CN112102838A - Vehicle detection report generation method and system and electronic equipment - Google Patents
Vehicle detection report generation method and system and electronic equipment Download PDFInfo
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Abstract
The invention discloses a vehicle detection report generation method, a vehicle detection report generation system and electronic equipment. The method comprises the following steps: the method comprises the steps that vehicle condition information which is imported by a detection party and aims at a vehicle to be detected is obtained, wherein the vehicle condition information comprises a vehicle condition description text and/or a vehicle condition description voice; under the condition that the vehicle condition information contains the vehicle condition description voice, performing voice recognition on the vehicle condition description voice to obtain a voice recognition text; semantic recognition is carried out on the voice recognition text and/or the vehicle condition description text based on a vehicle condition semantic recognition model, and a standard vehicle condition description text matched with the voice recognition text and/or the vehicle condition description text is determined, wherein the vehicle condition semantic recognition model represents a mapping relation between the vehicle condition description text with the same meaning and the standard vehicle condition description text; and generating a vehicle detection report according to the standard vehicle condition description text. Thereby improving the accuracy and the normalization of the report.
Description
Technical Field
The invention belongs to the technical field of vehicle detection, and particularly relates to a vehicle detection report generation method, a vehicle detection report generation system and electronic equipment.
Background
Currently, before the used-vehicle transaction is carried out, the price needs to be evaluated according to the detection report of the vehicle. In the prior art, for the generation of a detection report, an inspector is generally required to obtain a picture, paint film data, historical driving data and the like of a vehicle on site, and generate the detection report through text description of the vehicle. The detection report generated based on the mode has low efficiency on one hand, different detectors often have different descriptions aiming at the same term on the other hand, the generated report is not standard in terms and has low accuracy.
Disclosure of Invention
The invention provides a vehicle detection report generation method, a vehicle detection report generation system and electronic equipment, and aims to overcome the defects that vehicle detection report phrases generated by the existing mode are not standard and the accuracy is low.
Specifically, the invention is realized by the following technical scheme:
in a first aspect, a vehicle detection report generation method is provided, and includes:
the method comprises the steps that vehicle condition information which is imported by a detection party and aims at a vehicle to be detected is obtained, wherein the vehicle condition information comprises a vehicle condition description text and/or a vehicle condition description voice;
under the condition that the vehicle condition information contains the vehicle condition description voice, performing voice recognition on the vehicle condition description voice to obtain a voice recognition text;
semantic recognition is carried out on the voice recognition text and/or the vehicle condition description text based on a vehicle condition semantic recognition model, and a standard vehicle condition description text matched with the voice recognition text and/or the vehicle condition description text is determined, wherein the vehicle condition semantic recognition model is used for representing the mapping relation between a plurality of vehicle condition description texts with the same semantic meaning and the standard vehicle condition description text;
and generating a vehicle detection report according to the standard vehicle condition description text.
Optionally, the vehicle detection report generating method further includes:
acquiring historical maintenance information and/or insurance information of the vehicle to be detected;
performing text matching on the vehicle detection report according to the historical maintenance information and/or insurance information;
and modifying the vehicle detection report according to the matching result.
Optionally, the vehicle detection report generating method further includes:
under the condition that a vehicle detection request sent by a vehicle detection requester is received, a detection task is assigned to the detection party according to the vehicle characteristic information and/or the geographical position of the vehicle to be detected carried by the vehicle detection request, so that the detection party imports the vehicle condition information.
Optionally, the vehicle condition information further includes a vehicle picture;
generating a vehicle detection report, comprising:
and filling the vehicle picture and the standard vehicle condition description text into corresponding areas in a report template, and generating the vehicle detection report.
Optionally, before generating the vehicle detection report, the method further includes:
and carrying out picture identification on the vehicle picture, and covering predefined privacy information in the vehicle picture.
Optionally, the vehicle detection report generating method further includes:
under the condition of receiving a vehicle detection request sent by a vehicle detection requester, acquiring a corresponding report template according to report use scenes carried by the vehicle detection request, and pre-configuring a corresponding report template for each report use scene;
filling the vehicle picture and the standard vehicle condition description text into corresponding areas in a report template, wherein the corresponding areas comprise:
and extracting target content matched with the corresponding area of the report template from the vehicle picture and the standard vehicle condition description text, and filling the target content into the corresponding area.
Optionally, the vehicle detection report generating method further includes:
acquiring a plurality of groups of text data, wherein each group of text data comprises a vehicle condition description text and a corresponding standard vehicle condition description text, the standard vehicle condition description texts in at least two groups of text data are the same, and the vehicle condition description texts are different but have the same expression meaning;
inputting the vehicle condition description text into a neural network, and determining the difference between the output result of the neural network and the standard vehicle condition description text;
adjusting a network parameter of the neural network based on the difference.
In a second aspect, a vehicle inspection report generation system is provided, the vehicle inspection report generation system comprising:
the acquisition module is used for acquiring vehicle condition information which is imported by a detection party and aims at a vehicle to be detected, wherein the vehicle condition information comprises a vehicle condition description text and/or a vehicle condition description voice;
the voice recognition module is used for carrying out voice recognition on the vehicle condition description voice under the condition that the vehicle condition information contains the vehicle condition description voice to obtain a voice recognition text;
the semantic recognition module is used for performing semantic recognition on the voice recognition text and/or the vehicle condition description text based on a vehicle condition semantic recognition model, and determining a standard vehicle condition description text matched with the voice recognition text and/or the vehicle condition description text, wherein the vehicle condition semantic recognition model is used for representing the mapping relation between a plurality of vehicle condition description texts with the same meaning and the standard vehicle condition description text;
and the report generation module is used for generating a vehicle detection report according to the standard vehicle condition description text.
In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the vehicle detection report generation method according to any one of the first aspect when executing the computer program.
In a fourth aspect, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the vehicle detection report generation method of any one of the first aspects.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
in the embodiment of the invention, the semantic recognition model of the vehicle condition is used for performing semantic recognition on the non-standardized vehicle condition description text imported by the inspector, the non-standardized vehicle condition description text is converted into the standard vehicle condition description text, and the vehicle detection report is generated based on the standard vehicle condition description text, so that the accuracy and the normalization of the report are improved, the requirement on the language description capacity of the inspector is reduced, the inspector is not required to describe the vehicle to be detected according to the normalized description, and the generation efficiency of the report can be improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic diagram illustrating an application scenario of a vehicle inspection report generation method according to an exemplary embodiment of the present invention;
FIG. 2 is a flow chart illustrating a method of vehicle inspection report generation in accordance with an exemplary embodiment of the present invention;
FIG. 3 is a flow chart illustrating another vehicle inspection report generation method in accordance with an exemplary embodiment of the present invention;
FIG. 4 is a block schematic diagram of a vehicle inspection report generation system in accordance with an exemplary embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification 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. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present invention. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
The embodiment of the invention provides a vehicle detection report generation method, which is used for automatically generating a vehicle detection report according to acquired vehicle condition information, and the generation of the report can be realized through a client or a server. The following describes the implementation process of the method by taking the client as an example. It should be noted that, referring to fig. 1, the client 11 may be installed on the intelligent terminal 12. And the user obtains the use authority after registering at the client. The client realizes customized configuration and gives different use authorities to users with different identities.
For example, if the user is a vehicle detection requester, the client provides the vehicle detection requester with the use permission related to the vehicle detection request, after the vehicle detection requester logs in the client, the vehicle detection requester can provide basic feature information (for example, vehicle model, brand, etc.) of the vehicle to be detected, a vehicle location, a payment procedure fee/deposit, a report use scene for selecting a detection report (for example, for second-hand vehicle transaction, financial evaluation, etc.) and the like through a user interface of the client, and the client can generate the vehicle detection request according to the basic feature information of the vehicle provided by the vehicle detection requester; the vehicle detection requester can also view the generated vehicle detection report through the client.
If the user is an inspector, the client provides the inspector with the use permission related to vehicle inspection. After logging in the client, the inspector can view the assigned inspection tasks and import vehicle condition information for generating vehicle inspection reports. The detection task can be that the client determines a proper detection party according to the characteristic information of the vehicle and/or the location of the vehicle carried by the vehicle detection request and assigns the detection task to the detection party when receiving the vehicle detection request sent by the vehicle detection request party, and the detection party notifies a detector to acquire the vehicle condition information of the vehicle to be detected after receiving the detection task. The client can assign the detection tasks to the detectors familiar with the models or brands of the vehicles to be detected, and the client can also assign the detection tasks to the detectors attached to the locations of the vehicles to be detected by referring to the locations of the vehicles to be detected.
And if the user is an auditor for auditing the vehicle detection report, the client provides the use permission related to the audit report for the user. After the auditor logs in the client, the auditor can check the vehicle detection report to be audited, and the auditor also has the authority of requiring the auditor to modify when the report is not audited.
The following describes a specific implementation process of generating a vehicle inspection report after an inspector is assigned to an inspection task, with reference to fig. 1.
Fig. 2 is a flowchart illustrating a vehicle inspection report generation method according to an exemplary embodiment of the present invention, the method including the steps of:
The detection party may be, but is not limited to, a terminal device of an inspector or a user account of a vehicle inspector login client.
The vehicle condition information includes: the vehicle characteristic information of the vehicle to be detected and the vehicle condition description text of the vehicle to be detected by the vehicle inspector. The vehicle characteristic information includes at least one of the following information: vehicle identification information, vehicle pictures (including body pictures, defective portion pictures, etc.), paint film data, historical operating data, vehicle configuration data, etc.
The vehicle characteristic information can be acquired by a detection person by using a terminal device when receiving a detection task, and it can be understood that the terminal device can be but is not limited to a mobile phone with a shooting function and/or a signal acquisition device capable of acquiring historical operation data from an ECU (electronic control unit) and/or a paint film instrument capable of acquiring paint film data later. The characteristic information of the vehicle to be detected can also be requested by the inspector from the vehicle detection requester.
The vehicle condition description text can be generated by an inspector by using office software in the terminal equipment; the inspector can also input a vehicle condition description text in a corresponding area in the user interface of the client.
The standard vehicle condition description text is also a term used in standard words commonly used in the automobile industry. The vehicle condition semantic recognition model is used for representing the mapping relation between various vehicle condition description texts with the same meaning and the standard vehicle condition description text. The vehicle condition semantic recognition model is used for performing semantic recognition on the vehicle condition description text so as to replace a non-standard description text in the vehicle condition description text with a standard vehicle condition description text and standardize expression words in the detection report. For example, if the vehicle condition description text is "there is a damage trace outside the vehicle-mounted controller" or "there is a damage trace outside the ECU" or "there is a damage trace outside the vehicle computer", the vehicle condition semantic recognition model performs semantic recognition on the vehicle condition description text, and the semantic recognition results are "there is a damage trace outside the vehicle computer".
The model training process is described below:
and S1, acquiring multiple groups of text data as training samples.
Each set of text data includes a vehicle condition description text and a corresponding standard vehicle condition description text, the standard vehicle condition description texts included in part of the text data are the same, the vehicle condition description texts are different but have the same expression meaning, for example, one set of text data is { driving computer | vehicle-mounted computer }, the other set of text data is { ECU | vehicle-mounted computer }, both sets of data include the standard vehicle condition description text "vehicle-mounted computer", the vehicle condition description texts of both sets of data are "driving computer", "ECU", and the expressions of "driving computer" and "ECU" are the same and are both "vehicle-mounted computer".
And S2, inputting the vehicle condition description text into the neural network for each group of text data, and determining the difference between the output result of the neural network and the standard vehicle condition description text.
S3, adjusting the network parameters of the neural network based on the difference.
And step 203, generating a vehicle detection report according to the vehicle characteristic information and the standard vehicle condition description text.
In this embodiment, a report template for generating a vehicle detection report is further provided, and in step 203, the vehicle detection report is generated, that is, the vehicle characteristic information and the standard vehicle condition description text are respectively filled into corresponding regions of the report template.
If the vehicle characteristic information includes a vehicle picture and/or imported paint film data and/or historical operation data and/or vehicle configuration data, and the like, in step 203, the vehicle picture, the standard vehicle condition description text and various types of data are respectively filled into corresponding areas of the report template, for example, the vehicle picture is filled into a picture display area; filling a standard vehicle condition description text into a text filling area; various data are filled into the corresponding data display area, and the data can be displayed by adopting various charts, so that the data can be conveniently checked by a user, and the user can be helped to quickly know the vehicle condition of the vehicle to be detected.
In this embodiment, before the detection report is generated, the semantic recognition model is used to perform semantic recognition on the non-standardized vehicle condition description text imported by the inspector, the non-standardized vehicle condition description text is converted into the standard vehicle condition description text, and the vehicle detection report is generated based on the standard vehicle condition description text, so that the accuracy and the normalization of the report are improved, the requirement on the language description capability of the inspector is reduced, the inspector is not required to describe the vehicle to be detected according to the normative description, and the generation efficiency of the vehicle condition description text can be improved.
Different report usage scenarios place different requirements on the content of the inspection report, and in another embodiment, different report templates may be configured for different report usage scenarios. And when the vehicle detection report is generated, acquiring a corresponding report template according to a report use scene carried by the vehicle detection request, extracting target content matched with a corresponding area of the report template from the vehicle characteristic information and the standard vehicle condition description text according to the report template, and filling the target content into the corresponding area.
In another embodiment, in order to avoid the disclosure of the privacy information, the vehicle picture needs to be processed before generating the vehicle detection report, specifically including picture recognition of the vehicle picture, recognition of predefined privacy information in the picture, for example, a license plate number, a background including a person, and the like, and performing an overlay process on the privacy information.
In another embodiment, in order to ensure the authenticity and effectiveness of the vehicle detection report, a process of auditing the report is added, and specifically, the client sends the vehicle detection report to an auditor qualified for auditing. And the auditor sends the vehicle detection report to the display platform for display under the condition that the audit is passed. The display platform may be, but is not limited to, a used car trading platform, an auction platform, and the like. And in the case that the audit is not passed, for example, the picture of the vehicle is not clear (which can be realized by detecting the picture resolution), the historical operation data of the vehicle is not consistent with the normal reason, and the like, returning the vehicle detection report to the detector, and requiring the detector to re-import the correct vehicle condition information. The auditor can also comprehensively grade and score the vehicles to be detected and add the content to the vehicle detection report.
It should be noted that semantic recognition of the vehicle description text, image recognition of the vehicle, and generation of the detection report may be implemented at the client, and the client may also upload the acquired vehicle condition information to the server, and implement generation of the detection report through the server.
FIG. 3 is a flow chart of another vehicle inspection report generation method, shown in an exemplary embodiment of the invention, comprising the steps of:
and 301, acquiring vehicle condition information which is imported by a detection party and aims at the vehicle to be detected.
In this embodiment, a specific implementation manner of obtaining the vehicle condition information is similar to that in step 201, and is not described here again, except that the vehicle condition information in this embodiment includes vehicle characteristic information and a vehicle condition description voice of a vehicle to be detected by a vehicle inspector.
In this embodiment, the vehicle condition speech recognition model may be used to perform speech recognition on the vehicle condition describing speech. The model can be obtained by training the neural network by collecting voice information related to the vehicle description as a voice sample.
In another embodiment, the client may add the vehicle condition description speech imported by the detecting party as a training sample, actively learn the personalized language of the user, such as dialect, special language, and the like, and establish a vehicle condition speech recognition model meeting the personalized requirements of the user.
And 303, performing semantic recognition on the voice recognition text based on the vehicle condition semantic recognition model, and determining a standard vehicle condition description text matched with the voice recognition text.
The specific implementation process of performing semantic recognition on the speech recognition text is similar to that in step 202, and is not described herein again.
And step 304, generating a vehicle detection report according to the vehicle characteristic information and the standard vehicle condition description text.
The specific implementation process of step 304 is similar to step 203, and is not described herein again.
In this embodiment, the inspector can use the voice input mode to describe the vehicle condition of the vehicle to be detected, and the method has extremely high flexibility and convenience.
In another embodiment, the detecting party describes the vehicle to be detected by using a voice mode and a text mode, the vehicle condition information acquired in step 301 includes vehicle feature information, vehicle condition description voice and a vehicle condition description text, in step 303, the voice recognition text and the vehicle condition description text are semantically recognized based on the vehicle condition semantic recognition model, and the specific implementation process is not repeated here.
Corresponding to the vehicle detection report generation method embodiment, the invention also provides an embodiment of a vehicle detection report generation system.
Fig. 4 is a block schematic diagram of a vehicle inspection report generation system according to an exemplary embodiment of the present invention, the vehicle inspection report generation system including: an acquisition module 41, a speech recognition module 42, a semantic recognition module 43, and a report generation module 44.
The obtaining module 41 is configured to obtain vehicle condition information, which is imported by a detecting party and is for a vehicle to be detected, where the vehicle condition information includes a vehicle condition description text and/or a vehicle condition description voice;
the voice recognition module 42 is configured to perform voice recognition on the vehicle condition description voice to obtain a voice recognition text when the vehicle condition information includes the vehicle condition description voice;
the semantic recognition module 43 is configured to perform semantic recognition on the speech recognition text and/or the vehicle condition description text based on a vehicle condition semantic recognition model, and determine a standard vehicle condition description text matching with the speech recognition text and/or the vehicle condition description text, where the vehicle condition semantic recognition model is used to represent a mapping relationship between multiple vehicle condition description texts with the same meaning and the standard vehicle condition description text;
the report generation module 44 generates a vehicle detection report based on the standard vehicle condition description text.
Optionally, the vehicle detection report generation system further includes:
and the auditing module is used for sending the vehicle detection report to an auditing party for auditing, sending the vehicle detection report to a display platform for displaying under the condition that the auditing is passed, and returning the vehicle detection report to the detecting party under the condition that the auditing is not passed.
Optionally, the vehicle detection report generation system further includes:
and the modification module is used for acquiring the historical maintenance information and/or insurance information of the vehicle to be detected, performing text matching on the vehicle detection report according to the historical maintenance information and/or insurance information, and modifying the vehicle detection report according to a matching result.
Optionally, the vehicle detection report generation system further includes:
and the task assignment module is used for assigning the detection task to the detection party according to the vehicle characteristic information and/or the geographical position of the vehicle to be detected carried by the vehicle detection request under the condition of receiving the vehicle detection request sent by the vehicle detection request party so as to lead the detection party to import the vehicle condition information.
Optionally, the vehicle condition information further includes a vehicle picture;
the report generation module is specifically configured to:
and filling the vehicle picture and the standard vehicle condition description text into corresponding areas in a report template, and generating the vehicle detection report.
Optionally, the vehicle detection report generation system further includes:
and the picture processing module is used for carrying out picture identification on the vehicle picture and covering predefined privacy information in the vehicle picture.
Optionally, the report generating module is further configured to:
under the condition of receiving a vehicle detection request sent by a vehicle detection requester, acquiring a corresponding report template according to report use scenes carried by the vehicle detection request, and pre-configuring a corresponding report template for each report use scene;
and extracting target content matched with the corresponding area of the report template from the vehicle picture and the standard vehicle condition description text, and filling the target content into the corresponding area.
Optionally, the vehicle detection report generation system further comprises a model training module for:
acquiring a plurality of groups of text data, wherein each group of text data comprises a vehicle condition description text and a corresponding standard vehicle condition description text, the standard vehicle condition description texts in at least two groups of text data are the same, and the vehicle condition description texts are different but have the same expression meaning;
inputting the vehicle condition description text into a neural network, and determining the difference between the output result of the neural network and the standard vehicle condition description text;
adjusting a network parameter of the neural network based on the difference.
Fig. 5 is a schematic diagram of an electronic device according to an exemplary embodiment of the present invention, and illustrates a block diagram of an exemplary electronic device 50 suitable for implementing embodiments of the present invention. The electronic device 50 shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 5, the electronic device 50 may be embodied in the form of a general purpose computing device, which may be, for example, a server device. The components of the electronic device 50 may include, but are not limited to: the at least one processor 51, the at least one memory 52, and a bus 53 connecting the various system components (including the memory 52 and the processor 51).
The bus 53 includes a data bus, an address bus, and a control bus.
The memory 52 may include volatile memory, such as Random Access Memory (RAM)521 and/or cache memory 522, and may further include Read Only Memory (ROM) 523.
The processor 51 executes various functional applications and data processing, such as the methods provided by any of the above embodiments, by running a computer program stored in the memory 52.
The electronic device 50 may also communicate with one or more external devices 54 (e.g., a keyboard, a pointing device, etc.). Such communication may be through an input/output (I/O) interface 55. Moreover, the model-generated electronic device 50 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via a network adapter 56. As shown, network adapter 56 communicates with the other modules of model-generated electronic device 50 over bus 53. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the model-generating electronic device 50, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.
It should be noted that although in the above detailed description several units/modules or sub-units/modules of the electronic device are mentioned, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the units/modules described above may be embodied in one unit/module according to embodiments of the invention. Conversely, the features and functions of one unit/module described above may be further divided into embodiments by a plurality of units/modules.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method steps provided in any of the above embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A vehicle inspection report generation method, characterized by comprising:
the method comprises the steps that vehicle condition information which is imported by a detection party and aims at a vehicle to be detected is obtained, wherein the vehicle condition information comprises a vehicle condition description text and/or a vehicle condition description voice;
under the condition that the vehicle condition information contains the vehicle condition description voice, performing voice recognition on the vehicle condition description voice to obtain a voice recognition text;
semantic recognition is carried out on the voice recognition text and/or the vehicle condition description text based on a vehicle condition semantic recognition model, and a standard vehicle condition description text matched with the voice recognition text and/or the vehicle condition description text is determined, wherein the vehicle condition semantic recognition model is used for representing the mapping relation between a plurality of vehicle condition description texts with the same semantic meaning and the standard vehicle condition description text;
and generating a vehicle detection report according to the standard vehicle condition description text.
2. The vehicle inspection report generation method according to claim 1, further comprising:
acquiring historical maintenance information and/or insurance information of the vehicle to be detected;
performing text matching on the vehicle detection report according to the historical maintenance information and/or insurance information;
and modifying the vehicle detection report according to the matching result.
3. The vehicle inspection report generation method according to claim 1, further comprising:
under the condition that a vehicle detection request sent by a vehicle detection requester is received, a detection task is assigned to the detection party according to the vehicle characteristic information and/or the geographical position of the vehicle to be detected carried by the vehicle detection request, so that the detection party imports the vehicle condition information.
4. The vehicle inspection report generation method according to claim 1, wherein the vehicle condition information further includes a vehicle picture;
generating a vehicle detection report, comprising:
and filling the vehicle picture and the standard vehicle condition description text into corresponding areas in a report template, and generating the vehicle detection report.
5. The vehicle inspection report generation method of claim 4, further comprising, prior to generating the vehicle inspection report:
and carrying out picture identification on the vehicle picture, and covering predefined privacy information in the vehicle picture.
6. The vehicle inspection report generation method according to claim 4, further comprising:
under the condition of receiving a vehicle detection request sent by a vehicle detection requester, acquiring a corresponding report template according to report use scenes carried by the vehicle detection request, and pre-configuring a corresponding report template for each report use scene;
filling the vehicle picture and the standard vehicle condition description text into corresponding areas in a report template, wherein the corresponding areas comprise:
and extracting target content matched with the corresponding area of the report template from the vehicle picture and the standard vehicle condition description text, and filling the target content into the corresponding area.
7. The vehicle inspection report generation method according to claim 1, further comprising:
acquiring a plurality of groups of text data, wherein each group of text data comprises a vehicle condition description text and a corresponding standard vehicle condition description text, the standard vehicle condition description texts in at least two groups of text data are the same, and the vehicle condition description texts are different but have the same expression meaning;
inputting the vehicle condition description text into a neural network, and determining the difference between the output result of the neural network and the standard vehicle condition description text;
adjusting a network parameter of the neural network based on the difference.
8. A vehicle inspection report generation system, characterized by comprising:
the acquisition module is used for acquiring vehicle condition information which is imported by a detection party and aims at a vehicle to be detected, wherein the vehicle condition information comprises a vehicle condition description text and/or a vehicle condition description voice;
the voice recognition module is used for carrying out voice recognition on the vehicle condition description voice under the condition that the vehicle condition information contains the vehicle condition description voice to obtain a voice recognition text;
the semantic recognition module is used for performing semantic recognition on the voice recognition text and/or the vehicle condition description text based on a vehicle condition semantic recognition model, and determining a standard vehicle condition description text matched with the voice recognition text and/or the vehicle condition description text, wherein the vehicle condition semantic recognition model is used for representing the mapping relation between a plurality of vehicle condition description texts with the same meaning and the standard vehicle condition description text;
and the report generation module is used for generating a vehicle detection report according to the standard vehicle condition description text.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the vehicle detection report generation method of any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the vehicle detection report generation method of any one of claims 1 to 7.
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