CN116049375B - Intelligent customer service response system based on AIGC - Google Patents
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Abstract
The invention discloses an AIGC-based intelligent customer service response system, which extracts demand characteristics from user demand information, converts the demand characteristics into demand images, determines response images according to the demand images, and determines response information according to the response images, so that various types of user demand information in a use scene can be represented by the demand images, normalization processing of the user demand information is facilitated, and applicability to use scenes in which interaction information comprises various information types is achieved.
Description
Technical Field
The invention relates to the technical field of intelligent equipment, in particular to an AIGC-based intelligent customer service response system.
Background
Patent CN106601237B discloses a speech recognition method for an interactive speech response system comprising a knowledge base comprising a set of knowledge points, the speech recognition method comprising obtaining a speech training corpus based on the set of knowledge points in the knowledge base; training a language model using the obtained speech training corpus; and using the language model to identify a user's speech input.
Patent CN111510564a discloses a data processing method, device and medium based on interactive voice response system. The method comprises the following steps: receiving an incoming message carrying a target session identifier, the incoming message being generated by an interactive voice response system based on input information of a target calling object; determining a monitoring time period based on a receiving time point corresponding to the incoming message; acquiring a plurality of agent connection messages corresponding to the monitoring time period, wherein each agent connection message carries a corresponding session identifier; when the agent connection messages indicating the target session identifier do not exist in the agent connection messages, acquiring target guiding strategy information according to the incoming call message; and returning response information to the target calling object based on the target guiding strategy information.
However, the response system related to the above technical solution is mainly directed to the interactive scenario of the voice information. In daily life, when people communicate online, the interactive information includes the types of expression packages (image information), text information and voice information. Then, the information types of the usage scenario aimed by the response system in the above technical solution are relatively single, which is not beneficial to optimizing the user experience of the response system.
Therefore, how to design a response system that is beneficial to multiple information types in a specific usage scenario is a technical problem that needs to be solved.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an AIGC-based intelligent customer service response system which is beneficial to aiming at various information types in a use scene.
In order to solve the technical problems, the invention discloses an intelligent customer service response system based on AIGC, which comprises a user demand information receiving end, a response information output end, a controller and a data platform, wherein the user demand information receiving end and the response information output end are respectively and electrically connected with the controller, the controller is in communication connection with the data platform based on public network,
the steps executed by the controller include:
the controller acquires user demand information input through the user demand information receiving end;
the controller extracts demand characteristics from the user demand information and converts the demand characteristics into demand images;
the controller transmits the required image to a data platform, so that the data platform screens out a corresponding response image from a response database;
the controller generates response information matched with the user demand information according to the response image;
and the controller controls the response information output end to output the response information.
According to the intelligent customer service response system based on the AIGC disclosed by the invention, the demand characteristics are extracted from the user demand information, the demand characteristics are converted into the demand images, the response images are determined according to the demand images, and then the response information is determined according to the response images, so that various types of user demand information in a use scene can be represented by the demand images, normalization processing of the user demand information is facilitated, and applicability to use scenes in which interaction information comprises various information types is achieved.
As an optional implementation manner, in the present invention, after the controller extracts a demand feature from the user demand information and converts the demand feature into a demand image, and before the controller transmits the demand image to a data platform, so that the data platform screens a corresponding response image from a response database, the step performed by the controller further includes:
the controller determines whether the user demand information matches the history demand information from the history information demand list based on the demand image,
if yes, the controller retrieves and executes a target work task corresponding to the history demand information from the history task, generates response information matched with the user demand information, controls the response information output end to output the response information,
if not, triggering the controller to transmit the required image to a data platform, so that the data platform screens out the corresponding response image from the response database.
As an optional implementation manner, in the present invention, the controller extracts a demand feature from the user demand information, and converts the demand feature into a demand image, and specifically includes:
the controller divides the user demand information into a plurality of unit demand information, and indicates the user demand information as follows by the unit demand information:
wherein X represents a user demand information quantization matrix,
representing the number of unit demand information +.>
A unit demand information quantization value included in the user demand information;
the controller inputs the unit demand information to a pre-trained feature extractor to generate unit demand features, and the unit demand features are represented as follows:
wherein Y represents a demand feature matrix,
the number of categories representing unit demand characteristics, +.>
Representing unit demand feature values contained in the demand feature matrix;
the controller constructs a demand image with a unit demand characteristic value as an ordinate and a unit demand information quantized value as an abscissa, as follows:
wherein ,
representing a demand image +.>
The pixel point of the required image F;
and after the controller transmits the demand image to a data platform, the data platform performs the following steps:
the data platform screens out target priori demand images matched with the demand images from a priori demand image database;
the data platform screens out response images corresponding to the target priori demand images from the response database;
the process of screening the target priori demand image matched with the demand image from the priori demand image database by the data platform specifically comprises the following steps:
the data platform obtains the matching degree of the demand image and the prior demand image in the prior demand image database, and the matching degree is as follows:
in the formula ,
representing the degree of matching of said demand image with a certain a priori demand image in a priori demand image database,/->
、/>
Mean value of coordinate values respectively representing abscissa and ordinate of pixel points of the required image,/->
、/>
Separate tableStandard deviation of coordinate values showing abscissa and ordinate of pixel points of the desired image,/->
、/>
Mean value of coordinate values respectively representing abscissa and ordinate of pixel points of the prior demand image,/->
、/>
Standard deviation of coordinate values of abscissa and ordinate of pixel points respectively representing the prior demand image,/->
For a predetermined correction factor, +.>
、/>
、/>
and />
Is a predetermined bias constant;
and the data platform screens out the priori demand image with the matching degree P closest to 1 from the priori demand image database and marks the priori demand image as a target priori demand image.
As an optional implementation manner, in the present invention, the types of the user requirement information include: one or more of image, text, and voice;
and/or, the type of the response information comprises: one or more of image, text, and voice.
In an alternative embodiment, the response database includes a response image database and a priori demand image database,
and the response image in the response image database and the prior demand image in the prior demand image database form a mapping relation.
As an alternative embodiment, the required features include one or more of image brightness features, image contrast features, image texture features, text content features, text expressed emotion features, voice volume features and voice audio features in the user required information.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an AIGC-based intelligent customer service response system in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of a portion of the steps performed by the controller according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of another part of the steps performed by the controller according to the embodiment of the present invention;
FIG. 4 is a schematic diagram of a demand image according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or elements but may, in the alternative, include other steps or elements not expressly listed or inherent to such process, method, article, or device.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
AIGC (artificial intelligence generated content, artificial Intelligence Generated Content, abbreviated as AIGC) is expected to be a new engine for innovation and development of digital content, and the advantages mainly include: 1) The AIGC can bear basic mechanical labor such as information mining, material calling, re-engraving editing and the like at a manufacturing capacity and knowledge level superior to those of human beings, and can meet mass personalized requirements in a low marginal cost and high-efficiency manner from the technical level; 2) AIGC can inoculate a new business state new mode by supporting multidimensional interaction, fusion and permeation of digital content and other industries; 3) The development of the "meta universe" is assisted, and the physical world is accelerated and repeated through AIGC to carry out infinite content creation, so that spontaneous organic growth is realized.
The invention discloses an AIGC-based intelligent customer service response system, which comprises a user demand information receiving end, a response information output end, a controller and a data platform, wherein the user demand information receiving end and the response information output end are respectively and electrically connected with the controller, and the controller is connected with the data platform based on public network communication. Wherein, as shown in fig. 2, the steps executed by the controller include:
s101, the controller acquires user demand information input through a user demand information receiving end.
S102, the controller extracts the demand characteristics from the user demand information and converts the demand characteristics into demand images.
And S103, the controller transmits the required image to the data platform, so that the data platform screens out the corresponding response image from the response database.
And S104, the controller generates response information matched with the user demand information according to the response image.
S105, the controller controls the response information output end to output response information.
According to the intelligent customer service response system based on the AIGC disclosed by the invention, the demand characteristics are extracted from the user demand information, the demand characteristics are converted into the demand images, the response images are determined according to the demand images, and then the response information is determined according to the response images, so that various types of user demand information in a use scene can be represented by the demand images, normalization processing of the user demand information is facilitated, and applicability to use scenes in which interaction information comprises various information types is achieved.
For response information which is made according to certain user demand information before, the intelligent customer service response system can carry out simplified processing, namely, the controller does not need to execute operation of extracting demand characteristics again for the user demand information to convert the demand characteristics into demand images, and the data platform does not need to screen operation of corresponding response images from a response database again, so that the task processing efficiency of the intelligent customer service response system is improved. Optionally, after step S101 and before step S103, as shown in fig. 3, the steps executed by the controller further include:
s102a, the controller judges whether the user demand information is matched with the history demand information in the history information demand list according to the demand image, if so, the step S103a is executed, and if not, the step S103 is executed.
S103a, the controller retrieves and executes a target work task corresponding to the historical demand information from the historical task, generates response information matched with the user demand information, and controls the response information output end to output the response information.
And S103, the controller transmits the required image to the data platform, so that the data platform screens out the corresponding response image from the response database.
In the intelligent customer service response system disclosed by the invention, the controller converts the user demand information into the demand image, the demand image is used as transmission information, the information intercommunication is realized with the data platform, the response image is obtained from the data platform and used as feedback information, and then the response information matched with the user demand information is finally determined according to the response image. The process of determining the demand image by the controller according to the user demand information and the process of determining the response information by the data platform according to the demand image have important influence on the operation of the intelligent customer service response system. In order to achieve the high efficiency of the controller to determine the demand image according to the user demand information, optionally, the specific process of the controller to extract the demand feature from the user demand information and to convert the demand feature into the demand image may be as follows:
1) The controller divides the user demand information into a plurality of unit demand information, and the unit demand information is used for representing the user demand information as follows:
wherein X represents a user demand information quantization matrix,
representing the number of unit demand information +.>
A unit demand information quantization value included in the user demand information;
2) The controller inputs the unit demand information to the pre-trained feature extractor to generate unit demand features, and the unit demand features are used to represent the demand features as follows:
wherein Y representsThe feature matrix is required to be a function of the feature matrix,
the number of categories representing unit demand characteristics, +.>
Representing unit demand feature values contained in the demand feature matrix;
3) As shown in fig. 4, the controller constructs a demand image with a unit demand characteristic value as an ordinate and a unit demand information quantized value as an abscissa, as follows:
wherein ,
representing a demand image +.>
Is the pixel point of the demand image F.
And in order to realize the high efficiency of determining the response information by the data platform according to the requirement image, further optionally, after the controller transmits the requirement image to the data platform, the data platform executes the following steps:
the data platform screens out target priori demand images matched with the demand images from the priori demand image database;
and the data platform screens out response images corresponding to the target priori demand images from the response database.
From a further alternative, the process of screening the target prior demand image matched with the demand image from the prior demand image database by the data platform specifically includes:
the data platform obtains the matching degree of the demand image and the prior demand image in the prior demand image database, and the matching degree is as follows:
in the formula ,
representing the degree of matching of the demand image with a certain a priori demand image in the a priori demand image database,
、/>
mean value of coordinate values of horizontal coordinate and vertical coordinate of pixel points respectively representing required images, ++>
、/>
Standard deviation of coordinate values of horizontal coordinate and vertical coordinate of pixel points respectively representing required images, +.>
、/>
Mean value of coordinate values respectively representing abscissa and ordinate of pixel points of the prior demand image,/->
、/>
Standard deviation of coordinate values of abscissa and ordinate of pixel points respectively representing the prior demand image,/->
For a predetermined correction factor (in particular, < >>
），/>
、/>
、/>
and />
For a predetermined bias constant (in particular, < ->
、/>
、/>
and />
Greater than 0);
the data platform screens the priori demand image with the matching degree P closest to 1 from the priori demand image database, and marks the priori demand image as a target priori demand image.
Still further alternatively, the type of the user demand information may be various, for example, may be one or a combination of plural kinds of images, characters, and voices; accordingly, the types of the response information may also be various, for example, may be one or a combination of a plurality of images, characters, and voices.
Still further alternatively, the response database includes a response image database and a priori demand image database,
and the response image in the response image database and the priori demand image in the priori demand image database form a mapping relation. In particular, the AIGC technology can be applied to the data volume expansion aspect of the response database, so that the comprehensiveness of the intelligent customer service response system in the aspect of responding to the user demand information is improved.
Still further alternatively, the operation of inputting the unit demand information from the controller to the pre-trained feature extractor to generate the unit demand feature may be based on a pre-trained deep convolutional neural network (in particular, the feature extractor includes a number of convolutional layers). When the user demand information is image information, the extracted features can be image brightness features, image contrast features, image texture features and the like; when the user demand information is text information, the extracted features can be text content features and emotion features expressed by the text; when the user demand information is voice information, the extracted voice volume feature, voice audio feature and the like can be extracted. The user demand information may then include one or more of image information, text information, and voice information, and accordingly the extracted features may be a combination of one or more of the above.
Finally, it should be noted that: in the intelligent customer service response system based on the AIGC disclosed by the embodiment of the invention, the disclosure is only a preferred embodiment of the invention, and is only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme described in the foregoing embodiments can be modified or some of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (4)
1. The intelligent customer service response system based on AIGC is characterized by comprising a user demand information receiving end, a response information output end, a controller and a data platform, wherein the user demand information receiving end and the response information output end are respectively and electrically connected with the controller, the controller is in communication connection with the data platform based on a public network,
the steps executed by the controller include:
the controller acquires user demand information input through the user demand information receiving end;
the controller extracts demand characteristics from the user demand information and converts the demand characteristics into demand images;
the controller transmits the required image to a data platform, so that the data platform screens out a corresponding response image from a response database;
the controller generates response information matched with the user demand information according to the response image;
the controller controls the response information output end to output the response information;
after the controller extracts the demand features from the user demand information and converts the demand features into demand images, and before the controller transmits the demand images to a data platform, so that the data platform screens corresponding response images from a response database, the steps executed by the controller further include:
the controller determines whether the user demand information matches the history demand information from the history information demand list based on the demand image,
if yes, the controller retrieves and executes a target work task corresponding to the history demand information from the history task, generates response information matched with the user demand information, controls the response information output end to output the response information,
if not, triggering the controller to transmit the required image to a data platform, so that the data platform screens out the corresponding response image from a response database to execute the step;
the controller extracts demand characteristics from the user demand information and converts the demand characteristics into demand images, and the method specifically comprises the following steps:
the controller divides the user demand information into a plurality of unit demand information, and indicates the user demand information as follows by the unit demand information:
wherein X represents a user demand information quantization matrix,
representing the number of unit demand information +.>
A unit demand information quantization value included in the user demand information;
the controller inputs the unit demand information to a pre-trained feature extractor to generate unit demand features, and the unit demand features are represented as follows:
wherein Y represents a demand feature matrix,
the number of categories representing unit demand characteristics, +.>
Representing unit demand feature values contained in the demand feature matrix;
the controller constructs a demand image with a unit demand characteristic value as an ordinate and a unit demand information quantized value as an abscissa, as follows:
wherein ,
representing a demand image +.>
The pixel point of the required image F;
and after the controller transmits the demand image to a data platform, the data platform performs the following steps:
the data platform screens out target priori demand images matched with the demand images from a priori demand image database;
the data platform screens out response images corresponding to the target priori demand images from the response database;
the process of screening the target priori demand image matched with the demand image from the priori demand image database by the data platform specifically comprises the following steps:
the data platform obtains the matching degree of the demand image and the prior demand image in the prior demand image database, and the matching degree is as follows:
in the formula ,
representing the degree of matching of said demand image with a certain a priori demand image in a priori demand image database,/->
、/>
Mean value of coordinate values respectively representing abscissa and ordinate of pixel points of the required image,/->
、/>
Standard deviation of coordinate values respectively representing abscissa and ordinate of pixel points of the required image,/->
、/>
Representing the a priori demanded images respectivelyMean value of coordinate values of abscissa and ordinate of pixel point,/->
、/>
Standard deviation of coordinate values of abscissa and ordinate of pixel points respectively representing the prior demand image,/->
For a predetermined correction factor, +.>
、/>
、/>
and />
Is a predetermined bias constant;
and the data platform screens out the priori demand image with the matching degree P closest to 1 from the priori demand image database and marks the priori demand image as a target priori demand image.
2. The AIGC-based intelligent customer service response system of claim 1, wherein the types of user demand information include: one or more of image, text, and voice;
and/or, the type of the response information comprises: one or more of image, text, and voice.
3. The AIGC-based intelligent customer service response system of claim 2, wherein the response database includes a response image database and a priori demand image database,
and the response image in the response image database and the prior demand image in the prior demand image database form a mapping relation.
4. The AIGC-based intelligent customer service response system according to claim 3, wherein the demand features include one or more of image brightness features, image contrast features, image texture features, text content features, text expressed emotion features, voice volume features, and voice audio features in the user demand information.
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| WO2021164618A1 (en) * | 2020-02-17 | 2021-08-26 | 京东方科技集团股份有限公司 | Knowledge graph-based question answering method and apparatus, computer device, and medium |
| CN113205507A (en) * | 2021-05-18 | 2021-08-03 | 合肥工业大学 | Visual question answering method, system and server |
| CN115203393A (en) * | 2022-07-21 | 2022-10-18 | 中国平安人寿保险股份有限公司 | Dialogue response method and system, electronic equipment and storage medium |
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