CN117113947B - Form filling system, method, electronic equipment and storage medium - Google Patents
Form filling system, method, electronic equipment and storage medium Download PDFInfo
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- CN117113947B CN117113947B CN202311386510.2A CN202311386510A CN117113947B CN 117113947 B CN117113947 B CN 117113947B CN 202311386510 A CN202311386510 A CN 202311386510A CN 117113947 B CN117113947 B CN 117113947B
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- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000013507 mapping Methods 0.000 claims abstract description 35
- 238000012545 processing Methods 0.000 claims abstract description 23
- 238000005516 engineering process Methods 0.000 claims abstract description 16
- 238000004590 computer program Methods 0.000 claims description 7
- 238000010276 construction Methods 0.000 claims description 3
- 239000000284 extract Substances 0.000 description 3
- 238000010801 machine learning Methods 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013079 data visualisation Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/174—Form filling; Merging
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/166—Editing, e.g. inserting or deleting
- G06F40/177—Editing, e.g. inserting or deleting of tables; using ruled lines
- G06F40/18—Editing, e.g. inserting or deleting of tables; using ruled lines of spreadsheets
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Abstract
The invention discloses a form filling system, a form filling method, electronic equipment and a storage medium, which comprise the steps of collecting a plurality of form templates, wherein a plurality of field names are arranged in the form templates; establishing a mapping relation between each field name and text semantic data matched with each field name according to the field names, and constructing a form matching file based on the mapping relation; collecting input voice or input text of a user side, and matching the input voice or the input text with the field name by using an NLP processing technology based on the form matching file to obtain a matching result; and automatically filling keywords matched with field names in the form to be filled according to the matching result. The form filling method and the form filling device can automatically fill forms, improve business handling efficiency and improve user operation experience.
Description
Technical Field
The invention belongs to the technical field of data visualization, and particularly relates to a form filling system, a form filling method, electronic equipment and a storage medium.
Background
At present, the form is filled in one field by a user, the speed is low, the user is inconvenient to fill in, for example, a fee reimbursement form is filled in a mobile phone, the amount of a ticket needs to be filled in, the departure place, the date and the like, the user needs to click different input boxes, and the operation of a plurality of current software systems in a data input link is very complicated.
Disclosure of Invention
The present invention is directed to a form filling method for solving the above-mentioned problems in the prior art.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the invention also provides a form filling method, which comprises the following steps:
collecting a plurality of form templates, wherein a plurality of field names are arranged in the form templates;
according to the field names, establishing a mapping relation between each field name and text semantic data matched with each field name, and constructing a form matching file based on the mapping relation;
collecting input voice or input text of a user side, and based on the form matching file, matching the input voice or the input text with field names in a form to be filled by using an NLP processing technology to obtain a matching result;
and automatically filling keywords matched with field names in the form to be filled according to the matching result.
In some embodiments, constructing the form matching file includes:
extracting field names, setting corresponding text semantics for each field name, and defining each field name in a plurality of form templates as a corresponding label;
and determining the mapping relation between each field name subjected to label processing and text semantics, and constructing a form matching file according to the mapping relation.
In some embodiments, decoding the collected input speech into text by the language recognition model includes:
extracting sound characteristic signals from the input voice, transmitting the extracted sound characteristic signals to a voice decoder, matching the sound characteristic signals with a word dictionary through the voice decoder, and transmitting the matched words to a language recognition model;
and decoding the matched characters through the language identification model to obtain an output character result.
In some embodiments, further comprising:
extracting keywords from the text result through an NLP processing technology, matching the extracted keywords with the field names based on the form matching file, and outputting manual input prompt information if the matching is incorrect;
recording incorrect data, reconstructing a form matching file, and improving the matching accuracy.
In some embodiments, after extracting the sound characteristic signal from the input voice, the method further includes:
the voice characteristic signal is preprocessed to filter out voice content unrelated to the field name.
The application also provides a form filling system, which comprises:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring a plurality of form templates, and a plurality of field names are arranged in the form templates;
the construction module is used for establishing a mapping relation between each field name and text semantic data matched with each field name according to the field names, and constructing a form matching file based on the mapping relation;
the matching module is used for collecting input voice or input characters of a user side, and based on the form matching file, matching the input voice or the input characters with field names in a form to be filled by using an NLP processing technology to obtain a matching result;
and the generating module is used for automatically filling keywords matched with field names in the form to be filled according to the matching result.
In some embodiments, the building module is specifically configured to:
extracting field names, setting corresponding text semantics for each field name, and defining each field name in a plurality of form templates as a corresponding label;
and determining the mapping relation between each field name subjected to label processing and text semantics, and constructing a form matching file according to the mapping relation.
An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method when the computer program is executed.
A non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method.
The beneficial effects are that:
the form can be automatically filled, the value which should be filled in each input box can be automatically identified through voice or text recognition, the input of the form is automatically completed, the operation experience is greatly improved, and the operation steps of inputting structured data by a user are greatly reduced.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, are included to provide a further understanding of the application and to provide a further understanding of the application with regard to the other features, objects and advantages of the application. The drawings of the illustrative embodiments of the present application and their descriptions are for the purpose of illustrating the present application and are not to be construed as unduly limiting the present application. In the drawings:
fig. 1 is a schematic flow chart of a form filling method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a form filling system according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present application.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly described below with reference to the accompanying drawings and the description of the embodiments or the prior art, and it is obvious that the following description of the structure of the drawings is only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art. It should be noted that the description of these examples is for aiding in understanding the present invention, but is not intended to limit the present invention.
It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments of the present invention.
It should be understood that for the term "and/or" that may appear herein, it is merely one association relationship that describes an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a alone, B alone, and both a and B; for the term "/and" that may appear herein, which is descriptive of another associative object relationship, it means that there may be two relationships, e.g., a/and B, it may be expressed that: a alone, a alone and B alone; in addition, for the character "/" that may appear herein, it is generally indicated that the context associated object is an "or" relationship.
Example 1:
fig. 1 is a schematic flow chart of a form filling method according to an embodiment of the present invention, including:
s201, collecting a plurality of form templates, wherein a plurality of field names are arranged in the form templates.
Specifically, in an actual application scenario, different services correspond to different forms, so for different services, form templates corresponding to different services can be created, where the form templates include a form name, a form category, and the like, for example, a leave application form template is created, including a name, a department, a leave type, an application date, a leave time, a leave event, a notice, and the like. The form name may refer to a real life name of the form, such as "leave application". For different service form models, the form template has a plurality of field names, such as name, department, leave type, application date, leave time, leave event and notice in the leave application form template are 7 field names.
S202, according to the field names, mapping relations between the field names and text semantic data matched with the field names are established, and form matching files are established based on the mapping relations.
Specifically, before input voice or input text is not received, the field names are preprocessed, corresponding text semantics of each field name are established, mapping relations between the field names and matched text semantic data are established, the mapping relations are written into a form matching file, and the form matching file is sequentially constructed.
In order to construct a form matching file, in a preferred embodiment of the present solution, constructing a form matching file includes:
extracting field names, setting corresponding text semantics for each field name, and defining each field name in a plurality of form templates as a corresponding label;
and determining the mapping relation between each field name subjected to label processing and text semantics, and constructing a form matching file according to the mapping relation.
Specifically, field names in a plurality of form templates are extracted, the field names are extracted, text semantics corresponding to the field names are set for each field name, each field name in a plurality of form templates is defined as a corresponding label, and each label corresponds to a corresponding function realization code. Based on the field names which are defined as labels, determining the mapping relation between each field name and text semantic data, writing the mapping relation into a form matching file, and sequentially constructing the form matching file. In one embodiment of the present application, the mapping rule is more than one, and may be adjusted in real time according to the actual situation. And taking the adjusted form matching file as a new form matching file.
S203, collecting input voice or input text of a user terminal, and based on the form matching file, matching the input voice or input text with field names in a form to be filled by using an NLP processing technology to obtain a matching result.
Specifically, input voice of a user terminal is collected, and based on the form matching file, the input voice is matched with the field name by using an NLP processing technology. And acquiring input characters of a user side, based on the form matching file, matching the input characters with field names in a form to be filled by using an NLP processing technology according to the input characters, and decoding the acquired input voice into characters through a language recognition model.
In order to decode the collected input speech into text by the language recognition model, in a preferred embodiment of the present solution, decoding the collected input speech into text by the language recognition model includes:
extracting sound characteristic signals from the input voice, transmitting the extracted sound characteristic signals to a voice decoder, matching the sound characteristic signals with a word dictionary through the voice decoder, and transmitting the matched words to a language recognition model;
and decoding the matched characters through the language identification model to obtain an output character result.
Specifically, if an accurate search result is to be obtained, the accuracy of speech recognition on the decoding grid is to be improved, so that the speech decoder plays a key role in the decoding process. Firstly, inputting the characteristics of a voice signal, decoding the characteristics into corresponding language characters, and continuously recognizing voice: firstly, through sound judgment, the rest information irrelevant to main content in the sound is removed, and the voice signal is preprocessed, namely the sound characteristic signal is preprocessed, so that the sound content irrelevant to the field name is filtered. And secondly, extracting the voice characteristic signals in the next stage, transmitting the extracted signal characteristics to a voice decoder, combining and acting a plurality of parts in the voice decoder, mainly matching voice with a word dictionary, transmitting the matched words to a language recognition model for processing, finally judging by using MAP (maximum a posteriori probability) criteria, and finally outputting a word result after decoding.
In order to ensure the correctness of form filling, in a preferred embodiment of the present solution, the method further includes:
extracting keywords from the text result through an NLP processing technology, matching the extracted keywords with the field names based on the form matching file, and manually inputting a correct value by a user side if the matching is incorrect;
recording incorrect data, reconstructing a form matching file, and improving the matching accuracy.
Specifically, keywords are extracted from the text result through an NLP processing technology, and the extracted keywords are matched with the field names based on the form matching file to generate a form. If a certain keyword is not matched with a field name in the generated form, the user side inputs a correct value. And meanwhile, data which are incorrectly matched are recorded, in one embodiment, if the fields filled in by the system for the first time are not matched or the filled-in values are not identified, after the user manually corrects the fields, the system records the result of the corrected records, trains the corrected results serving as calibration values according to historical data by a machine learning method, reconstructs form matching files, and improves the accuracy of the filled-in fields and the accuracy of the filled-in values.
S204, automatically filling keywords matched with field names in the form to be filled according to the matching result.
Specifically, a large number of form templates and form field names are collected, training is performed by adopting a machine learning method, field names matched with various input values are found, a user inputs voice or a section of characters, and the system extracts keywords such as quantity and date in the characters. The system extracts the field names in the form to be entered. The system extracts the field names matched with the keywords by matching the voice input or the text input. And filling the keywords into the matched fields according to the matching result by the system. If the system is incorrectly matched, the user needs to input the correct value, and the system adds the input as a new sample into the training data set and retrains the training data set. According to the requirement, a proprietary model can be trained for a specific user group (such as a user of a certain enterprise) so as to improve the matching accuracy.
It should be noted that, the form filling method in the present application does not require the user to input the values of the respective fields one by one voice, but the user inputs the values of all the fields or a plurality of the fields at a time by speaking a sentence.
Example 2:
the present forms are all filled in one field by one field of the user, the speed is low, the user is inconvenient to fill in, for example, the user fills in a charge reimbursement form on a mobile phone, the amount of the ticket needs to be filled in, the departure place and the date need to be filled in, the user needs to click different input boxes, after the method is used, the user only needs to speak the charge reimbursement content, for example, a 1200-element ticket going to the sea yesterday, the system automatically recognizes the value which each input box needs to be filled in, and the user finishes the input of the form in a usual speaking mode, so that the operation experience is greatly improved.
The method comprises the following specific steps:
1) Different services correspond to different forms, so that form templates corresponding to different services can be created for different services, wherein the form templates comprise form names, form categories and the like, such as creating a leave application form template comprising names, departments, leave types, application dates, leave times, leave events, notes and the like. The form name may refer to a real life name of the form, such as "leave application". For different service form models, the form template has a plurality of field names, such as name, department, leave type, application date, leave time, leave event and notice in the leave application form template are 7 field names.
2) Before input voice or input words are not received, the field names are preprocessed, corresponding text semantics of the field names are established for each field name, mapping relations between the field names and matched text semantic data are established, the mapping relations are written into a form matching file, and the form matching file is sequentially established.
3) And acquiring input voice or input text of a user side, matching the input voice or input text with the field names by using an NLP processing technology based on the form matching file to obtain a matching result, and automatically filling keywords matched with the field names in the form to be filled according to the matching result.
4) Extracting keywords from the text result through an NLP processing technology, matching the extracted keywords with the field names based on the form matching file, and filling a form according to the matching result. If a certain keyword is not matched with a field name in the filled form, the user side inputs a correct value. And meanwhile, data which are incorrectly matched are recorded, in one embodiment, if the fields filled in by the system for the first time are not matched or the filled-in values are not identified, after the user manually corrects the fields, the system records the result of the corrected records, trains the corrected results serving as calibration values according to historical data by a machine learning method, reconstructs form matching files, and improves the accuracy of the filled-in fields and the accuracy of the filled-in values.
The form can be automatically filled, the value which should be filled in each input box can be automatically identified through voice or text recognition, the input of the form is automatically completed, the operation experience is greatly improved, and the operation steps of inputting structured data by a user are greatly reduced.
Fig. 2 is a flowchart of an embodiment of a form filling system according to the present invention, as shown in fig. 2, and the form filling system according to the embodiment of the present invention includes the following steps:
the collection module 10 is used for collecting a plurality of form templates, wherein a plurality of field names are arranged in the form templates;
the construction module 20 is used for establishing a mapping relation between each field name and text semantic data matched with each field name according to the field names, and constructing a form matching file based on the mapping relation;
the matching module 30 collects input voice or input text of the user side, and matches the input voice or input text with field names in the form to be filled by using an NLP processing technology based on the form matching file to obtain a matching result;
and the generating module 40 is used for automatically filling the keywords matched with the field names in the form to be filled in according to the matching result.
In a specific application scenario, the building module 20 is specifically configured to:
extracting field names, setting corresponding text semantics for each field name, and defining each field name in a plurality of form templates as a corresponding label;
and determining the mapping relation between each field name subjected to label processing and text semantics, and constructing a form matching file according to the mapping relation.
Fig. 3 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present invention, as shown in fig. 3, an electronic device 60 includes: a processor 601 (processor), a memory 602 (memory), and a bus 603;
wherein, the processor 601 and the memory 602 complete communication with each other through the bus 603;
the processor 601 is configured to invoke program instructions in the memory 602 to perform the methods provided by the method embodiments described above, including, for example: collecting a plurality of form templates, wherein a plurality of field names are arranged in the form templates; establishing a mapping relation between each field name and text semantic data matched with each field name according to the field names, and constructing a form matching file based on the mapping relation; collecting input voice or input text of a user side, and matching the input voice or the input text with the field name by using an NLP processing technology based on the form matching file to obtain a matching result; and automatically filling keywords matched with field names in the form to be filled according to the matching result.
The present embodiment provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described method embodiments. Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
The apparatus embodiments described above are merely illustrative, wherein elements illustrated as separate elements may or may not be physically separate, and elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product, which may be stored in a computer-readable storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the various embodiments or methods of some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the scope of the invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A form filling method, comprising:
collecting a plurality of form templates, wherein a plurality of field names are arranged in the form templates;
according to the field names, establishing a mapping relation between each field name and text semantic data matched with each field name, and constructing a form matching file based on the mapping relation;
collecting input voice or input characters of a user side, and based on the form matching file, matching the input voice or the input characters with field names in a form to be filled by using an NLP processing technology to obtain a matching result, wherein the collected input voice is decoded into characters through a language recognition model;
automatically filling keywords matched with field names in the form to be filled according to the matching result;
decoding the collected input voice into words through a language identification model, comprising:
extracting sound characteristic signals from the input voice, transmitting the extracted sound characteristic signals to a voice decoder, matching the sound characteristic signals with a word dictionary through the voice decoder, and transmitting the matched words to a language recognition model;
and decoding the matched characters through the language identification model to obtain an output character result.
2. The method of claim 1, wherein constructing a form matching file comprises:
extracting field names, setting corresponding text semantics for each field name, and defining each field name in a plurality of form templates as a corresponding label;
and determining the mapping relation between each field name subjected to label processing and text semantics, and constructing a form matching file according to the mapping relation.
3. The method as recited in claim 1, further comprising:
extracting keywords from the text result through an NLP processing technology, matching the extracted keywords with the field names based on the form matching file, and outputting manual input prompt information if the matching is incorrect;
recording incorrect data, reconstructing a form matching file, and improving the matching accuracy.
4. The method of claim 1, further comprising, after extracting the sound feature signal from the input speech:
the voice characteristic signal is preprocessed to filter out voice content unrelated to the field name.
5. A form filling system, comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring a plurality of form templates, and a plurality of field names are arranged in the form templates;
the construction module is used for establishing a mapping relation between each field name and text semantic data matched with each field name according to the field names, and constructing a form matching file based on the mapping relation;
the matching module is used for collecting input voice or input characters of a user side, and based on the form matching file, matching the input voice or the input characters with field names in a form to be filled by using an NLP processing technology to obtain a matching result;
and the generating module is used for automatically filling keywords matched with field names in the form to be filled according to the matching result.
6. The system of claim 5, wherein the building block is specifically configured to:
extracting field names, setting corresponding text semantics for each field name, and defining each field name in a plurality of form templates as a corresponding label;
and determining the mapping relation between each field name subjected to label processing and text semantics, and constructing a form matching file according to the mapping relation.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1 to 4 when the computer program is executed.
8. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1 to 4.
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| CN113988029A (en) * | 2021-10-09 | 2022-01-28 | 深圳金蝶互联网金融服务有限公司 | Form generation method and device, computer equipment and storage medium |
| CN115470861A (en) * | 2022-09-28 | 2022-12-13 | 中国农业银行股份有限公司 | Data processing method and device and electronic equipment |
| CN116311306A (en) * | 2023-03-16 | 2023-06-23 | 精英数智科技股份有限公司 | Form identification method and device based on computer vision algorithm and related components |
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