CN112182185A - Intelligent client auxiliary processing method and system for power supply field - Google Patents
Intelligent client auxiliary processing method and system for power supply field Download PDFInfo
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Abstract
The invention provides an intelligent client processing method used in the field of power supply, which receives voice data containing a customer service request of a client through a power supply intelligent client system; carrying out voice recognition on received voice data of the client by an intelligent voice client service, and collecting client service requirements of the client through a preset knowledge question-answering or dialect template to form a client requirement table; giving a historical customer service record to the customer to obtain an updated customer request list; and sending the client request table to a manual customer service node, and providing the client service by the manual customer service based on the customer service request table. The invention also provides a corresponding system. By implementing the invention, the customer service requirement can be acquired through the conversation template, and the repetitive workload of manual customer service is reduced; meanwhile, the customer service pertinence can be improved according to the historical customer service records of the customers, so that the customer service efficiency and the use experience of the customers are improved.
Description
Technical Field
The invention relates to the technical field of power supply intelligent clients, in particular to an intelligent client processing method and system used in the field of power supply.
Background
For customer service work, intelligent voice is one of the trends of future development, although many power supply enterprises are actively building intelligent customer service systems, most of the existing voice navigation systems have some disadvantages, mainly embodied in the disadvantages of low intelligent degree, limited voice recognition effect, complex service flow, poor integrity, poor serviceability and the like;
meanwhile, for the existing customer service system, the manual customer service often needs to repeatedly inquire some key information, such as names, numbers, affairs and the like, and the process is complicated; therefore, the pertinence of the customer service is poor, and the customer service efficiency is low.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an intelligent client auxiliary processing method and system for the power supply field, which can receive and analyze a request form of a client in advance through an intelligent client system, and then can be served by an artificial customer service, so that the efficiency of the customer service can be improved.
In order to solve the above technical problem, an aspect of the present invention provides an intelligent client auxiliary processing method for the power supply field, which includes the following steps:
step S10, receiving voice data containing customer service request of customer through power supply intelligent customer system;
step S11, the intelligent voice customer service performs voice recognition to the received voice data of the customer, and collects the customer service requirement of the customer through a preset knowledge question-answering or talk template to form a customer requirement table;
step S12, analyzing according to the demand sheet to obtain the preliminary processing content and the historical customer service record of the customer to obtain the updated customer request sheet;
and step S13, sending the client request form to a manual customer service node, and providing the client service by the manual customer service based on the customer service request form.
Preferably, further comprising:
presetting a feedback mode and a service type corresponding to the identity of a client; setting a corresponding question-answer template or a corresponding dialect template for each service type; and presetting and storing a name of a person, a place name and a hot word related to the service.
Preferably, the step S11 further includes:
step S110, the identity of the client is determined according to the customer service request of the client, and a corresponding feedback mode is determined according to the identity of the client, wherein the feedback mode comprises the following steps: picture display, voice feedback, text feedback and short message feedback;
step S111, determining a corresponding service type according to a customer service request of a client, acquiring a question and answer template or a talk template preset by the service type, carrying out a dialogue with the client according to the dialogue template in a determined feedback mode, carrying out voice recognition on received voice data of the client by an intelligent voice customer service, and acquiring hotword information in the dialogue process with the client;
and step S112, collecting the customer service requirements of the customers according to the hotword information in the conversation process to form a customer requirement table.
Preferably, the step S12 further includes:
obtaining historical customer service information according to identity query of a current customer;
and combining the client demand table and the historical customer service information of the client to form a client request table of the current client.
Preferably, further comprising:
and receiving a correction request for the customer service request table from the artificial customer service node, and updating according to the data dialogue template of the correction request.
Accordingly, in another aspect of the present invention, there is also provided a smart client assistant processing system for use in the field of power supply, including:
the voice data receiving unit is used for receiving voice data containing customer service requests of customers through the power supply intelligent customer system;
the customer demand table generating unit is used for carrying out voice recognition on the received voice data of the customer by the intelligent voice customer service and collecting customer service demands of the customer through a preset knowledge question-answering or a preset talk template to form a customer demand table;
the client request table generating unit is used for analyzing according to the demand table, obtaining the primary processing content, and obtaining the historical customer service record of the client to obtain an updated client request table;
and the manual processing unit is used for sending the client request table to a manual customer service node, and the manual customer service provides the client service based on the customer service request table.
Preferably, further comprising:
the setting unit is used for presetting a feedback mode and a service type corresponding to the identity of the client; setting a corresponding question-answer template or a corresponding dialect template for each service type; and presetting and storing a name of a person, a place name and a hot word related to the service.
Preferably, the customer requirement table generating unit further comprises:
the identity recognition unit is used for determining the identity of the client according to the customer service request of the client and determining a corresponding feedback mode according to the identity of the client, wherein the feedback mode comprises the following steps: picture display, voice feedback, text feedback and short message feedback;
the service processing unit is used for determining a corresponding service type according to a customer service request of a client, acquiring a question-answer template or a talk template preset by the service type, carrying out a conversation with the client according to the conversation template in a determined feedback mode, carrying out voice recognition on received voice data of the client by the intelligent voice customer service, and acquiring hotword information in a conversation process with the client;
and the collection processing unit is used for collecting the customer service requirements of the customers according to the hotword information in the conversation process to form a customer requirement table.
Preferably, the client request table generating unit further includes:
the historical information obtaining unit is used for obtaining the historical customer service information according to the identity query of the current customer;
and the combination unit is used for combining the client demand table and the historical customer service information of the client to form a client request table of the current client.
Preferably, further comprising:
and the template adjusting unit is used for receiving a correction request of the customer service request table from the artificial customer service node and updating the data dialogue template according to the correction request.
The embodiment of the invention has the following beneficial effects:
the invention provides an intelligent client auxiliary processing method and system used in the field of power supply, wherein a power supply intelligent client system receives voice data of a client, which comprises a client service request; carrying out voice recognition on received voice data of the client by an intelligent voice client service, and collecting client service requirements of the client through a preset knowledge question-answering or dialect template to form a client requirement table; giving a historical customer service record to the customer to obtain an updated customer request list; and sending the client request table to a manual customer service node, and providing the client service by the manual customer service based on the customer service request table. By implementing the invention, the customer service requirement can be acquired through the conversation template, and the repetitive workload of manual customer service is reduced; meanwhile, the customer service pertinence can be improved according to the historical customer service records of the customers, so that the customer service efficiency and the use experience of the customers are improved.
Drawings
Fig. 1 is a main flow diagram of an embodiment of an intelligent auxiliary customer handling method for the power supply field according to the present invention;
FIG. 2 is a more detailed flowchart of step S11 of FIG. 1;
FIG. 3 is a schematic diagram of an embodiment of an intelligent auxiliary client processing system for the field of power supply according to the present invention;
FIG. 4 is a schematic structural diagram of a client requirement table generating unit in FIG. 3;
fig. 5 is a structural diagram of the client request table generating unit in fig. 3.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The invention provides an intelligent client auxiliary processing method and system for the power supply field, which are characterized in that an intelligent voice client service model is correspondingly constructed according to each service system, when client service request voice data sent by a client is received, a client service auxiliary platform performs voice recognition on the received voice data of the client and performs natural language processing, client service requirements of the client are collected through a preset knowledge question-answering or conversation template, meanwhile, the collected client service requirements are analyzed based on client service analysis strategies of each service system, so that the client service requirements of the client are recombined through natural language, corresponding processing references are given, and then manual client service is given to assist the manual client service to provide accurate and efficient client service. The customer service auxiliary platform is mainly used for communicating and interacting with customers, collecting customer service requirements of the customers and forwarding the customer service requirements to corresponding manual customer service nodes for processing.
For those skilled in the art to more clearly understand the objects, technical solutions and advantages of the present invention, the following description will be further provided in conjunction with the accompanying drawings and examples.
Fig. 1 is a schematic structural diagram illustrating an embodiment of a smart client assistant processing method for the field of power supply according to the present invention. Referring to fig. 2, in this embodiment, the method includes the following steps:
step S10, receiving voice data containing customer service request of customer through power supply intelligent customer system;
step S11, the intelligent voice customer service performs voice recognition to the received voice data of the customer, and collects the customer service requirement of the customer through a preset knowledge question-answering or talk template to form a customer requirement table;
specifically, in one embodiment, the step S11 further includes:
step S110, the identity of the client is determined according to the customer service request of the client, and a corresponding feedback mode is determined according to the identity of the client, wherein the feedback mode comprises the following steps: picture display, voice feedback, text feedback and short message feedback; specifically, the identity of the client can be determined by the user identification carried in the client request; the feedback mode can be determined according to the historical feedback mode of the client, or can be determined according to the client information and the selection of the client.
Step S111, determining a corresponding service type according to a customer service request of a client, acquiring a question and answer template or a talk template preset by the service type, carrying out a dialogue with the client according to the dialogue template in a determined feedback mode, carrying out voice recognition on received voice data of the client by an intelligent voice customer service, and acquiring hotword information in the dialogue process with the client;
and step S112, collecting the customer service requirements of the customers according to the hotword information in the conversation process to form a customer requirement table. Specifically, the client requirements are determined according to the communication content of the customer service and the clients; for example, if power is cut off, power needs to be supplied; arrears, needs to pay, etc.; the customer requirement table can record the reason of the customer initiating the voice customer service request, namely the problem of the customer.
Step S12, analyzing according to the demand sheet to obtain the preliminary processing content and the historical customer service record of the customer to obtain the updated customer request sheet;
in a specific example, the step S12 further includes:
step S120, obtaining historical customer service information according to the identity query of the current customer;
and step S11, combining the client requirement table and the historical customer service information of the client to form a client request table of the current client.
And step S13, sending the client request form to a manual customer service node, and providing the client service by the manual customer service based on the customer service request form.
It is understood that, in the embodiment of the present invention, further comprising:
presetting a feedback mode and a service type corresponding to the identity of a client; setting a corresponding question-answer template or a corresponding dialect template for each service type; and presetting and storing a name of a person, a place name and a hot word related to the service.
In a specific example, the method may further include:
and receiving a correction request for the customer service request table from the artificial customer service node, and updating according to the data dialogue template of the correction request.
It will be appreciated that for automatically derived request forms, adjustments are initiated manually, such as adjustment expressions, adjustment problem descriptions, and the like; the manual adjustment record can generate corresponding correction data, and the correction data can further update the dialoging template to update the dialoging template, so that the effectiveness of the dialoging template is improved.
It can be understood that, in step S11 of the present invention, when performing speech recognition on the speech data of the client, the time period in which both sides of the speech are silent can be accurately located through noise recognition and noise removal, and the corresponding start-stop time is given. The method is started from multiple angles through voiceprint features and semantic understanding, identifies abnormal emotional positions (such as tone, intonation, speed of speech and the like) in the conversation process, and can accurately position sentence contents and related personnel at the positions where the abnormal emotional positions occur. Providing a hotword configuration interface: according to the development of the service, the client configures the name of a person, the name of a place and the special hot words of the service through the interface, and the recognition effect of the hot words is improved. And providing a learning function of the service field text: the client can import the text data in the service field, and the recognition effect of the text is improved on the whole. Providing a hotword configuration interface: according to the development of the service, the client configures the name of a person, the name of a place and the special hot words of the service through the interface, and the recognition effect of the hot words is improved. Providing a text learning function: and the client imports the text data in the business field, and the system learns to improve the recognition effect on the whole.
Fig. 3 is a schematic structural diagram illustrating an embodiment of a smart client auxiliary processing system for the field of power supply according to the present invention. Referring to fig. 4 to 5 together, in this embodiment, the intelligent client auxiliary processing system 1 for the power supply domain includes:
a voice data receiving unit 10, configured to receive voice data of a customer including a customer service request through a power supply smart client system;
the client requirement table generating unit 11 is used for performing voice recognition on the received voice data of the client by the intelligent voice client service, and collecting the client service requirements of the client through a preset knowledge question-answer or a preset talk template to form a client requirement table;
the client request table generating unit 12 is configured to analyze the request table to obtain a preliminary processing content, and obtain a historical customer service record of the client to obtain an updated client request table;
and the manual processing unit 13 is configured to send the client request form to a manual customer service node, and the manual customer service provides a customer service based on the customer service request form.
A setting unit 15, configured to preset a feedback mode and a service type corresponding to an identity of a client; setting a corresponding question-answer template or a corresponding dialect template for each service type; and presetting and storing a name of a person, a place name and a hot word related to the service.
More specifically, the customer requirement table generating unit 11 further includes:
the identity recognition unit 110 is configured to determine an identity of a client according to a customer service request of the client, and determine a corresponding feedback manner according to the identity of the client, where the feedback manner includes: picture display, voice feedback, text feedback and short message feedback;
the service processing unit 111 is used for determining a corresponding service type according to a customer service request of a customer, acquiring a question and answer template or a dialogue template preset by the service type, carrying out dialogue with the customer according to the dialogue template in a determined feedback mode, carrying out voice recognition on received voice data of the customer by the intelligent voice customer service, and acquiring hotword information in the dialogue process with the customer;
and the collection processing unit 112 is used for collecting the customer service requirements of the customers according to the hotword information in the conversation process to form a customer requirement table.
More specifically, the client request table generating unit 12 further includes:
a history information obtaining unit 120, configured to obtain history customer service information according to identity query of a current customer;
the combining unit 121 is configured to combine the customer requirement table and the historical customer service information of the customer to form a customer request table of the current customer.
More specifically, the present system further comprises:
and the template adjusting unit 15 is used for receiving a correction request of the customer service request table from the artificial customer service node and updating the data dialogue template according to the correction request.
For more, reference may be made to the foregoing description of fig. 1 and fig. 2, which is not repeated herein.
The embodiment of the invention has the following beneficial effects:
the invention provides an intelligent client auxiliary processing method and system used in the field of power supply, wherein a power supply intelligent client system receives voice data of a client, which comprises a client service request; carrying out voice recognition on received voice data of the client by an intelligent voice client service, and collecting client service requirements of the client through a preset knowledge question-answering or dialect template to form a client requirement table; giving a historical customer service record to the customer to obtain an updated customer request list; and sending the client request table to a manual customer service node, and providing the client service by the manual customer service based on the customer service request table. By implementing the invention, the customer service requirement can be acquired through the conversation template, and the repetitive workload of manual customer service is reduced; meanwhile, the customer service pertinence can be improved according to the historical customer service records of the customers, so that the customer service efficiency and the use experience of the customers are improved.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (10)
1. An intelligent client auxiliary processing method for the power supply field is characterized by comprising the following steps:
step S10, receiving voice data containing customer service request of customer through power supply intelligent customer system;
step S11, the intelligent voice customer service performs voice recognition to the received voice data of the customer, and collects the customer service requirement of the customer through a preset knowledge question-answering or talk template to form a customer requirement table;
step S12, analyzing according to the demand sheet to obtain the preliminary processing content and the historical customer service record of the customer to obtain the updated customer request sheet;
and step S13, sending the client request form to a manual customer service node, and providing the client service by the manual customer service based on the customer service request form.
2. The method of claim 1, further comprising:
presetting a feedback mode and a service type corresponding to the identity of a client; setting a corresponding question-answer template or a corresponding dialect template for each service type; and presetting and storing a name of a person, a place name and a hot word related to the service.
3. The method of claim 2, wherein the step S11 further comprises:
step S110, the identity of the client is determined according to the customer service request of the client, and a corresponding feedback mode is determined according to the identity of the client, wherein the feedback mode comprises the following steps: picture display, voice feedback, text feedback and short message feedback;
step S111, determining a corresponding service type according to a customer service request of a client, acquiring a question and answer template or a talk template preset by the service type, carrying out a dialogue with the client according to the dialogue template in a determined feedback mode, carrying out voice recognition on received voice data of the client by an intelligent voice customer service, and acquiring hotword information in the dialogue process with the client;
and step S112, collecting the customer service requirements of the customers according to the hotword information in the conversation process to form a customer requirement table.
4. The method of claim 3, wherein the step S12 further comprises:
obtaining historical customer service information according to identity query of a current customer;
and combining the client demand table and the historical customer service information of the client to form a client request table of the current client.
5. The method of claim 4, further comprising:
and receiving a correction request for the customer service request table from the artificial customer service node, and updating according to the data dialogue template of the correction request.
6. A smart client auxiliary processing system for the field of power supply, comprising:
the voice data receiving unit is used for receiving voice data containing customer service requests of customers through the power supply intelligent customer system;
the customer demand table generating unit is used for carrying out voice recognition on the received voice data of the customer by the intelligent voice customer service and collecting customer service demands of the customer through a preset knowledge question-answering or a preset talk template to form a customer demand table;
the client request table generating unit is used for analyzing according to the demand table, obtaining the primary processing content, and obtaining the historical customer service record of the client to obtain an updated client request table;
and the manual processing unit is used for sending the client request table to a manual customer service node, and the manual customer service provides the client service based on the customer service request table.
7. The system of claim 6, further comprising:
the setting unit is used for presetting a feedback mode and a service type corresponding to the identity of the client; setting a corresponding question-answer template or a corresponding dialect template for each service type; and presetting and storing a name of a person, a place name and a hot word related to the service.
8. The system of claim 7, wherein the customer requirements table generation unit further comprises:
the identity recognition unit is used for determining the identity of the client according to the customer service request of the client and determining a corresponding feedback mode according to the identity of the client, wherein the feedback mode comprises the following steps: picture display, voice feedback, text feedback and short message feedback;
the service processing unit is used for determining a corresponding service type according to a customer service request of a client, acquiring a question-answer template or a talk template preset by the service type, carrying out a conversation with the client according to the conversation template in a determined feedback mode, carrying out voice recognition on received voice data of the client by the intelligent voice customer service, and acquiring hotword information in a conversation process with the client;
and the collection processing unit is used for collecting the customer service requirements of the customers according to the hotword information in the conversation process to form a customer requirement table.
9. The system of claim 8, wherein the client request table generating unit further comprises:
the historical information obtaining unit is used for obtaining the historical customer service information according to the identity query of the current customer;
and the combination unit is used for combining the client demand table and the historical customer service information of the client to form a client request table of the current client.
10. The system of claim 9, further comprising:
and the template adjusting unit is used for receiving a correction request of the customer service request table from the artificial customer service node and updating the data dialogue template according to the correction request.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112925898A (en) * | 2021-04-13 | 2021-06-08 | 平安科技（深圳）有限公司 | Question-answering method, device, server and storage medium based on artificial intelligence |
| CN115086283A (en) * | 2022-05-18 | 2022-09-20 | 阿里巴巴（中国）有限公司 | Voice stream processing method and unit |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170068976A1 (en) * | 2015-09-09 | 2017-03-09 | Hartford Fire Insurance Company | System using automatically triggered analytics for feedback data |
| CN107451274A (en) * | 2017-08-04 | 2017-12-08 | 百度在线网络技术（北京）有限公司 | Aid in method for pushing, device, equipment and the storage medium of customer service information |
| CN110060083A (en) * | 2019-01-21 | 2019-07-26 | 阿里巴巴集团控股有限公司 | The personalization method, apparatus and equipment to be serviced such as busy based on machine learning |
| CN111246031A (en) * | 2020-02-27 | 2020-06-05 | 大连即时智能科技有限公司 | Man-machine cooperative telephone customer service method and system |
-
2020
- 2020-09-30 CN CN202011064228.9A patent/CN112182185A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170068976A1 (en) * | 2015-09-09 | 2017-03-09 | Hartford Fire Insurance Company | System using automatically triggered analytics for feedback data |
| CN107451274A (en) * | 2017-08-04 | 2017-12-08 | 百度在线网络技术（北京）有限公司 | Aid in method for pushing, device, equipment and the storage medium of customer service information |
| CN110060083A (en) * | 2019-01-21 | 2019-07-26 | 阿里巴巴集团控股有限公司 | The personalization method, apparatus and equipment to be serviced such as busy based on machine learning |
| CN111246031A (en) * | 2020-02-27 | 2020-06-05 | 大连即时智能科技有限公司 | Man-machine cooperative telephone customer service method and system |
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| CN112925898B (en) * | 2021-04-13 | 2023-07-18 | 平安科技（深圳）有限公司 | Question-answering method and device based on artificial intelligence, server and storage medium |
| CN115086283A (en) * | 2022-05-18 | 2022-09-20 | 阿里巴巴（中国）有限公司 | Voice stream processing method and unit |
| CN115086283B (en) * | 2022-05-18 | 2024-02-06 | 阿里巴巴（中国）有限公司 | Voice stream processing method and device |
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