 3 The current character IP of the robot is the character A, and the obtained user input information is “put a song to listen”.
- the information generating unit includes: an original information generating subunit, configured to generate original reply information corresponding to the input information according to the knowledge map subgraph and grammar rules; and a confidence calculation subunit for storing according to the The weight of the historical data and the user intent, calculating a confidence that the default character IP is in the current scene, the habit of each character; the habit determining subunit is configured to determine a reasonable character habit of the current scene according to the confidence level; And generating a subunit, configured to process the original reply information according to the reasonable character habit and grammar rules, and generate reply information with a preset default person IP as an image.
- the reply information includes: voice response information and/or action response information.
- the embodiment of the present invention further provides a human-computer interaction device based on a person IP, including: a memory, a processor, and a memory and can be stored in the memory
- a human-computer interaction device based on a person IP, including: a memory, a processor, and a memory and can be stored in the memory
- a computer program running on a processor which implements the above-described human IP-based human-computer interaction method when the processor executes the program.
- the human-computer interaction device based on the character IP provided by the embodiment of the present invention can realize the above-mentioned human-computer interaction method based on the character IP when the processor works, can give the robot anthropomorphic personality, and enable the robot to simulate the specific person IP to the specific person.
- the identity of the IP interacts with the user, and responds to the user more specifically; and considers the character habits of the character IP, making the robot more intelligent and anthropomorphic, and better interacting with the user, thereby improving the user experience.
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The present invention provides a person IP-based human-computer interaction method and system, a medium and a device. The method of the present invention comprises: acquiring input information of a user; extracting an input entity included in the input information; identifying a user intention according to the input information; according to the input entity and the user intention and on the basis of a pre-established knowledge graph, generating reply information in the persona of a preset default person IP; and outputting, in the persona of a default person IP, the reply information to the user. The present invention can give the robot a humanoid personality, making the robot simulate a specific person IP and interact with the user with the identity of the specific person IP, thereby responding to the user in a more customized manner; furthermore, the personal habits of the person IP are taken into consideration, enabling the robot to be smarter and humanoid and to better interact with the user, thereby improving the user experience.
Description
本发明涉及人工智能技术领域,具体涉及一种基于人物IP的人机交互方法、系统、介质及设备。The present invention relates to the field of artificial intelligence technologies, and in particular, to a human-computer interaction method, system, medium and device based on a person IP.
在现有技术中,机器人在对用户输入进行回复时,是通过在已有的对话库中检索与用户输入相近的问句,然后将该问句对应的答案作为对用户输入的回复;或者通过使用机器学习、深度学习、RNN等人工智能算法,通过将已有的对话数据进行标注,作为人工智能算法的输入,对人工智能算法进行训练得到训练模型,该模型可以在获得用户新输入后,自动生成对用户的回复,并没有考虑机器人的个性,不能以拟人化的方式回复用户,用户体验较差。In the prior art, when the robot responds to the user input, it searches for a question similar to the user input in the existing dialog library, and then uses the answer corresponding to the question as a reply to the user input; or Using artificial intelligence algorithms such as machine learning, deep learning, and RNN, the existing interactive data is labeled as an input of the artificial intelligence algorithm, and the artificial intelligence algorithm is trained to obtain a training model, which can obtain a new input from the user. The user's reply is automatically generated, and the personality of the robot is not considered. The user cannot be replied in an anthropomorphic manner, and the user experience is poor.
发明内容Summary of the invention
针对现有技术中的缺陷,本发明提供一种基于人物IP的人机交互方法、系统、介质及设备,能够赋予机器人拟人的人格,使机器人模拟具体人物IP,以具体人物IP的身份与用户进行交互,更有针对性地响应用户;并且考虑了人物IP的人物习惯,使机器人更加智能化、拟人化,更好地与用户进行交互,能够提高用户体验。In view of the deficiencies in the prior art, the present invention provides a human-computer interaction method, system, medium and device based on a person IP, which can give a robot anthropomorphic personality, and enable the robot to simulate a specific person IP, with the identity and user of the specific person IP. Interacting, more targeted response to users; and taking into account the character habits of the character IP, making the robot more intelligent, anthropomorphic, better interact with the user, can improve the user experience.
第一方面,本发明提供了一种基于人物IP的人机交互方法,包括:In a first aspect, the present invention provides a human-computer interaction method based on a person IP, including:
获取用户的输入信息;Obtain the user's input information;
提取所述输入信息中包含的输入实体;Extracting an input entity included in the input information;
根据所述输入信息识别用户意图;Identifying user intent based on the input information;
根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息;And generating, according to the input entity and the user intention, reply information with a preset default person IP as an image based on the pre-established knowledge map;
以所述默认人物IP为形象,向用户输出所述回复信息。The reply message is output to the user with the default person IP as an image.
优选地,所述知识图谱,包括:以默认人物IP的人物名称为核心节点的知识图谱和/或通用知识图谱。Preferably, the knowledge map comprises: a knowledge map and/or a general knowledge map with the person name of the default person IP as a core node.
优选地,根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息,包括:Preferably, according to the input entity and the user intention, based on the pre-established knowledge map, generating reply information with a preset default person IP as an image, including:
将所述输入实体与所述知识图谱中的实体进行关联;Associating the input entity with an entity in the knowledge map;
从所述知识图谱中,提取与所述输入实体和用户意图相关的知识图谱子图;Extracting, from the knowledge map, a knowledge map subgraph related to the input entity and user intent;
根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息。According to the knowledge map sub-graph and the grammar rule, the reply information with the preset default person IP as the image is generated.
优选地,根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息,包括:Preferably, according to the knowledge map sub-graph and the grammar rule, generating reply information with a preset default person IP as an image, including:
根据所述知识图谱子图和语法规则,生成与所述输入信息对应的原始回复信息;Generating original reply information corresponding to the input information according to the knowledge map sub-graph and the grammar rule;
根据储存的历史数据的权重和所述用户意图,计算默认人物IP在当前场景中,每种人物习惯出现的置信度;Calculating a confidence level of the default character IP in the current scene according to the weight of the stored historical data and the user intention;
根据所述置信度,确定当前场景的合理人物习惯;Determining a reasonable character habit of the current scene according to the confidence level;
根据所述合理人物习惯和语法规则,对所述原始回复信息进行加工,生成以预先设定的默认人物IP为形象的回复信息。According to the reasonable person habits and grammar rules, the original reply information is processed to generate reply information with a preset default person IP as an image.
优选地,还包括:Preferably, the method further comprises:
获取用户输入的人物IP更改指令;Obtaining the character IP change instruction input by the user;
根据所述更改指令,将人物IP从默认人物IP设置为新人物IP;According to the change instruction, the person IP is set from the default person IP to the new person IP;
从数据库中调取所述新人物IP对应的新知识图谱;Retrieving a new knowledge map corresponding to the IP of the new character from the database;
根据所述新知识图谱与用户进行人机交互。Performing human-computer interaction with the user according to the new knowledge map.
优选地,所述数据库中存储有至少一个人物IP的知识图谱。Preferably, the knowledge map of at least one person IP is stored in the database.
优选地,所述回复信息,包括:语音响应信息和/或动作响应信息。Preferably, the reply information includes: voice response information and/or action response information.
第二方面,本发明提供的一种基于人物IP的人机交互系统,包括:In a second aspect, the present invention provides a human-computer interaction system based on a person IP, including:
信息获取模块,用于获取用户的输入信息;An information acquisition module, configured to acquire input information of a user;
实体提取模块,用于提取所述输入信息中包含的输入实体;An entity extraction module, configured to extract an input entity included in the input information;
意图识别模块,用于根据所述输入信息识别用户意图;An intention identification module, configured to identify a user intention according to the input information;
回复生成模块,用于根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息;a reply generation module, configured to generate, according to the input entity and the user intention, reply information with a preset default person IP as an image based on the pre-established knowledge map;
信息输出模块,用于以所述默认人物IP为形象,向用户输出所述回复信息。The information output module is configured to output the reply information to the user by using the default character IP as an image.
优选地,所述知识图谱,包括:以默认人物IP的人物名称为核心节点的知识图谱和/或通用知识图谱。Preferably, the knowledge map comprises: a knowledge map and/or a general knowledge map with the person name of the default person IP as a core node.
优选地,回复生成模块,包括:关联单元,用于将所述输入实体与所述知识图谱中的实体进行关联;提取单元,用于从所述知识图谱中,提取与所述输入实体和用户意图相关的知识图谱子图;信息生成单元,用于根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息。Preferably, the reply generation module includes: an association unit, configured to associate the input entity with an entity in the knowledge map; and an extraction unit, configured to extract, from the knowledge map, the input entity and the user An intent-related knowledge map sub-graph; an information generating unit configured to generate reply information with a preset default person IP as an image according to the knowledge map sub-picture and the grammar rule.
优选地,信息生成单元,包括:原始信息生成子单元,用于根据所述知识图谱子图和语法规则,生成与所述输入信息对应的原始回复信息;置信度计算子单元,用于根据储存的历史数据的权重和所述用户意图,计算默认人物IP在当前场景中,每种人物习惯出现的置信度;习惯确定子单元,用于根据所述置信度,确定当前场景的合理人物习惯;信息生成子单元,用于根据所述合理人物习惯和语法规则,对所述原始回复信息进行加工,生成以预先设定的默认人物IP为形象的回复信息。Preferably, the information generating unit includes: an original information generating subunit, configured to generate original reply information corresponding to the input information according to the knowledge map subgraph and grammar rules; and a confidence calculation subunit for storing according to the The weight of the historical data and the user intent, calculating a confidence level of the default character IP in the current scene, each character habit; the habit determining subunit is configured to determine a reasonable character habit of the current scene according to the confidence level; The information generating subunit is configured to process the original reply information according to the reasonable character habit and grammar rules, and generate reply information with a preset default person IP as an image.
优选地,还包括:指令获取模块,用于获取用户输入的人物IP更改指令;更改模块,用于根据所述更改指令,将人物IP从默认人物IP设置为新人物IP;知识图谱调取模块,用于从数据库中调取所述新人物IP对应的新知识图谱;交互模块,用于根据所述新知识图谱与用户进行人机交互。Preferably, the method further includes: an instruction obtaining module, configured to acquire a character IP change instruction input by the user; and a change module, configured to set the character IP from the default character IP to the new person IP according to the change instruction; the knowledge map retrieval module And the new knowledge map corresponding to the new person IP is retrieved from the database; the interaction module is configured to perform human-computer interaction with the user according to the new knowledge map.
优选地,所述数据库中存储有至少一个人物IP的知识图谱。Preferably, the knowledge map of at least one person IP is stored in the database.
优选地,所述回复信息,包括:语音响应信息和/或动作响应信息。Preferably, the reply information includes: voice response information and/or action response information.
第三方面,本发明提供的一种计算机可读存储介质,其上存储有计算机程序,该程序被处理器执行时实现第一方面中的一种基于人物IP的人机交互方法。In a third aspect, the present invention provides a computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements a human IP interaction method based on a person IP in the first aspect.
第四方面,本发明提供的一种基于人物IP的人机交互设备,包括:存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序,所述处理器执行所述程序时实现第一方面中的一种基于人物IP的人机交互方法。In a fourth aspect, the present invention provides a human IP interaction device based on a person IP, comprising: a memory, a processor, and a computer program stored on the memory and operable on the processor, when the processor executes the program A human-computer interaction method based on the character IP in the first aspect is implemented.
本发明实施例提供的基于人物IP的人机交互方法,通过获取用户的输入信息,提取输入信息中包含的输入实体,根据输入信息识别用户意图,再根据输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息,最后以默认人物IP为形象,向用户输出回复信息。能够赋予机器人拟人的人格,使机器人模拟具体人物IP,以具体人物IP的身份与用户进行交互,更有针对性地响应用户;并且考虑了人物IP的人物习惯,使机器人更加智能化、拟人化,更好地与用户进行交互,能够提高用户体验。The human-computer interaction method based on the person IP provided by the embodiment of the present invention extracts the input entity included in the input information by acquiring the input information of the user, identifies the user intention according to the input information, and then based on the input entity and the user intention, based on the pre-established The knowledge map generates a reply message with a preset default person IP as an image, and finally outputs a reply message to the user with the default character IP as an image. It can give the robot a personification personality, enable the robot to simulate the specific person IP, interact with the user as the specific person IP, and respond to the user more specifically; and consider the character habits of the person IP to make the robot more intelligent and anthropomorphic Better interaction with users can improve the user experience.
本发明提供的一种基于人物IP的人机交互系统、一种计算机可读存储介质和一种基于人物IP的人机交互设备,与上述一种基于人物IP的人机交互方法出于相同的发明构思,具有相同的有益效果。The human IP interaction system based on the person IP, a computer readable storage medium and a human-computer interaction device based on the character IP provided by the invention are the same as the above-mentioned human-computer interaction method based on the character IP The inventive concept has the same advantageous effects.
为了更清楚地说明本发明具体实施方式或现有技术中的技术方案,下面将对具体实施方式或现有技术描述中所需要使用的附图作简单地介绍。在所有附图中,类似的元件或部分一般由类似的附图标记标识。附图中,各元件或部分并不一定按照实际的比例绘制。In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings to be used in the specific embodiments or the description of the prior art will be briefly described below. In all the figures, like elements or parts are generally identified by like reference numerals. In the figures, elements or parts are not necessarily drawn to scale.
图1为本发明提供的一种基于人物IP的人机交互方法的流程图;1 is a flowchart of a human-computer interaction method based on a character IP according to the present invention;
图2为本发明提供的一种基于人物IP的人机交互系统的示意图。FIG. 2 is a schematic diagram of a human-computer interaction system based on a person IP according to the present invention.
下面将结合附图对本发明技术方案的实施例进行详细的描述。以下实施例仅用于更加清楚地说明本发明的技术方案,因此只是作为示例,而不能以此来限制本发明的保护范围。The embodiments of the technical solution of the present invention will be described in detail below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention, and thus are merely exemplary and are not intended to limit the scope of the present invention.
需要注意的是,除非另有说明,本申请使用的技术术语或者科学术语应当为本发明所属领域技术人员所理解的通常意义。It should be noted that the technical terms or scientific terms used herein should be used in the ordinary meaning as understood by those skilled in the art to which the invention belongs, unless otherwise stated.
本发明提供了一种基于人物IP的人机交互方法、系统、介质及设备。下面结合附图对本发明的实施例进行说明。The invention provides a human-computer interaction method, system, medium and device based on a person IP. Embodiments of the present invention will be described below with reference to the accompanying drawings.
本发明的执行主体为聊天机器人,机器人在出厂时可以设置有默认人物IP,当用户在使用机器人时,机器人可以以默认人物IP为形象来与用户进行交互。本发明能够适配粉丝群体,满足用户需求。The execution body of the present invention is a chat robot. The robot can be set with a default character IP when it leaves the factory. When the user is using the robot, the robot can interact with the user with the default character IP as the image. The invention can adapt to the fan group and meet the user's needs.
请参考图1,图1为本发明具体实施例提供的一种基于人物IP的人机交互方法的流程图,本实施例提供的一种基于人物IP的人机交互方法,包括:Please refer to FIG. 1. FIG. 1 is a flowchart of a human-computer interaction method based on a person IP according to a specific embodiment of the present invention. The human-computer interaction method based on a person IP provided by this embodiment includes:
步骤S101:获取用户的输入信息。Step S101: Acquire input information of the user.
其中,用户的输入信息可以是语音输入信息、文字输入信息、按键操作输入信息等中的一种或多种,这都在本发明的保护范围内。The input information of the user may be one or more of voice input information, text input information, key operation input information, and the like, which are all within the protection scope of the present invention.
步骤S102:提取所述输入信息中包含的输入实体。Step S102: Extract an input entity included in the input information.
在获取到输入信息后,需要将输入信息转换为文字输入信息;如果获取到的输入信息为文字输入信息,则不需要进行转换。After the input information is obtained, the input information needs to be converted into text input information; if the input information obtained is text input information, no conversion is required.
在提取输入信息中包含的输入实体时,包括以下几个步骤:When extracting the input entities contained in the input information, the following steps are included:
第一步,将输入信息转换为文字输入信息;The first step is to convert the input information into text input information;
第二步,采用自然语言理解方法,对文字输入信息进行分词操作;The second step is to use a natural language understanding method to perform word segmentation on text input information;
第三步,采用实体对齐方式,将分词后的每个词语与实体对齐;In the third step, the physical alignment is used to align each word after the word segmentation with the entity;
第四步,采用消歧、泛化技术,识别词语中的实体,并提取该实体,作为输入实体。The fourth step is to use disambiguation and generalization techniques to identify the entity in the word and extract the entity as the input entity.
通过该方法能够准确地提取输入实体,进而能够生成更加合理的回复信息,更好地与用户进行交互。Through this method, the input entity can be accurately extracted, thereby generating more reasonable reply information and better interacting with the user.
步骤S103:根据所述输入信息识别用户意图。Step S103: Identify the user's intention according to the input information.
根据输入信息识别用户意图的过程为:The process of identifying user intent based on input information is:
提取输入信息中的输入实体,与步骤S102的方法相同;Extracting the input entity in the input information is the same as the method of step S102;
识别输入信息的句型;在识别句型时,可以利用常规规则进行识别;Identify the sentence pattern of the input information; when identifying the sentence pattern, it can be identified by using the regular rules;
根据提取的输入实体和输入信息的句型,识别用户意图。The user's intent is identified based on the extracted input entity and the sentence pattern of the input information.
在根据输入实体和句型识别用户意图时,可以采用机器学习方法、规则和槽填充等方法,来识别用户意图,任何适用的常规技术手段都可以用来识别用户意图。这里并不限定具体的用户意图识别方法。When the user's intent is identified based on the input entity and sentence pattern, methods such as machine learning methods, rules, and slot filling may be employed to identify the user's intent, and any applicable conventional techniques may be used to identify the user's intent. The specific user intent identification method is not limited herein.
步骤S104:根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息。Step S104: Generate reply information with a preset default person IP as an image based on the pre-established knowledge map according to the input entity and the user intention.
其中,所述知识图谱,包括:以默认人物IP的人物名称为核心节点的知识图谱和/或通用知识图谱。The knowledge map includes: a knowledge map and/or a general knowledge map with the person name of the default person IP as a core node.
在根据输入实体和用户意图,基于预先建立的知识图谱,生成回复信息之前,还可以包括:Before generating the reply information based on the pre-established knowledge map according to the input entity and the user's intention, the method may further include:
建立知识图谱,包括:建立以人物IP的人物名称为核心节点的知识图谱以及通用知识图谱。其中,建立的人物IP的知识图谱可以包括多个人物IP的知识图谱。对于每个人物IP,可以建立多个知识图谱,也可以建立一个知识图谱。通用知识图谱也可以有一个或多个,这都在本发明的保护范围内。在本发明中,建立知识图谱的执行主体可以是服务端。The knowledge map is established, including: establishing a knowledge map with a character name of the character IP as a core node and a general knowledge map. Wherein, the knowledge map of the established person IP may include a knowledge map of a plurality of characters IP. For each character IP, multiple knowledge maps can be created, or a knowledge map can be created. There may also be one or more general knowledge maps, which are all within the scope of the present invention. In the present invention, the execution subject that establishes the knowledge map may be the server.
在建立以人物IP的人物名称为核心节点的知识图谱时,包括:采集人物IP的人物信息;根据人物信息,建立以相应的人物名称为核心节点的知识图谱。When establishing the knowledge map with the character name of the character IP as the core node, the method includes: collecting the character information of the character IP; and, according to the character information, establishing the knowledge map with the corresponding character name as the core node.
具体人物IP的知识图谱的建立过程为:The process of establishing the knowledge map of the specific person IP is:
设置人物知识图谱架构;确定人物IP;采集人物IP的人物信息,根据人物信息和人物知识图谱架构,建立以相应的人物名称为核心节点的知识图谱。Set the character knowledge map structure; determine the character IP; collect the character information of the person IP, and establish a knowledge map with the corresponding person name as the core node according to the character information and the character knowledge map structure.
其中,人物IP是指特定人物形象,可以是明星人物。例如,用户A、用户B等人物IP。Among them, the character IP refers to a specific person image, which can be a star character. For example, user A, user B, and the like IP.
人物知识图谱架构是指以人物名称为核心节点的知识图谱架构。The character knowledge map architecture refers to the knowledge map structure with the character name as the core node.
其中,人物信息,可以包括:人物的客观信息、习惯信息、事件信息、主观态度信息等。The character information may include: objective information of the character, habit information, event information, subjective attitude information, and the like.
其中,客观信息,包括:别名/昵称、性别、出生日期、职业、特长、信仰、喜好、外貌特点、微博账户、粉丝数、作品(及作品的播放次数、人数、上市时间、具体角色、其它参与人员)、社会关系(朋友、婚恋关系、之前的婚恋关系)等。Among them, objective information, including: alias/nickname, gender, date of birth, occupation, specialty, belief, preference, appearance, Weibo account, number of fans, works (and number of times of play, number of people, time to market, specific role, Other participants), social relations (friends, relationships, previous marriages).
习惯信息,包括:人物对话习惯信息和人物动作习惯信息。Customary information, including: character dialogue habits and character action habits.
事件信息是指人物在一段时间内做过的一些有记录意义的事情。Event information refers to some recorded things that people have done over a period of time.
主观态度信息是指人物对某件事所持有的态度和观点等。Subjective attitude information refers to the attitudes and opinions held by a person on something.
人物对话习惯信息,包括:用词习惯、句式习惯、发音习惯、语气习惯等。Character dialogue habits, including: word habits, sentence habits, pronunciation habits, tone habits, etc.
人物动作习惯信息是指人物平时的习惯动作,例如,捂嘴、摸头、搓手等。The character action habit information refers to the usual habitual actions of the character, for example, grinning, touching, picking up hands, and the like.
上述人物信息包含从各个渠道收集到的该人物的所有信息,例如,可以通过直接提供已有知识图谱、网页检索提取、从采访中提取等方式获取信息。The above-mentioned person information includes all the information of the person collected from various channels, for example, information can be obtained by directly providing an existing knowledge map, extracting from a web page, extracting from an interview, and the like.
获取人物信息后,可以根据人物信息和人物知识图谱架构,构建以人物名称为核心节点的知识图谱。在构建时,将人物信息按照人物知识图谱架构进行分类并存储。例如,可以建立人物对话库、动作库等。这样,方便后续根据知识图谱响应用户的输入信息。After obtaining the character information, the knowledge map with the character name as the core node can be constructed according to the character information and the character knowledge map structure. At the time of construction, the character information is classified and stored according to the character knowledge map architecture. For example, a character dialogue library, an action library, and the like can be established. In this way, it is convenient to respond to the user's input information according to the knowledge map.
其中,人物对话库中包含有人物已有的对话内容,如从网页、影视作品、采访等途径获取的人物对话、问答的音视频,进而从音视频中提取到对话的内容和文字组成对话库。人物的动作库用于帮助虚拟聊天机器人模仿人物的动作。动作库中包括:人物舞蹈的整段视频、人物参演影视剧的动作片段、人物日常典型习惯性动作片段等。Among them, the character dialogue library contains the dialogue content of the character, such as the dialogue of the characters, the audio and video of the question and answer obtained from the webpage, the film and television works, the interview, etc., and then the content and the text of the dialogue are extracted from the audio and video to form a dialogue library. . The character's action library is used to help the virtual chat bot mimic the action of the character. The action library includes: the entire video of the character dance, the action segments of the characters participating in the film and television drama, and the typical habitual action segments of the characters.
对话库和动作库也可以以三元组的形式存储在知识图谱中。例如,人物IP为人物A,知识图谱中标识人物IP对应的对话库的三元组格式为<人物A,对话库,“DialogDatabase123055601”>,其中,DialogDatabase123055601表示人物A对应的对话库ID,可以作为人物A对话库的索引,通过该索引可以找到人物A的对话库。The dialog library and action library can also be stored in the knowledge map in the form of a triple. For example, the character IP is the character A, and the triplet format of the dialog library corresponding to the character IP in the knowledge map is <person A, dialog library, “DialogDatabase123055601”>, wherein DialogDatabase123055601 represents the dialog library ID corresponding to the character A, which can be used as The index of the character A dialog library, through which the character A's dialog library can be found.
在构建完人物IP的知识图谱后,可以实时采集所述人物形象的更新信息;根据所述更新信息,及时更新相应人物IP的知识图谱。这样,能够生成更加准确的回复信息,进而提高用户体验。After the knowledge map of the character IP is constructed, the update information of the character image may be collected in real time; and the knowledge map of the corresponding person IP is updated in time according to the update information. In this way, more accurate reply information can be generated, thereby improving the user experience.
其中,更新信息是指人物信息变更的信息。可以根据网络上的信息、新闻、系统推送等及时更新人物IP的知识图谱。The update information refers to information that changes the person information. The knowledge map of the person's IP can be updated in time according to information, news, system push, etc. on the network.
服务端可以建立以人物名称为核心节点的知识图谱,为聊天机器人提供与人物IP相对应的知识图谱,进而能够使聊天机器人以特定人物IP与用户进行交互,能够为用户提供更有针对性的、准确的回复信息,能够减少答非所问的情况,进而能够提高用户体验。The server can establish a knowledge map with the name of the person as the core node, and provide the chat robot with a knowledge map corresponding to the IP of the character, thereby enabling the chat robot to interact with the user with the specific person IP, and can provide the user with more targeted. Accurate reply information can reduce the number of questions and answers, and thus improve the user experience.
在本发明中,通用知识图谱用于存储公知的一些知识。在建立通用知识图谱时,首先,需要获取公知常识;然后,根据公知常识,建立通用知识图谱。In the present invention, a general knowledge map is used to store some of the well-known knowledge. When establishing a general knowledge map, first of all, it is necessary to obtain common knowledge; then, based on common knowledge, establish a general knowledge map.
在本发明中,不同知识图谱的结构具有一致性,均符合知识图谱的一般定义和结构。In the present invention, the structures of different knowledge maps are consistent and conform to the general definition and structure of the knowledge map.
在知识图谱中,一般用RDF形式化地表示这种三元关系。RDF(Resource Description Framework),即资源描述框架,是W3C制定的用于描述实体/资源的标准数据模型。知识图谱由一些相互连接的实体和他们的属性构成,简单理解,知识图谱是由一条条知识组成,每条知识表示为一个SPO三元组(Subject-Predicate-Object)。In the knowledge map, this ternary relationship is generally represented formally by RDF. RDF (Resource Description Framework), the resource description framework, is a standard data model developed by the W3C to describe entities/resources. The knowledge map consists of a number of interconnected entities and their attributes. It is simple to understand that the knowledge map consists of a set of knowledge, each of which is represented as an SPO triple (Subject-Predicate-Object).
在建立完知识图谱后,可以将知识图谱存储到机器人自带的存储设备中,也可以将知识图谱存储到远程服务器或者云服务器的数据库中,如果需要的知识图谱没有存储在自带的存储设备中,则可以在与用户交互过程中,临时从数据库中调取相应的知识图谱。After the knowledge map is established, the knowledge map can be stored in the storage device that is provided by the robot, or the knowledge map can be stored in the database of the remote server or the cloud server, if the required knowledge map is not stored in the storage device. In the process of interacting with the user, the corresponding knowledge map can be temporarily retrieved from the database.
在建立完知识图谱后,根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息,包括:将所述输入实体与所述知识图谱中的实体进行关联;从所述知识图谱中,提取与所述输入实体和用户意图相关的知识图谱子图;根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息。After the knowledge map is established, based on the input entity and the user's intention, based on the pre-established knowledge map, generating reply information with a preset default person IP as an image, including: inputting the input entity and the knowledge map The entity in the association is associated; extracting, from the knowledge map, a knowledge map sub-graph related to the input entity and the user intent; and generating, according to the knowledge map sub-graph and the grammar rule, a preset default person IP Image reply message.
回复信息的生成过程:Reply message generation process:
输入实体与知识图谱中的实体进行关联的过程为:将输入实体与知识图谱中的实体进行对比,将相同实体或相似实体进行关联。The process of associating an input entity with an entity in a knowledge map is: associating an input entity with an entity in a knowledge map to associate the same entity or a similar entity.
关联后,可以直接提取相应的多个三元组,也可以根据关联的三元组重新生成新三元组,并存储,进而得到与输入实体相关的多个三元组。After the association, the corresponding plurality of triples may be directly extracted, or the new triplet may be regenerated according to the associated triplet and stored, thereby obtaining a plurality of triples related to the input entity.
再从知识图谱中与输入实体相关的三元组中,提取与用户意图相关的三元组,组成知识图谱子图。Then, from the triples related to the input entity in the knowledge map, the triples related to the user's intention are extracted to form a knowledge map subgraph.
最后,根据知识图谱子图和语法规则,将知识图谱子图中的三元组根据语法规则进行拆分、组合,生成以预先设定的默认人物IP为形象的回复信息。Finally, according to the knowledge map subgraph and grammar rules, the triples in the knowledge map subgraph are split and combined according to the grammar rules, and the reply information with the preset default person IP as the image is generated.
根据该过程生成的回复信息,能够很好地符合用户的输入信息,有针对性地进行答复。According to the reply information generated by the process, the user's input information can be well matched, and the response is targeted.
在本发明提供的一个具体实施例中,根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息,包括:根据所述知识图谱子图和语法规则,生成与所述输入信息对应的原始回复信息;根据储存的历史数据的权重和所述用户意图,计算默认人物IP在当前场景中,每种人物习惯出现的置信度;根据所述置信度,确定当前场景的合理人物习惯;根据所述合理人物习惯和语法规则,对所述原始回复信息进行加工,生成以预先设定的默认人物IP为形象的回复信息。In a specific embodiment provided by the present invention, according to the knowledge map sub-graph and the grammar rule, generating reply information with a preset default person IP as an image, including: according to the knowledge map sub-graph and grammar rules, Generating original reply information corresponding to the input information; calculating, according to the weight of the stored historical data and the user's intention, a confidence level of the default character IP in the current scene, and each character's habit appears; determining according to the confidence level Reasonable character habits of the current scene; processing the original reply information according to the reasonable character habits and grammar rules, and generating reply information with a preset default person IP as an image.
在根据知识图谱子图和语法规则,生成回复信息时,还可以加入人物习惯,使回复信息更加有针对性,更加逼真,进而提高用户体验。In the generation of reply information according to the knowledge map sub-graph and grammar rules, character habits can also be added, so that the reply information is more targeted and more realistic, thereby improving the user experience.
具体步骤为:The specific steps are:
第一步,根据知识图谱子图和语法规则,生成与输入信息对应的原始 回复信息;具体过程与上述根据知识图谱子图和语法规则生成回复信息的过程相同。In the first step, the original reply information corresponding to the input information is generated according to the knowledge map subgraph and the grammar rule; the specific process is the same as the above process of generating the reply information according to the knowledge map subgraph and the grammar rule.
第二步,根据存储的历史数据的权重和用户意图,计算默认人物IP在当前场景中,每种人物习惯出现的置信度;In the second step, according to the weight of the stored historical data and the user's intention, the confidence of the default character IP in the current scene and the habit of each character is calculated;
在计算每种人物习惯出现的置信度之前,需要查找人物习惯,人物习惯可以存储在知识图谱中,也可以存储在提前取出来的习惯子图中,这都在本发明的保护范围内。通过提取出习惯子图备用,能够提高回复信息生成的效率。Before calculating the confidence level of each character's habit, it is necessary to find the character habits, the character habits can be stored in the knowledge map, or can be stored in the habit subgraphs taken out in advance, which are all within the scope of the present invention. By extracting the habit subgraphs, the efficiency of reply information generation can be improved.
其中,历史数据是指存储的人物IP的说话数据,可以包括:说话内容和说话场景的数据。The historical data refers to the spoken data of the stored person IP, and may include: the spoken content and the data of the speaking scene.
优选的,历史数据的权重与说话数据的产生时间有关,时间点越近的数据越能反应人物形象最近的习惯,因此,可以设置时间点近的数据权值高。Preferably, the weight of the historical data is related to the generation time of the speech data, and the closer the data is, the more the data can reflect the most recent habit of the character image. Therefore, the data weight near the time point can be set high.
再根据历史数据的权重和用户意图,计算在当前场景中,每种人物习惯出现的置信度。Based on the weight of the historical data and the user's intention, the confidence level of each character's habit appears in the current scene.
在计算置信度时,统计历史数据中与用户意图相符的当前场景中所有的人物习惯,包括语言习惯和动作习惯,再根据每种人物习惯的权重,也就是相应的历史数据的权重,计算每种人物习惯的置信度。When calculating the confidence, all the character habits in the current scene in the historical data that match the user's intention are included, including language habits and action habits, and then according to the weight of each character's habits, that is, the weight of the corresponding historical data, calculate each The confidence of a person's habits.
第三步,根据计算得到的置信度,确定当前场景的合理人物习惯。The third step is to determine the reasonable character habits of the current scene based on the calculated confidence.
若查找到用户在当前场景中使用的人物习惯有多个,且每种人物习惯的置信度不同,则选择置信度最高的人物习惯作为合理人物习惯。If it is found that there are multiple character habits used by the user in the current scene, and the confidence of each character's habit is different, then the person with the highest confidence is selected as a reasonable character habit.
当两种人物习惯的置信度相同时,可以将两种人物习惯都作为合理人物习惯,也可以随机选择其中一种人物习惯作为合理人物习惯。When the confidence of the two characters is the same, the two characters can be used as a reasonable character habit, or one of the characters can be randomly selected as a reasonable character habit.
第四步,根据合理人物习惯和语法规则,对所述原始回复信息进行加工,生成以预先设定的默认人物IP为形象的回复信息。In the fourth step, the original reply information is processed according to reasonable character habits and grammar rules, and a reply message with a preset default person IP as an image is generated.
选择好合理人物习惯后,将合理人物习惯加入到原始回复信息中,对原始回复信息进行加工,在加工过程中,需要依据语法规则,生成符合语法规则的回复信息。After selecting a reasonable character habit, the reasonable character habits are added to the original reply information, and the original reply information is processed. In the process of processing, a reply message conforming to the grammatical rules is generated according to the grammar rules.
例如,机器人人物IP形象为人物A,输入信息为:“你的年龄是多少?”原始回复信息为:“我出生于1982年,今年35岁”,合理人物习惯为:“哎呦,不错哦”,加工后的以人物IP为形象的回复信息为:“哎呦,我出生于1982年,今年35岁,不错哦”。For example, the IP image of the robot character is the character A, and the input message is: “What is your age?” The original reply message is: “I was born in 1982, 35 years old this year.” Reasonable characters are used to: “Hey, good. "The processed reply message with the character IP is: "Hey, I was born in 1982, 35 years old this year, not bad."
在本发明中,如果知识图谱中没有存储人物习惯,则不需要结合人物习惯生成回复信息,直接根据知识图谱子图和语法规则,生成回复信息。In the present invention, if the character habit is not stored in the knowledge map, it is not necessary to generate reply information in combination with the character habit, and the reply information is generated directly according to the knowledge map subgraph and the grammar rule.
通过考虑不同场景不同的人物习惯,可以根据不同的输入信息,有针对性地结合不同的人物习惯,向用户输出更加逼真的回复信息,进而提高用户体验。By considering different people's habits in different scenes, it is possible to combine different character habits according to different input information, and output more realistic reply information to the user, thereby improving the user experience.
在本发明提供的一个具体实施例中,所述方法,还可以包括:获取用户输入的人物IP更改指令;根据所述更改指令,将人物IP从默认人物IP设置为新人物IP;从数据库中调取所述新人物IP对应的新知识图谱;根据所述新知识图谱与用户进行人机交互。In a specific embodiment provided by the present invention, the method may further include: acquiring a character IP change instruction input by the user; and setting the person IP from the default person IP to the new person IP according to the change instruction; Retrieving a new knowledge map corresponding to the new person IP; and performing human-computer interaction with the user according to the new knowledge map.
用户在使用机器人的过程中,如果对当前的人物形象不满意,还可以更改人物IP,当前的人物IP可以是默认人物IP,也可以是用户已经更换过的人物IP,可以多次进行更换。In the process of using the robot, if the user is dissatisfied with the current character image, the IP of the character can also be changed. The current character IP can be the default character IP, or the IP of the person that the user has changed, and can be replaced multiple times.
当机器人接收到用户输入的人物IP更改指令后,根据更改指令,将人物IP从默认人物IP设置为新人物IP,并从数据库中调取新人物IP对应的新知识图谱,再根据新知识图谱与用户进行人机交互,交互过程与默认人物IP的交互过程相同。After the robot receives the character IP change command input by the user, according to the change instruction, the person IP is set from the default character IP to the new person IP, and the new knowledge map corresponding to the new person IP is retrieved from the database, and then according to the new knowledge map. Human-computer interaction with the user, the interaction process is the same as the interaction process of the default character IP.
用户向机器人发送人物IP更改指令时,可以通过语音发送指令,也可以通过按键、动作等其它方式发送指令。这都在本发明的保护范围内。When the user sends a character IP change command to the robot, the command can be sent by voice, or the command can be sent by other means such as a button or an action. This is all within the scope of the invention.
通过这种方式切换聊天机器人的人物IP,不需要更改底层的代码,人物IP切换更加方便,利于聊天机器人产品的推广和维护。By switching the character IP of the chat robot in this way, there is no need to change the underlying code, and the IP switching of the character is more convenient, which is advantageous for the promotion and maintenance of the chat robot product.
步骤S105:以所述默认人物IP为形象,向用户输出所述回复信息。Step S105: output the reply information to the user by using the default character IP as an image.
最后,以默认人物IP为形象,向用户输出回复信息。Finally, the default person IP is used as the image to output a reply message to the user.
其中,回复信息可以包括:语音回复信息和/或动作回复信息。The reply information may include: voice reply information and/or action reply information.
用户与聊天机器人闲聊,在对话时,问聊天机器人的年龄,聊天机器 人会回答当前设置的人物IP的年龄,聊天机器人可以以语音的形式、动作(手语、口型)的形式等回答自己的年龄。当用户要求聊天机器人展示某一动作,聊天机器人可以根据用户的输入信息,基于知识图谱中存储的人物IP的习惯动作,对用户进行多模态回复,将相应的动作展示给用户。The user chats with the chat bot. When talking, asks the age of the chat bot. The chat bot will answer the age of the currently set person IP. The chat bot can answer his or her age in the form of voice, action (sign language, mouth type), etc. . When the user requests the chat robot to display a certain action, the chat robot can perform multi-modal reply to the user based on the user's input information, based on the custom action of the person's IP stored in the knowledge map, and present the corresponding action to the user.
例如,用户要求机器人展示人物A某一动作,如表演MV,则机器人从知识图谱中检索人物A的动作库,并从动作库中找到相应MV的动作,再将该动作展示给用户。For example, if the user asks the robot to display a certain action of the character A, such as a performance MV, the robot retrieves the action library of the character A from the knowledge map, and finds the action of the corresponding MV from the action library, and then presents the action to the user.
例如,如果用户在要求机器人满足陪伴需求,如读书,则机器人需要模仿人物A讲话的音调、音色、语气等读书。机器人在选择读书的书本时,可以检索知识图谱,寻找人物A经常读书的书籍和/或用户喜欢的书籍,并利用语音模式展示该书籍。For example, if the user is asking the robot to meet the companion needs, such as reading, the robot needs to imitate the tone, tone, tone, etc. of the character A's speech. When selecting a book to read, the robot can retrieve the knowledge map, find books that the character A often reads, and/or books that the user likes, and display the book in a voice mode.
例如,如果用户要求机器人展示技能,如写诗等,首先检索人物A知识图谱,确定人物A是否有相应的技能,如果有,则选择人物A已经写出的作品展示给用户(朗读),如果没有,则机器人根据人物A习惯的回应方式和人物性格回应用户“没做过/不会/不做”等。For example, if the user asks the robot to display skills, such as writing poetry, first search the character A knowledge map to determine whether the character A has the corresponding skill, and if so, select the work that the character A has written to display to the user (read aloud), if No, the robot responds to the user's "not done / not / not done" according to the response mode and character of the character A's habits.
示例1:机器人当前人物IP为人物A,获取的用户输入信息为“你今年的年龄是多少?”Example 1: The current character IP of the robot is character A, and the user input information obtained is “What is your age this year?”
机器人识别的用户意图是“闲聊”,主体是“机器”,对象是“年龄”,其中,对象和主体都属于输入实体。其中,在识别主体时,采用了泛化技术,将“你”识别为主体“机器”,也就是“人物A”。The user intent of the robot recognition is "chat", the subject is "machine", and the object is "age", in which both the object and the subject belong to the input entity. Among them, when identifying the subject, the generalization technique is adopted, and "you" is recognized as the subject "machine", that is, "person A".
机器人根据输入实体和用户意图,从建立的人物A的知识图谱和通用知识图谱中,查找与年龄有关的三元组,查找的结果可能为:(“人物A”,“年龄”,“35”)、(“人物A”,“出生时间”,“1982”),这两个三元组可以组成知识图谱子图,根据该知识图谱子图和语法规则,可以生成原始回复信息:“我出生于1982年,今年35岁”。Based on the input entity and user intent, the robot searches for the age-related triples from the established knowledge map of the character A and the general knowledge map. The search result may be: ("character A", "age", "35" ), ("People A", "Birth Time", "1982"), these two triples can form a knowledge map subgraph, according to the knowledge map subgraph and grammar rules, can generate the original reply message: "I was born In 1982, this year is 35 years old."
再从人物A的知识图谱中查找人物A的用语习惯和对相关提问的回复习惯,并计算每种人物习惯的置信度,选择置信度较高的人物习惯作为合理人物习惯,例如,仅查找到人物A的的用语习惯为“哎呦,不错哦”,但未查找到其它相关的人物习惯,则该用语习惯为合理人物习惯。最后,根 据合理人物习惯和语法规则,对原始回复信息进行加工,最终生成的回复信息为:“哎呦,我出生于1982年,今年35岁,不错哦”。Then look up the character A's habits of the character A and the reply habits of the related questions from the knowledge map of the character A, and calculate the confidence of each character's habits, and select the character with higher confidence as a reasonable character habit, for example, only find The idiom habit of character A is “哎呦, not bad”, but the habit of using other related characters is not used, so the terminology is a reasonable character habit. Finally, according to reasonable character habits and grammatical rules, the original reply information is processed, and the resulting reply message is: “Hey, I was born in 1982, 35 years old this year, not bad.”
机器人再以人物A的身份形象,向用户回复:“哎呦,我出生于1982年,今年35岁,不错哦”。The robot then responded to the user with the identity of the character A: "Hey, I was born in 1982, 35 years old this year, not bad."
示例2:机器人当前人物IP为人物B,获取的用户输入信息为:“人物A今年的年龄是多少?”Example 2: The current character IP of the robot is the character B, and the obtained user input information is: "What is the age of the character A this year?"
机器人识别的用户意图是“闲聊”,主体是“人物A”,对象是“年龄”,其中,对象和主体都属于输入实体。The user's intention of the robot recognition is "chat", the subject is "person A", and the object is "age", in which both the object and the subject belong to the input entity.
机器人根据输入实体和用户意图,从建立的人物B的知识图谱和通用知识图谱中,查找与人物A和年龄有关的三元组,但是,人物A与人物B没有社会关系,最终在通用知识图谱中查找到了人物A的年龄信息。According to the input entity and the user's intention, the robot searches for the triples related to the character A and the age from the knowledge map and the general knowledge map of the established character B. However, the character A and the character B have no social relationship, and finally the general knowledge map. The age information of the character A was found.
机器人查找到人物B的习惯用户为空,则直接根据查找的年龄信息,结合语法规则,生成回复信息,最终的回复信息可以为:“人物B刚帮你问了,人物A出生于1982年,今年35岁”。When the robot finds that the custom user of the character B is empty, the response information is generated according to the age information of the search and the grammar rule. The final reply message can be: "The character B just asked you, the character A was born in 1982. 35 years old this year."
机器人再以人物B的身份形象,向用户回复:“人物B刚帮你问了,人物A出生于1982年,今年35岁”。The robot then responded to the user with the identity of the character B: "Character B just asked you, character A was born in 1982, 35 years old this year."
示例3:机器人当前人物IP为人物A,获取的用户输入信息为“放首歌来听听”。Example 3: The current character IP of the robot is the character A, and the obtained user input information is “put a song to listen”.
提取的输入实体为:“歌”,用户意图为“放松听歌”,则根据输入实体和用户意图,从人物A的知识图谱和通用知识图谱中查找与歌和人物A相关的知识图谱子图,发现人物A发布了新歌,则机器人向用户输出:“那好吧,听听我的新歌XXX”。The extracted input entity is: "song", the user's intention is "relaxed listening to the song", and according to the input entity and the user's intention, the knowledge map sub-picture related to the song and the character A is searched from the knowledge map of the character A and the general knowledge map. When the character A is released with a new song, the robot outputs to the user: "Well, listen to my new song XXX."
通过本发明,能够赋予机器人拟人的人格,使机器人模拟具体人物IP,以具体人物IP的身份与用户进行交互,更有针对性地响应用户;并且考虑了人物IP的人物习惯,使机器人更加智能化、拟人化,更好地与用户进行交互,能够提高用户体验。Through the invention, the human character of the robot can be given, the robot simulates the IP of the specific character, interacts with the user with the identity of the specific person IP, and responds to the user more specifically; and considers the character habit of the character IP to make the robot smarter. Anthropomorphic and better interaction with users can improve the user experience.
基于与上述一种基于人物IP的人机交互方法相同的发明构思,本发明 实施例提供了一种基于人物IP的人机交互系统,如图2所示,包括:信息获取模块101,用于获取用户的输入信息;实体提取模块102,用于提取所述输入信息中包含的输入实体;意图识别模块103,用于根据所述输入信息识别用户意图;回复生成模块104,用于根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息;信息输出模块105,用于以所述默认人物IP为形象,向用户输出所述回复信息。The embodiment of the present invention provides a human-computer interaction system based on a person IP, as shown in FIG. 2, which includes an information acquisition module 101, which is used for the human-computer interaction system based on the above-mentioned human IP-based human-computer interaction method. Obtaining input information of the user; the entity extracting module 102 is configured to extract an input entity included in the input information; the intent identifying module 103 is configured to identify a user intent according to the input information; and the reply generating module 104 is configured to: Entering entity and user intent, based on the pre-established knowledge map, generating reply information with a preset default person IP as an image; the information output module 105 is configured to output the reply to the user by using the default person IP as an image information.
其中,所述知识图谱,包括:以默认人物IP的人物名称为核心节点的知识图谱和/或通用知识图谱。The knowledge map includes: a knowledge map and/or a general knowledge map with the person name of the default person IP as a core node.
其中,回复生成模块104,包括:关联单元,用于将所述输入实体与所述知识图谱中的实体进行关联;提取单元,用于从所述知识图谱中,提取与所述输入实体和用户意图相关的知识图谱子图;信息生成单元,用于根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息。The reply generation module 104 includes: an association unit, configured to associate the input entity with an entity in the knowledge map; and an extraction unit, configured to extract, from the knowledge map, the input entity and the user An intent-related knowledge map sub-graph; an information generating unit configured to generate reply information with a preset default person IP as an image according to the knowledge map sub-picture and the grammar rule.
其中,信息生成单元,包括:原始信息生成子单元,用于根据所述知识图谱子图和语法规则,生成与所述输入信息对应的原始回复信息;置信度计算子单元,用于根据储存的历史数据的权重和所述用户意图,计算默认人物IP在当前场景中,每种人物习惯出现的置信度;习惯确定子单元,用于根据所述置信度,确定当前场景的合理人物习惯;信息生成子单元,用于根据所述合理人物习惯和语法规则,对所述原始回复信息进行加工,生成以预先设定的默认人物IP为形象的回复信息。The information generating unit includes: an original information generating subunit, configured to generate original reply information corresponding to the input information according to the knowledge map subgraph and grammar rules; and a confidence calculation subunit for storing according to the The weight of the historical data and the user intent, calculating a confidence that the default character IP is in the current scene, the habit of each character; the habit determining subunit is configured to determine a reasonable character habit of the current scene according to the confidence level; And generating a subunit, configured to process the original reply information according to the reasonable character habit and grammar rules, and generate reply information with a preset default person IP as an image.
在本发明提供的一个具体实施例中,还可以包括:指令获取模块,用于获取用户输入的人物IP更改指令;更改模块,用于根据所述更改指令,将人物IP从默认人物IP设置为新人物IP;知识图谱调取模块,用于从数据库中调取所述新人物IP对应的新知识图谱;交互模块,用于根据所述新知识图谱与用户进行人机交互。In a specific embodiment provided by the present invention, the method may further include: an instruction obtaining module, configured to acquire a character IP change instruction input by the user; and a change module, configured to set the character IP from the default person IP according to the change instruction a new character IP; a knowledge map retrieval module, configured to retrieve a new knowledge map corresponding to the new person IP from the database; and an interaction module, configured to perform human-computer interaction with the user according to the new knowledge map.
其中,所述数据库中存储有至少一个人物IP的知识图谱。The knowledge map of at least one person IP is stored in the database.
其中,所述回复信息,包括:语音响应信息和/或动作响应信息。The reply information includes: voice response information and/or action response information.
本发明实施例提供的基于人物IP的人机交互系统,在机器人中加入了 知识图谱,该知识图谱包括:以人物IP的人物名称为核心节点的知识图谱以及通用知识图谱,能够赋予机器人拟人的人格,使机器人模拟具体人物IP,以具体人物IP的身份与用户进行交互,更有针对性地响应用户;并且考虑了人物IP的人物习惯,使机器人更加智能化、拟人化,更好地与用户进行交互,能够提高用户体验。The human-computer interaction system based on the character IP provided by the embodiment of the present invention adds a knowledge map to the robot, and the knowledge map includes: a knowledge map with a character name of the person IP as a core node and a general knowledge map, which can give the robot anthropomorphic Personality, the robot simulates the specific person IP, interacts with the user with the identity of the specific person IP, and responds to the user more specifically; and considers the character habits of the character IP, making the robot more intelligent and anthropomorphic, better with Users interact to improve the user experience.
基于与上述一种基于人物IP的人机交互方法相同的发明构思,本发明实施例提供了一种计算机可读存储介质,其上存储有计算机程序,该程序被处理器执行时实现上述一种基于人物IP的人机交互方法。The embodiment of the present invention provides a computer readable storage medium having a computer program stored thereon, and the program is implemented by the processor to implement the above-mentioned one, based on the same inventive concept as the above-described human IP-based human-computer interaction method. Human-computer interaction method based on character IP.
本发明实施例提供的计算机可读存储介质,能够在处理器的控制下,实现上述基于人物IP的人机交互方法,能够赋予机器人拟人的人格,使机器人模拟具体人物IP,以具体人物IP的身份与用户进行交互,更有针对性地响应用户;并且考虑了人物IP的人物习惯,使机器人更加智能化、拟人化,更好地与用户进行交互,能够提高用户体验。The computer readable storage medium provided by the embodiment of the present invention can realize the human-computer interaction method based on the character IP under the control of the processor, and can give the robot a personification personality, and the robot simulates the specific person IP to the specific person IP. The identity interacts with the user and responds to the user more specifically; and considers the character habits of the character IP, making the robot more intelligent and anthropomorphic, and better interacting with the user, which can improve the user experience.
基于与上述一种基于人物IP的人机交互方法相同的发明构思,本发明实施例还提供了一种基于人物IP的人机交互设备,包括:存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序,所述处理器执行所述程序时实现上述一种基于人物IP的人机交互方法。Based on the same inventive concept as the above-described human IP-based human-computer interaction method, the embodiment of the present invention further provides a human-computer interaction device based on a person IP, including: a memory, a processor, and a memory and can be stored in the memory A computer program running on a processor, which implements the above-described human IP-based human-computer interaction method when the processor executes the program.
本发明实施例提供的基于人物IP的人机交互设备,能够在处理器工作时,实现上述基于人物IP的人机交互方法,能够赋予机器人拟人的人格,使机器人模拟具体人物IP,以具体人物IP的身份与用户进行交互,更有针对性地响应用户;并且考虑了人物IP的人物习惯,使机器人更加智能化、拟人化,更好地与用户进行交互,能够提高用户体验。The human-computer interaction device based on the character IP provided by the embodiment of the present invention can realize the above-mentioned human-computer interaction method based on the character IP when the processor works, can give the robot anthropomorphic personality, and enable the robot to simulate the specific person IP to the specific person. The identity of the IP interacts with the user, and responds to the user more specifically; and considers the character habits of the character IP, making the robot more intelligent and anthropomorphic, and better interacting with the user, thereby improving the user experience.
本发明的说明书中,说明了大量具体细节。然而,能够理解,本发明的实施例可以在没有这些具体细节的情况下实践。在一些实例中,并未详细示出公知的方法、结构和技术,以便不模糊对本说明书的理解。In the description of the invention, numerous specific details are illustrated. However, it is understood that the embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of the description.
在本说明书的描述中,参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中,对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且,描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外,在不相互矛盾的情况下,本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。In the description of the present specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means a specific feature described in connection with the embodiment or example. A structure, material or feature is included in at least one embodiment or example of the invention. In the present specification, the schematic representation of the above terms is not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, various embodiments or examples described in the specification, as well as features of various embodiments or examples, may be combined and combined.
最后应说明的是:以上各实施例仅用以说明本发明的技术方案,而非对其限制;尽管参照前述各实施例对本发明进行了详细的说明,本领域的普通技术人员应当理解:其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分或者全部技术特征进行等同替换;而这些修改或者替换,并不使相应技术方案的本质脱离本发明各实施例技术方案的范围,其均应涵盖在本发明的权利要求和说明书的范围当中。Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that The technical solutions described in the foregoing embodiments may be modified, or some or all of the technical features may be equivalently replaced; and the modifications or substitutions do not deviate from the technical solutions of the embodiments of the present invention. The scope is intended to be included within the scope of the claims and the description of the invention.
Claims (10)
- 一种基于人物IP的人机交互方法,其特征在于,包括:A human-computer interaction method based on character IP, characterized in that it comprises:获取用户的输入信息;Obtain the user's input information;提取所述输入信息中包含的输入实体;Extracting an input entity included in the input information;根据所述输入信息识别用户意图;Identifying user intent based on the input information;根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息;And generating, according to the input entity and the user intention, reply information with a preset default person IP as an image based on the pre-established knowledge map;以所述默认人物IP为形象,向用户输出所述回复信息。The reply message is output to the user with the default person IP as an image.
- 根据权利要求1所述的方法,其特征在于,所述知识图谱,包括:以默认人物IP的人物名称为核心节点的知识图谱和/或通用知识图谱。The method according to claim 1, wherein the knowledge map comprises: a knowledge map and/or a general knowledge map with a person name of a default person IP as a core node.
- 根据权利要求2所述的方法,其特征在于,根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息,包括:The method according to claim 2, wherein, based on the input entity and the user's intention, based on the pre-established knowledge map, generating reply information with a preset default person IP as an image, including:将所述输入实体与所述知识图谱中的实体进行关联;Associating the input entity with an entity in the knowledge map;从所述知识图谱中,提取与所述输入实体和用户意图相关的知识图谱子图;Extracting, from the knowledge map, a knowledge map subgraph related to the input entity and user intent;根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息。According to the knowledge map sub-graph and the grammar rule, the reply information with the preset default person IP as the image is generated.
- 根据权利要求3所述的方法,其特征在于,根据所述知识图谱子图和语法规则,生成以预先设定的默认人物IP为形象的回复信息,包括:The method according to claim 3, wherein the reply information based on the preset default person IP is generated according to the knowledge map sub-graph and the grammar rule, and includes:根据所述知识图谱子图和语法规则,生成与所述输入信息对应的原始回复信息;Generating original reply information corresponding to the input information according to the knowledge map sub-graph and the grammar rule;根据储存的历史数据的权重和所述用户意图,计算默认人物IP在当前场景中,每种人物习惯出现的置信度;Calculating a confidence level of the default character IP in the current scene according to the weight of the stored historical data and the user intention;根据所述置信度,确定当前场景的合理人物习惯;Determining a reasonable character habit of the current scene according to the confidence level;根据所述合理人物习惯和语法规则,对所述原始回复信息进行加工,生成以预先设定的默认人物IP为形象的回复信息。According to the reasonable person habits and grammar rules, the original reply information is processed to generate reply information with a preset default person IP as an image.
- 根据权利要求1所述的方法,其特征在于,还包括:The method of claim 1 further comprising:获取用户输入的人物IP更改指令;Obtaining the character IP change instruction input by the user;根据所述更改指令,将人物IP从默认人物IP设置为新人物IP;According to the change instruction, the person IP is set from the default person IP to the new person IP;从数据库中调取所述新人物IP对应的新知识图谱;Retrieving a new knowledge map corresponding to the IP of the new character from the database;根据所述新知识图谱与用户进行人机交互。Performing human-computer interaction with the user according to the new knowledge map.
- 根据权利要求5所述的方法,其特征在于,所述数据库中存储有至少一个人物IP的知识图谱。The method according to claim 5, characterized in that the knowledge map of at least one person IP is stored in the database.
- 根据权利要求1所述的方法,其特征在于,所述回复信息,包括:语音响应信息和/或动作响应信息。The method according to claim 1, wherein the reply information comprises: voice response information and/or action response information.
- 一种基于人物IP的人机交互系统,其特征在于,包括:A human-computer interaction system based on a character IP, characterized in that it comprises:信息获取模块,用于获取用户的输入信息;An information acquisition module, configured to acquire input information of a user;实体提取模块,用于提取所述输入信息中包含的输入实体;An entity extraction module, configured to extract an input entity included in the input information;意图识别模块,用于根据所述输入信息识别用户意图;An intention identification module, configured to identify a user intention according to the input information;回复生成模块,用于根据所述输入实体和用户意图,基于预先建立的知识图谱,生成以预先设定的默认人物IP为形象的回复信息;a reply generation module, configured to generate, according to the input entity and the user intention, reply information with a preset default person IP as an image based on the pre-established knowledge map;信息输出模块,用于以所述默认人物IP为形象,向用户输出所述回复信息。The information output module is configured to output the reply information to the user by using the default character IP as an image.
- 一种计算机可读存储介质,其上存储有计算机程序,其特征在于,该程序被处理器执行时实现权利要求1-7之一所述的方法。A computer readable storage medium having stored thereon a computer program, characterized in that the program, when executed by a processor, implements the method of any one of claims 1-7.
- 一种基于人物IP的人机交互设备,包括:存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序,其特征在于,所述处理器执行所述程序时实现权利要求1-7之一所述的方法。A human-computer interaction device based on a person IP, comprising: a memory, a processor, and a computer program stored on the memory and operable on the processor, wherein the processor executes the program when implementing the claim 1 -7 one of the methods described.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810286505.7 | 2018-03-30 | ||
CN201810286505 | 2018-03-30 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2019184103A1 true WO2019184103A1 (en) | 2019-10-03 |
Family
ID=64086586
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2018/091636 WO2019184103A1 (en) | 2018-03-30 | 2018-06-15 | Person ip-based human-computer interaction method and system, medium and device |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN108804698A (en) |
WO (1) | WO2019184103A1 (en) |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111177335A (en) * | 2019-11-29 | 2020-05-19 | 广东轩辕网络科技股份有限公司 | Intelligent assistant information processing method and device based on knowledge graph |
CN111737492A (en) * | 2020-06-23 | 2020-10-02 | 安徽大学 | Autonomous robot task planning method based on knowledge graph technology |
CN111737481A (en) * | 2019-10-10 | 2020-10-02 | 北京沃东天骏信息技术有限公司 | Noise reduction method, device and equipment of knowledge graph and storage medium |
CN112466307A (en) * | 2020-11-19 | 2021-03-09 | 珠海格力电器股份有限公司 | Voice reply method and device, storage medium and electronic device |
CN115840841A (en) * | 2023-02-01 | 2023-03-24 | 阿里巴巴达摩院(杭州)科技有限公司 | Multi-modal dialog method, device, equipment and storage medium |
CN116049425A (en) * | 2022-11-04 | 2023-05-02 | 合肥中科前沿科技有限公司 | Robot interaction method based on RCS architecture |
CN116627261A (en) * | 2023-07-25 | 2023-08-22 | 安徽淘云科技股份有限公司 | Interaction method, device, storage medium and electronic equipment |
US11875362B1 (en) | 2020-07-14 | 2024-01-16 | Cisco Technology, Inc. | Humanoid system for automated customer support |
US11907670B1 (en) | 2020-07-14 | 2024-02-20 | Cisco Technology, Inc. | Modeling communication data streams for multi-party conversations involving a humanoid |
US12118568B2 (en) | 2021-01-27 | 2024-10-15 | Cisco Technology, Inc. | Self-provisioning humanoid for automated customer support |
Families Citing this family (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109522399B (en) * | 2018-11-20 | 2022-08-12 | 北京京东尚科信息技术有限公司 | Method and apparatus for generating information |
CN110111795B (en) * | 2019-04-23 | 2021-08-27 | 维沃移动通信有限公司 | Voice processing method and terminal equipment |
CN110070370A (en) * | 2019-04-29 | 2019-07-30 | 上海智臻智能网络科技股份有限公司 | Pay a return visit providing method, device, computer equipment and the storage medium of service |
CN110532399A (en) * | 2019-08-07 | 2019-12-03 | 广州多益网络股份有限公司 | Knowledge mapping update method, system and the device of object game question answering system |
CN110674398A (en) * | 2019-09-05 | 2020-01-10 | 深圳追一科技有限公司 | Virtual character interaction method and device, terminal equipment and storage medium |
CN111159546B (en) * | 2019-12-24 | 2023-10-24 | 深圳市雅阅科技有限公司 | Event pushing method, event pushing device, computer readable storage medium and computer equipment |
CN111897864B (en) * | 2020-08-13 | 2021-04-20 | 创智和宇信息技术股份有限公司 | Expert database data extraction method and system based on Internet AI outbound |
CN112102840B (en) * | 2020-09-09 | 2024-05-03 | 中移(杭州)信息技术有限公司 | Semantic recognition method, semantic recognition device, terminal and storage medium |
CN112395399A (en) * | 2020-11-13 | 2021-02-23 | 四川大学 | Specific personality dialogue robot training method based on artificial intelligence |
CN114363277B (en) * | 2020-12-31 | 2023-08-01 | 万翼科技有限公司 | Intelligent chat method and device based on social relationship and related products |
CN114067033A (en) * | 2021-11-19 | 2022-02-18 | 云知声(上海)智能科技有限公司 | System and method for three-dimensional recording and human history restoration |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2004295766A (en) * | 2003-03-28 | 2004-10-21 | Sony Corp | Robot apparatus and user authentication method through robot |
CN103489210A (en) * | 2013-09-06 | 2014-01-01 | 雷路德 | Virtual character proactive contacting system and method thereof |
CN106297789A (en) * | 2016-08-19 | 2017-01-04 | 北京光年无限科技有限公司 | The personalized interaction method of intelligent robot and interactive system |
CN106503156A (en) * | 2016-10-24 | 2017-03-15 | 北京百度网讯科技有限公司 | Man-machine interaction method and device based on artificial intelligence |
CN107563517A (en) * | 2017-08-25 | 2018-01-09 | 深圳狗尾草智能科技有限公司 | Robot autognosis real time updating method and system |
Family Cites Families (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9805718B2 (en) * | 2013-04-19 | 2017-10-31 | Sri Internaitonal | Clarifying natural language input using targeted questions |
CN105068661B (en) * | 2015-09-07 | 2018-09-07 | 百度在线网络技术(北京)有限公司 | Man-machine interaction method based on artificial intelligence and system |
CN107589826B (en) * | 2016-07-07 | 2019-11-05 | 苏州狗尾草智能科技有限公司 | The man-machine interaction method and system of knowledge based map |
CN107589828A (en) * | 2016-07-07 | 2018-01-16 | 深圳狗尾草智能科技有限公司 | The man-machine interaction method and system of knowledge based collection of illustrative plates |
CN106202476B (en) * | 2016-07-14 | 2017-06-06 | 广州安望信息科技有限公司 | A kind of interactive method and device of knowledge based collection of illustrative plates |
WO2018045553A1 (en) * | 2016-09-09 | 2018-03-15 | 上海海知智能科技有限公司 | Man-machine interaction system and method |
CN107294837A (en) * | 2017-05-22 | 2017-10-24 | 北京光年无限科技有限公司 | Engaged in the dialogue interactive method and system using virtual robot |
CN107273477A (en) * | 2017-06-09 | 2017-10-20 | 北京光年无限科技有限公司 | A kind of man-machine interaction method and device for robot |
CN107340865B (en) * | 2017-06-29 | 2020-12-11 | 北京光年无限科技有限公司 | Multi-modal virtual robot interaction method and system |
CN107368572A (en) * | 2017-07-13 | 2017-11-21 | 张勇 | Multifunctional intellectual man-machine interaction method and system |
CN107797663A (en) * | 2017-10-26 | 2018-03-13 | 北京光年无限科技有限公司 | Multi-modal interaction processing method and system based on visual human |
-
2018
- 2018-06-15 CN CN201810623329.1A patent/CN108804698A/en active Pending
- 2018-06-15 WO PCT/CN2018/091636 patent/WO2019184103A1/en active Application Filing
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2004295766A (en) * | 2003-03-28 | 2004-10-21 | Sony Corp | Robot apparatus and user authentication method through robot |
CN103489210A (en) * | 2013-09-06 | 2014-01-01 | 雷路德 | Virtual character proactive contacting system and method thereof |
CN106297789A (en) * | 2016-08-19 | 2017-01-04 | 北京光年无限科技有限公司 | The personalized interaction method of intelligent robot and interactive system |
CN106503156A (en) * | 2016-10-24 | 2017-03-15 | 北京百度网讯科技有限公司 | Man-machine interaction method and device based on artificial intelligence |
CN107563517A (en) * | 2017-08-25 | 2018-01-09 | 深圳狗尾草智能科技有限公司 | Robot autognosis real time updating method and system |
Cited By (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111737481A (en) * | 2019-10-10 | 2020-10-02 | 北京沃东天骏信息技术有限公司 | Noise reduction method, device and equipment of knowledge graph and storage medium |
CN111737481B (en) * | 2019-10-10 | 2024-03-01 | 北京沃东天骏信息技术有限公司 | Method, device, equipment and storage medium for noise reduction of knowledge graph |
CN111177335A (en) * | 2019-11-29 | 2020-05-19 | 广东轩辕网络科技股份有限公司 | Intelligent assistant information processing method and device based on knowledge graph |
CN111177335B (en) * | 2019-11-29 | 2023-11-21 | 广东轩辕网络科技股份有限公司 | Knowledge graph-based intelligent assistant information processing method and device |
CN111737492B (en) * | 2020-06-23 | 2023-11-03 | 安徽大学 | Autonomous robot task planning method based on knowledge graph technology |
CN111737492A (en) * | 2020-06-23 | 2020-10-02 | 安徽大学 | Autonomous robot task planning method based on knowledge graph technology |
US11907670B1 (en) | 2020-07-14 | 2024-02-20 | Cisco Technology, Inc. | Modeling communication data streams for multi-party conversations involving a humanoid |
US11875362B1 (en) | 2020-07-14 | 2024-01-16 | Cisco Technology, Inc. | Humanoid system for automated customer support |
CN112466307A (en) * | 2020-11-19 | 2021-03-09 | 珠海格力电器股份有限公司 | Voice reply method and device, storage medium and electronic device |
CN112466307B (en) * | 2020-11-19 | 2023-09-26 | 珠海格力电器股份有限公司 | Voice replying method and device, storage medium and electronic device |
US12118568B2 (en) | 2021-01-27 | 2024-10-15 | Cisco Technology, Inc. | Self-provisioning humanoid for automated customer support |
CN116049425B (en) * | 2022-11-04 | 2023-09-22 | 合肥中科前沿科技有限公司 | Robot interaction method based on RCS architecture |
CN116049425A (en) * | 2022-11-04 | 2023-05-02 | 合肥中科前沿科技有限公司 | Robot interaction method based on RCS architecture |
CN115840841A (en) * | 2023-02-01 | 2023-03-24 | 阿里巴巴达摩院(杭州)科技有限公司 | Multi-modal dialog method, device, equipment and storage medium |
CN116627261A (en) * | 2023-07-25 | 2023-08-22 | 安徽淘云科技股份有限公司 | Interaction method, device, storage medium and electronic equipment |
Also Published As
Publication number | Publication date |
---|---|
CN108804698A (en) | 2018-11-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2019184103A1 (en) | Person ip-based human-computer interaction method and system, medium and device | |
CN112119454B (en) | Automatic assistant adapted to multiple age groups and/or vocabulary levels | |
US11823074B2 (en) | Intelligent communication manager and summarizer | |
CN109416816B (en) | Artificial intelligence system supporting communication | |
CN109844741B (en) | Generating responses in automated chat | |
KR102170563B1 (en) | Human machine interactive method and apparatus based on artificial intelligence | |
CN107944027B (en) | Method and system for creating semantic key index | |
JP6876752B2 (en) | Response method and equipment | |
JP2020071869A (en) | Video-based job provider and job seeker matching server and method | |
Ali et al. | Automatic text‐to‐gesture rule generation for embodied conversational agents | |
CN108470188B (en) | Interaction method based on image analysis and electronic equipment | |
CN116932733B (en) | Information recommendation method and related device based on large language model | |
Wilks et al. | A prototype for a conversational companion for reminiscing about images | |
CN113392273A (en) | Video playing method and device, computer equipment and storage medium | |
CN111046148A (en) | Intelligent interaction system and intelligent customer service robot | |
CN115577316A (en) | User personality prediction method based on multi-mode data fusion and application | |
CN113761156A (en) | Data processing method, device and medium for man-machine interaction conversation and electronic equipment | |
CN111553138B (en) | Auxiliary writing method and device for standardizing content structure document | |
CN108306813B (en) | Session message processing method, server and client | |
JP6697373B2 (en) | Sentence generating device, sentence generating method and program | |
Matsuyama et al. | Automatic expressive opinion sentence generation for enjoyable conversational systems | |
Gamborino et al. | Towards effective robot-assisted photo reminiscence: Personalizing interactions through visual understanding and inferring | |
CN113806620B (en) | Content recommendation method, device, system and storage medium | |
CN114449297A (en) | Multimedia information processing method, computing equipment and storage medium | |
JP2021043723A (en) | Information processing apparatus, information processing method, and program |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
32PN | Ep: public notification in the ep bulletin as address of the adressee cannot be established |
Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205 DATED 09/02/2021) |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 18912116 Country of ref document: EP Kind code of ref document: A1 |