CN113705224A - Voice recognition scheduling service voice interaction method and system - Google Patents
Voice recognition scheduling service voice interaction method and system Download PDFInfo
- Publication number
- CN113705224A CN113705224A CN202111040094.1A CN202111040094A CN113705224A CN 113705224 A CN113705224 A CN 113705224A CN 202111040094 A CN202111040094 A CN 202111040094A CN 113705224 A CN113705224 A CN 113705224A
- Authority
- CN
- China
- Prior art keywords
- scheduling service
- voice
- information
- scheduling
- ticket
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 32
- 230000003993 interaction Effects 0.000 title claims abstract description 29
- 238000004422 calculation algorithm Methods 0.000 claims description 14
- 238000013473 artificial intelligence Methods 0.000 claims description 11
- 238000013145 classification model Methods 0.000 claims description 6
- 230000011218 segmentation Effects 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 230000002452 interceptive effect Effects 0.000 claims 2
- 238000011084 recovery Methods 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000003672 processing method Methods 0.000 description 4
- 238000004590 computer program Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 235000019800 disodium phosphate Nutrition 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/26—Speech to text systems
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Human Computer Interaction (AREA)
- Acoustics & Sound (AREA)
- Multimedia (AREA)
- Telephonic Communication Services (AREA)
Abstract
The invention provides a voice interaction method and a system for scheduling service of voice recognition, wherein the method comprises the following steps: receiving scheduling service voice information, and converting the scheduling service voice information into semantic information; executing corresponding scheduling service according to the semantic information and generating a scheduling service processing result; and carrying out voice broadcast on the scheduling service processing result. The method automatically draws an operation ticket and performs comprehensive check according to the voice information of the dispatcher, replaces manual operation ticket writing, and directly verifies the written operation ticket which is subjected to comprehensive check without manually writing the operation ticket, thereby reducing the workload of the dispatcher, improving the efficiency and safety of dispatching operation, and solving the technical problems that the operation service of the current power grid is increased sharply, and the relevant power failure and recovery conditions need to be verified and confirmed by a large amount of manual work of the dispatcher before and after operation, so that the efficiency of dispatching operation and the operation safety of the power grid are influenced.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a voice interaction method and system for scheduling services through voice recognition.
Background
With the continuous expansion of the scale of the power grid and the power transmission scale, the system has various operation modes and complex characteristics, various power grid risk points are increased day by day, and the operation amount and the control difficulty of the power grid are increased continuously. The traditional scheduling service mode is used for processing scheduling services under new situations, and great challenges are faced to operation efficiency and operation safety. The low operating efficiency results in long equipment power failure time, influences the electric wire netting safety, reduces the power supply reliability and then increases user power failure time, and customer satisfaction and power consumption experience receive very big influence. In order to prevent misoperation, various countermeasures and safety measures added by management units at all levels influence and restrict the operation efficiency.
Disclosure of Invention
The invention provides a voice recognition scheduling service voice interaction method and system, which improve the operation efficiency and safety of a power grid, accelerate the fusion application of advanced technologies such as artificial intelligence and the like in scheduling operation services, and construct an intelligent scheduling application power system.
The first aspect of the present invention provides a voice interaction method for scheduling services by voice recognition, including:
receiving scheduling service voice information, and converting the scheduling service voice information into semantic information;
executing corresponding scheduling service according to the semantic information and generating a scheduling service processing result;
and carrying out voice broadcast on the scheduling service processing result.
Further, the converting the scheduling service voice information into semantic information includes:
converting the scheduling service voice information into text information through voice recognition;
segmenting the text information through a segmentation tool, and deleting stop words in the segmented words through a stop table to obtain filtered text information;
calculating the similarity between the filtered text information and the scheduling service in the scheduling service classification model by a cosine similarity algorithm;
and taking the scheduling service with the highest similarity as semantic information.
Further, the scheduling service is: drawing up a write operation order;
executing corresponding scheduling service according to the semantic information, and generating a scheduling service processing result, wherein the scheduling service processing result comprises the following steps:
judging whether to carry out ticket drawing according to the semantic information; if yes, generating a corresponding operation ticket by the ticket drawing tool according to the ticket drawing element in the semantic information;
and performing term check, topology check, logic check and state check on the operation ticket through an automatic check function of the ticket-drawing tool.
Further, before the scheduling service processing result is subjected to voice broadcast, the method includes:
and analyzing and processing the scheduling service by adopting an artificial intelligence algorithm and combining with a knowledge rule, and providing decision support for scheduling operation.
Further, before the scheduling service processing result is subjected to voice broadcast, the method includes:
and converting the scheduling service processing result into a voice result through character recognition.
The second aspect of the present invention provides a speech recognition scheduling service speech interaction system, including:
the voice conversion module receives scheduling service voice information through voice and converts the scheduling service voice information into semantic information;
the scheduling service execution module is used for executing the corresponding scheduling service according to the semantic information and generating a scheduling service processing result;
and the voice broadcasting module is used for carrying out voice broadcasting on the scheduling service processing result.
Further, the voice conversion module is further configured to:
converting the scheduling service voice information into text information through voice recognition;
segmenting the text information through a segmentation tool, and deleting stop words in the segmented words through a stop table to obtain filtered text information;
calculating the similarity between the filtered text information and the scheduling service in the scheduling service classification model by a cosine similarity algorithm;
and taking the scheduling service with the highest similarity as semantic information.
Further, the scheduling service is: drawing up a write operation order;
the scheduling service execution module is further configured to:
judging whether to carry out ticket drawing according to the semantic information; if yes, generating a corresponding operation ticket by the ticket drawing tool according to the ticket drawing element in the semantic information;
and performing term check, topology check, logic check and state check on the operation ticket through an automatic check function of the ticket-drawing tool.
Further, the voice broadcast module is also used for:
and analyzing and processing the scheduling service by adopting an artificial intelligence algorithm and combining with a knowledge rule, and providing decision support for scheduling operation.
Further, the voice broadcast module is also used for:
and converting the scheduling service processing result into a voice result through character recognition.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
the invention provides a voice interaction method and a system for scheduling service of voice recognition, wherein the method comprises the following steps: receiving scheduling service voice information, and converting the scheduling service voice information into semantic information; executing corresponding scheduling service according to the semantic information and generating a scheduling service processing result; and carrying out voice broadcast on the scheduling service processing result. The method automatically draws an operation ticket according to the information input by the voice of the dispatcher and carries out comprehensive check, replaces manual writing of the operation ticket, and directly checks the written and comprehensively checked operation ticket without manually writing the operation ticket by the dispatcher, thereby reducing the workload of the dispatcher, improving the efficiency and safety of dispatching operation, and solving the technical problems that the operation business of the current power grid is greatly increased, and the relevant power failure and recovery conditions need to be confirmed by a large amount of manual checks of the dispatcher before and after operation, so that the dispatching operation efficiency and the operation safety of the power grid are influenced.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a voice interaction method for scheduling services by voice recognition according to an embodiment of the present invention;
fig. 2 is a diagram of an apparatus of a speech recognition dispatch service speech interaction system according to an embodiment of the present invention;
fig. 3 is a block diagram of an electronic device according to an embodiment of the present invention.
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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
A first aspect.
Referring to fig. 1, an embodiment of the present invention provides a voice interaction method for scheduling service of voice recognition, including:
and S10, receiving the scheduling service voice information, and converting the scheduling service voice information into semantic information.
In a specific implementation manner of the embodiment of the present invention, the converting the scheduling service voice information into semantic information includes:
converting the scheduling service voice information into text information through voice recognition;
segmenting the text information through a segmentation tool, and deleting stop words in the segmented words through a stop table to obtain filtered text information;
calculating the similarity between the filtered text information and the scheduling service in the scheduling service classification model by a cosine similarity algorithm;
and taking the scheduling service with the highest similarity as semantic information.
It should be noted that the scheduling service voice information may be voice input by a dispatcher, or may be voice of a dispatch telephone, voice of a dispatch network command client, or the like.
It will be appreciated that through artificial intelligence techniques, speech is converted into corresponding textual information and extraneous information is filtered to obtain text.
And S20, executing the corresponding scheduling service according to the semantic information, and generating a scheduling service processing result.
In a specific implementation manner of the embodiment of the present invention, the scheduling service is: drawing up a write operation order;
executing corresponding scheduling service according to the semantic information, and generating a scheduling service processing result, wherein the scheduling service processing result comprises the following steps:
judging whether to carry out ticket drawing according to the semantic information; if yes, generating a corresponding operation ticket by the ticket drawing tool according to the ticket drawing element in the semantic information;
and performing term check, topology check, logic check and state check on the operation ticket through an automatic check function of the ticket-drawing tool.
It can be understood that, the semantic information is obtained by calculation, whether the semantic information is complete (if there is a missing parameter or the parameter types are not matched, the scheduling service cannot be executed) is judged, and when the semantic information is incomplete:
acquiring incomplete semantic information;
processing the incomplete semantic information by adopting an artificial intelligent semantic analysis method (such as a similarity algorithm and a deep learning algorithm) to obtain corrected semantic information;
and weighting the incomplete semantic information and the corrected semantic information to finally obtain the semantic information of the current content.
The scheduling service processing is divided into three types of intelligent application operation, intelligent log retrieval and intelligent information interaction based on the intelligent scheduling service;
the intelligent scheduling service foundation comprehensively utilizes a plurality of scheduling service systems adopted in the Guangdong power grid scheduling operation, and adopts an artificial intelligence technology to associate, analyze and process in combination with knowledge rules such as a regulation rule, a control rule, a safety rule and the like, so that the Guangdong power grid scheduling operation is not limited to the appearance data, the intelligent and rapid extraction of operation key points is ensured, and support is provided for effective and rapid decision of scheduling operation. In addition, the artificial intelligence technology is used for mining and repeatedly training the scheduling operation big data, and the scene recognition accuracy and the service prompt accuracy are improved.
According to the intelligent application operation, a dispatcher can input basic ticket drawing information in a voice mode according to needs through an intelligent voice system, and the intelligent voice system judges and calls a graphical ticket drawing tool of a dispatching command control system to draw an operation ticket automatically. The generated operation order can be comprehensively checked by the system in combination with a power grid operation control system. If the equipment in the operation order content does not accord with the current equipment state, the corresponding problem can be positioned and described.
And intelligent log retrieval is realized, a dispatcher can input log information to be inquired in a voice mode, and an intelligent voice system automatically acquires log contents appointed by a dispatching command control system according to the contents to modify and display the log contents.
And (3) intelligent information interaction, wherein a dispatcher records contents to be inquired, such as comprehensive information of a power grid, system common knowledge and the like, in a man-machine voice interaction dialog box of the intelligent voice system, and the system automatically acquires and displays corresponding contents based on the intelligent dispatching service basis.
It should be noted that, the scheduling service processing method identifies the information intention expression through the obtained text semantics of the scheduling service voice information, and obtains the processing method corresponding to the scheduling service according to the text semantics.
And S30, carrying out voice broadcast on the scheduling service processing result.
In a specific implementation manner of the embodiment of the present invention, before the step S30, the method further includes:
and analyzing and processing the scheduling service by adopting an artificial intelligence algorithm and combining with a knowledge rule, and providing decision support for scheduling operation.
In a specific implementation manner of the embodiment of the present invention, before the step S30, the method further includes:
and converting the scheduling service processing result into a voice result through character recognition.
It should be noted that the dispatcher is fed back in the form of voice, text, etc. by calling the processing method corresponding to the dispatching service and obtaining the processing result.
According to the method and the system, the semantic information of the input content is automatically acquired through the voice information of the scheduling service input by the dispatcher, the information intention expression is recognized, the scheduling service is classified, the processing method corresponding to the scheduling service is called, and finally the processing result corresponding to the scheduling service is pushed to the dispatcher in the forms of voice and the like, so that man-machine interaction of the scheduling service is realized. The intelligent voice system can divide the scheduling service processing into three types of intelligent application operation, intelligent log retrieval and intelligent information interaction based on the intelligent scheduling service basis. The intelligent scheduling service foundation comprehensively utilizes a plurality of scheduling service systems such as a Guangdong power grid scheduling command control system, a power grid operation control system and the like, adopts an artificial intelligence technology to be associated, analyzed and processed in combination with knowledge rules such as a regulation rule, an operation rule, a safety rule and the like, and provides support for effective and rapid decision making of scheduling operation. And (3) intelligent application operation, wherein a dispatcher can input basic operation information in a voice mode, the intelligent voice system calls a scheduling command control system graphic ticket simulation tool to automatically draft an operation ticket after judging, and the operation ticket is comprehensively checked according to a power grid operation control system and the like, so that an operation ticket subjected to comprehensive checking is finally obtained. And intelligent log retrieval is realized, a dispatcher can input log information to be inquired in a voice mode, and an intelligent voice system automatically acquires log contents appointed by a dispatching command control system according to the contents to modify and display the log contents. And (3) intelligent information interaction, wherein a dispatcher records contents to be inquired, such as comprehensive information of a power grid, system common knowledge and the like, in a man-machine voice interaction dialog box of the intelligent voice system, and the system automatically acquires and displays corresponding contents based on the intelligent dispatching service basis.
A second aspect.
Referring to fig. 2, an embodiment of the present invention provides a speech recognition scheduling service speech interaction system, including:
and the voice conversion module 10 receives the scheduling service voice information through voice and converts the scheduling service voice information into semantic information.
In a specific implementation manner of the embodiment of the present invention, the speech conversion module 10 is further configured to:
converting the scheduling service voice information into text information through voice recognition;
segmenting the text information through a segmentation tool, and deleting stop words in the segmented words through a stop table to obtain filtered text information;
calculating the similarity between the filtered text information and the scheduling service in the scheduling service classification model by a cosine similarity algorithm;
and taking the scheduling service with the highest similarity as semantic information.
And the scheduling service execution module 20 is configured to execute the corresponding scheduling service according to the semantic information, and generate a scheduling service processing result.
In a specific implementation manner of the embodiment of the present invention, the scheduling service is: drawing up a write operation order;
the scheduling service execution module 20 is further configured to:
judging whether to carry out ticket drawing according to the semantic information; if yes, generating a corresponding operation ticket by the ticket drawing tool according to the ticket drawing element in the semantic information;
and performing term check, topology check, logic check and state check on the operation ticket through an automatic check function of the ticket-drawing tool.
And the voice broadcasting module 30 is configured to perform voice broadcasting on the scheduling service processing result.
In a specific implementation manner of the embodiment of the present invention, the voice broadcast module 30 is further configured to:
and analyzing and processing the scheduling service by adopting an artificial intelligence algorithm and combining with a knowledge rule, and providing decision support for scheduling operation.
In a specific implementation manner of the embodiment of the present invention, the voice broadcast module 30 is further configured to:
the voice broadcast module is also used for:
and converting the scheduling service processing result into a voice result through character recognition.
The method automatically draws an operation ticket according to the information input by the voice of the dispatcher and carries out comprehensive check, replaces manual writing of the operation ticket, and directly checks the written and comprehensively checked operation ticket without manually writing the operation ticket by the dispatcher, thereby reducing the workload of the dispatcher, improving the efficiency and safety of dispatching operation, and solving the technical problems that the operation business of the current power grid is greatly increased, and the relevant power failure and recovery conditions need to be confirmed by a large amount of manual checks of the dispatcher before and after operation, so that the dispatching operation efficiency and the operation safety of the power grid are influenced.
In a third aspect.
The present invention provides an electronic device, including:
a processor, a memory, and a bus;
the bus is used for connecting the processor and the memory;
the memory is used for storing operation instructions;
the processor is configured to invoke the operation instruction, and the executable instruction enables the processor to execute an operation corresponding to the speech recognition scheduling service speech interaction method according to the first aspect of the present application.
In an alternative embodiment, an electronic device is provided, as shown in fig. 3, the electronic device 5000 shown in fig. 3 includes: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are coupled, such as via a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that the transceiver 5004 is not limited to one in practical application, and the structure of the electronic device 5000 is not limited to the embodiment of the present application.
The processor 5001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 5001 may also be a combination of processors implementing computing functionality, e.g., a combination comprising one or more microprocessors, a combination of DSPs and microprocessors, or the like.
The memory 5003 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 5003 is used for storing application program codes for executing the present solution, and the execution is controlled by the processor 5001. The processor 5001 is configured to execute application program code stored in the memory 5003 to implement the teachings of any of the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like.
A fourth aspect.
The present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for scheduling service voice interaction for voice recognition as shown in the first aspect of the present application.
Yet another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, which, when run on a computer, enables the computer to perform the corresponding content in the aforementioned method embodiments.
Claims (10)
1. A speech recognition method for scheduling service speech interaction is characterized by comprising the following steps:
receiving scheduling service voice information, and converting the scheduling service voice information into semantic information;
executing corresponding scheduling service according to the semantic information and generating a scheduling service processing result;
and carrying out voice broadcast on the scheduling service processing result.
2. The method for speech interaction of speech recognition dispatch services according to claim 1, wherein said converting the speech information of dispatch services into semantic information comprises:
converting the scheduling service voice information into text information through voice recognition;
segmenting the text information through a segmentation tool, and deleting stop words in the segmented words through a stop table to obtain filtered text information;
calculating the similarity between the filtered text information and the scheduling service in the scheduling service classification model by a cosine similarity algorithm;
and taking the scheduling service with the highest similarity as semantic information.
3. The speech recognition voice interaction method for scheduling service as claimed in claim 1, wherein the scheduling service is: drawing up a write operation order;
executing corresponding scheduling service according to the semantic information, and generating a scheduling service processing result, wherein the scheduling service processing result comprises the following steps:
judging whether to carry out ticket drawing according to the semantic information; if yes, generating a corresponding operation ticket by the ticket drawing tool according to the ticket drawing element in the semantic information;
and performing term check, topology check, logic check and state check on the operation ticket through an automatic check function of the ticket-drawing tool.
4. The voice interaction method for scheduling service of voice recognition according to claim 1, wherein before the voice broadcasting the scheduling service processing result, the method comprises:
and analyzing and processing the scheduling service by adopting an artificial intelligence algorithm and combining with a knowledge rule, and providing decision support for scheduling operation.
5. The voice interaction method for scheduling service of voice recognition according to claim 1, wherein before the voice broadcasting the scheduling service processing result, the method comprises:
and converting the scheduling service processing result into a voice result through character recognition.
6. A speech-recognized dispatch service speech interaction system, comprising:
the voice conversion module receives scheduling service voice information through voice and converts the scheduling service voice information into semantic information;
the scheduling service execution module is used for executing the corresponding scheduling service according to the semantic information and generating a scheduling service processing result;
and the voice broadcasting module is used for carrying out voice broadcasting on the scheduling service processing result.
7. The speech recognition dispatch service speech interaction system of claim 6, wherein the speech translation module is further configured to:
converting the scheduling service voice information into text information through voice recognition;
segmenting the text information through a segmentation tool, and deleting stop words in the segmented words through a stop table to obtain filtered text information;
calculating the similarity between the filtered text information and the scheduling service in the scheduling service classification model by a cosine similarity algorithm;
and taking the scheduling service with the highest similarity as semantic information.
8. The speech recognition dispatch service speech interaction system of claim 6, wherein the dispatch service is: drawing up a write operation order;
the scheduling service execution module is further configured to:
judging whether to carry out ticket drawing according to the semantic information; if yes, generating a corresponding operation ticket by the ticket drawing tool according to the ticket drawing element in the semantic information;
and performing term check, topology check, logic check and state check on the operation ticket through an automatic check function of the ticket-drawing tool.
9. The voice interactive system for scheduling service of voice recognition according to claim 6, wherein the voice broadcasting module is further configured to:
and analyzing and processing the scheduling service by adopting an artificial intelligence algorithm and combining with a knowledge rule, and providing decision support for scheduling operation.
10. The voice interactive system for scheduling service of voice recognition according to claim 6, wherein the voice broadcasting module is further configured to:
and converting the scheduling service processing result into a voice result through character recognition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111040094.1A CN113705224A (en) | 2021-09-06 | 2021-09-06 | Voice recognition scheduling service voice interaction method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111040094.1A CN113705224A (en) | 2021-09-06 | 2021-09-06 | Voice recognition scheduling service voice interaction method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113705224A true CN113705224A (en) | 2021-11-26 |
Family
ID=78660636
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111040094.1A Pending CN113705224A (en) | 2021-09-06 | 2021-09-06 | Voice recognition scheduling service voice interaction method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113705224A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115101067A (en) * | 2022-06-16 | 2022-09-23 | 陈明华 | Smart power grids voice system based on block chain technique |
| CN115277955A (en) * | 2022-08-08 | 2022-11-01 | 国家石油天然气管网集团有限公司 | Telephone scheduling method, device and system for natural gas pipe network |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018102980A1 (en) * | 2016-12-06 | 2018-06-14 | 吉蒂机器人私人有限公司 | Speech interaction method, device and system |
| CN111048080A (en) * | 2019-11-22 | 2020-04-21 | 广东电网有限责任公司 | Intelligent dispatching command system based on voice recognition technology |
| CN111326153A (en) * | 2019-12-17 | 2020-06-23 | 国家电网有限公司 | Power grid intelligent regulation and control auxiliary robot interaction method based on semantic understanding |
| CN113314106A (en) * | 2021-05-19 | 2021-08-27 | 国网辽宁省电力有限公司 | Electric power information query and regulation function calling method based on voice and intention recognition |
-
2021
- 2021-09-06 CN CN202111040094.1A patent/CN113705224A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018102980A1 (en) * | 2016-12-06 | 2018-06-14 | 吉蒂机器人私人有限公司 | Speech interaction method, device and system |
| CN111048080A (en) * | 2019-11-22 | 2020-04-21 | 广东电网有限责任公司 | Intelligent dispatching command system based on voice recognition technology |
| CN111326153A (en) * | 2019-12-17 | 2020-06-23 | 国家电网有限公司 | Power grid intelligent regulation and control auxiliary robot interaction method based on semantic understanding |
| CN113314106A (en) * | 2021-05-19 | 2021-08-27 | 国网辽宁省电力有限公司 | Electric power information query and regulation function calling method based on voice and intention recognition |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115101067A (en) * | 2022-06-16 | 2022-09-23 | 陈明华 | Smart power grids voice system based on block chain technique |
| CN115101067B (en) * | 2022-06-16 | 2024-04-16 | 陈明华 | Smart power grids voice system based on blockchain technique |
| CN115277955A (en) * | 2022-08-08 | 2022-11-01 | 国家石油天然气管网集团有限公司 | Telephone scheduling method, device and system for natural gas pipe network |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109002510B (en) | Dialogue processing method, device, equipment and medium | |
| CN111428010B (en) | Man-machine intelligent question-answering method and device | |
| JP2020030408A (en) | Method, apparatus, device and medium for identifying key phrase in audio | |
| CN113705224A (en) | Voice recognition scheduling service voice interaction method and system | |
| CN109947924B (en) | Dialogue system training data construction method and device, electronic equipment and storage medium | |
| CN112286485B (en) | Method and device for controlling application through voice, electronic equipment and storage medium | |
| CN112653798A (en) | Intelligent customer service voice response method and device, computer equipment and storage medium | |
| CN112671985A (en) | Agent quality inspection method, device, equipment and storage medium based on deep learning | |
| CN112836521A (en) | Question-answer matching method and device, computer equipment and storage medium | |
| CN112182157B (en) | Training method of online sequence labeling model, online labeling method and related equipment | |
| CN112669850A (en) | Voice quality detection method and device, computer equipment and storage medium | |
| CN116541494A (en) | Model training method, device, equipment and medium for replying information | |
| CN115098677A (en) | User interface component classification method and device | |
| CN113724738A (en) | Voice processing method, decision tree model training method, device, equipment and storage medium | |
| CN114118937A (en) | Information recommendation method and device based on task, electronic equipment and storage medium | |
| CN112925889A (en) | Natural language processing method, device, electronic equipment and storage medium | |
| CN113515280A (en) | Page code generation method and device | |
| CN111104118A (en) | AIML-based natural language instruction execution method and system | |
| CN114818683B (en) | Operation and maintenance method and device based on mobile terminal | |
| CN113223512B (en) | Automatic operation and maintenance system voice construction method | |
| CN112711654B (en) | Chinese character interpretation technique generation method, system, equipment and medium for voice robot | |
| CN111967273B (en) | Dialog management system, method and rule engine device | |
| CN112287101B (en) | Information processing method, device and computer equipment | |
| CN116939111A (en) | Man-machine customer service switching method and device, electronic equipment and storage medium | |
| CN113010812A (en) | Information acquisition method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |