CN113010707A - Homework correcting method and device and electronic equipment - Google Patents
Homework correcting method and device and electronic equipment Download PDFInfo
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Abstract
The invention provides a homework correcting method, a homework correcting device and electronic equipment, wherein after a homework image uploaded by a student is obtained, a text line of the homework image can be detected by utilizing a neural network model, and a print character text line and a handwritten character text line of the homework image are determined; and then the homework image with the determined text line is respectively input into a first font recognition model and a second font recognition model, the print character text line and the handwritten character text line in the homework image are recognized, the recognized print character text line in the homework image is determined as a homework topic, and the recognized handwritten character text line in the homework image is determined as a student homework topic answer, so that the homework uploaded by students is automatically corrected, a teacher does not need to manually correct a large amount of homework, and a large amount of correction homework time is saved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for correcting a job and electronic equipment.
Background
At present, with the progress of internet technology and the development of scientific technology, artificial intelligence can provide more and more help for life and reduce the burden of people, in a teaching scene, the homework correction is a very time-consuming and labor-consuming matter, a teacher often manages dozens or even hundreds of students, the homework correction is hard every day, one homework often takes several days to be corrected, the mistake can not be annotated every time after the homework correction is finished, and the problems that the students do homework in a family scene and parents also have difficulty in correcting homework for children exist.
Disclosure of Invention
In order to solve the above problems, embodiments of the present invention provide a method and an apparatus for batch modification of jobs, and an electronic device.
In a first aspect, an embodiment of the present invention provides a job approval method, including:
acquiring homework images uploaded by students;
detecting a text line of the operation image by using a neural network model, and determining the text line of the operation image; wherein the text line comprises: a line of print character text and a line of handwritten character text;
respectively inputting the work image with the determined text line into a first font recognition model and a second font recognition model, and recognizing characters in the text line of the print font characters and characters in the text line of the handwriting font characters in the work image;
determining characters in the identified text lines of the print characters in the homework image as homework questions, and determining characters in the text lines of the handwriting characters in the identified homework image as answers of the homework questions of students;
and finding out the correct answer of the homework title from the question bank by using the homework title, and comparing the found correct answer of the homework title with the determined answer of the homework title of the student, so as to judge the right and wrong answers of the homework title of the student and obtain the correction result of the homework image.
In a second aspect, an embodiment of the present invention further provides a job approval apparatus, including:
the acquisition module is used for acquiring the homework images uploaded by students;
the determining module is used for detecting the text line of the operation image by utilizing a neural network model and determining the text line of the operation image; wherein the text line comprises: a line of print character text and a line of handwritten character text;
the processing module is used for respectively inputting the work image with the determined text line into the first font recognition model and the second font recognition model and recognizing the characters in the text line of the print font characters and the characters in the text line of the hand-written font characters in the work image;
the recognition module is used for determining the characters in the identified print character text lines in the operation image as operation questions and determining the characters in the identified handwritten character text lines in the operation image as operation question answers of students;
and the correction module is used for finding out the correct answer of the homework title from the question bank by using the homework title, and comparing the found correct answer of the homework title with the confirmed answer of the homework title of the student, so that the correct and wrong answers of the homework title of the student are judged, and the correction result of the homework image is obtained.
In a third aspect, the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the method in the first aspect.
In a fourth aspect, embodiments of the present invention also provide an electronic device, which includes a memory, a processor, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor to perform the steps of the method according to the first aspect.
In the solutions provided in the first to fourth aspects of the embodiments of the present invention, after obtaining the homework image uploaded by the student, the text line of the homework image may be detected by using a neural network model, so as to determine the print character text line and the handwritten character text line of the homework image; and then the homework images with the determined text lines are respectively input into a first font recognition model and a second font recognition model, the print character text lines and the handwritten character text lines in the homework images are recognized, the recognized print character text lines in the homework images are determined as homework topics, and the recognized handwritten character text lines in the homework images are determined as answers of the homework topics of students, so that the homework uploaded by the students is automatically corrected.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart illustrating a job modification method according to embodiment 1 of the present invention;
fig. 2 is a schematic structural diagram illustrating a job modification apparatus according to embodiment 2 of the present invention;
fig. 3 shows a schematic structural diagram of an electronic device provided in embodiment 3 of the present invention.
Detailed Description
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
At present, with the progress of internet technology and the development of scientific technology, artificial intelligence can provide more and more help for life and reduce the burden of people, in a teaching scene, the homework correction is a very time-consuming and labor-consuming matter, a teacher often manages dozens or even hundreds of students, the homework correction is hard every day, one homework often takes several days to be corrected, the mistake can not be annotated every time after the homework correction is finished, and the problems that the students do homework in a family scene and parents also have difficulty in correcting homework for children exist.
Based on this, embodiments of the application provide a method, a device and an electronic device for homework approval, after a homework image uploaded by a student is acquired, a text line of the homework image can be detected by using a neural network model, and a print character text line and a handwritten character text line of the homework image are determined; and then the homework image with the determined text line is respectively input into a first font recognition model and a second font recognition model, the print character text line and the handwritten character text line in the homework image are recognized, the recognized print character text line in the homework image is determined as a homework topic, and the recognized handwritten character text line in the homework image is determined as a student homework topic answer, so that the homework uploaded by students is automatically corrected, a teacher does not need to manually correct a large amount of homework, and a large amount of correction homework time is saved.
The scene that this application is applicable to clapping and changes is the calculation of a mouth and teaching and supplementary, and after the student finishes answering and uploads the homework result, the automatic homework of correcting of server and output correcting result, very big alleviate mr, head of a family and student's homework correcting burden.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
Example 1
In the job modification method provided by this embodiment, the execution main body is a server.
Referring to a flowchart of a job modification method shown in fig. 1, the present embodiment provides a job modification method, including the following specific steps:
and step 100, acquiring homework images uploaded by students.
In the above step 100, the student may upload the homework image to the server in the following various ways.
1: and (4) shooting, recording and uploading, namely recording the operation of the user in a mode of shooting through a mobile phone or a pad camera to obtain an operation image, and uploading the operation image to the server.
2: and the dot matrix pen records and uploads, the students normally write and note the notes by the dot matrix technology, and the dot matrix pen instantly electronizes the writing content of the paper pen to generate a homework image and uploads the homework image to the server.
3: and the scanner records and uploads, the written job is put into the scanner, a job image is obtained through a scanning technology, and the obtained job image is uploaded to the server.
4: and voice recording and uploading, wherein students say the homework content, then use Kaldi to extract acoustic features, use WFST to realize a decoding algorithm, and after the feature extraction is completed, the normalized features can be obtained through an acoustic feature form flat.scp and a cepstrum mean variance normalization coefficient form cmvn.scp in a data folder. The method comprises the steps of forming all possible paths of text pronunciation according to a statistical training text corpus, forming a large search graph by combining the paths and a pronunciation dictionary, obtaining the probability of phonemes by a voice characteristic through a neural network, carrying out Viterbi search on the probabilities of continuous frames in the large search graph to finally obtain a recognized text, generating a text image from the recognized text, and uploading the text image to a server.
5: and (3) inputting, inputting and uploading on line, inputting the text in a mode of inputting the job content by a computer to obtain a job image, and uploading the obtained job image to a server.
The homework image carries the name of the student and the class identification of the class in which the student is located.
In step 102, detecting the text line of the job image by using the neural network model, and determining the text line of the job image is the prior art, and is not described herein again.
And when the text line of the job image is determined, the position information of the text line of the job image can be obtained.
And the position information of the text line of the job image is the end point information of four end points of the text line of the job image.
The position information of the text line of the job image comprises: position information of text lines of print characters and position information of text lines of handwritten characters.
And 104, respectively inputting the work image with the determined text line into the first font recognition model and the second font recognition model, and recognizing the characters in the text line of the print font characters and the characters in the text line of the handwriting font characters in the work image.
In step 104, the job image with the text line determined is input into the first font identification model and the second font identification model, and the process of identifying the text in the print font character text line and the text in the handwritten character text line in the job image is the prior art, and is not described herein again.
And the first font identification model is used for identifying the characters of the printed style.
And the second font recognition model is used for recognizing the handwritten characters.
After identifying the print character text lines and the handwritten character text lines in the job image, the following steps may be continued to remove background information between the job title and the student's job title answer:
(1) determining the position relation between the homework questions and the answers of the student homework questions;
(2) and removing background information between the homework questions and the answers of the student homework questions according to the determined position relation between the homework questions and the answers of the student homework questions.
In the step (1), the position information of the text line of the print characters can be determined as the position information of the job title; determining the position information of the text line of the handwritten characters as the position information of the answer of the homework question of the student; and then determining the position relation between the homework questions and the answers of the student homework questions according to the position information of the homework questions and the position information of the answers of the student homework questions.
The specific process of determining the position relationship between the homework questions and the answers of the student homework questions according to the position information of the homework questions and the position information of the answers of the student homework questions is the prior art, and is not repeated here.
In the step (2), according to the determined position relationship between the homework topic and the student homework topic answer, the background information between the homework topic and the student homework topic answer can be obtained, and then the background information between the homework topic and the student homework topic answer can be removed by using any existing background removal technology in the image processing technology, wherein the specific process is the prior art and is not described herein again.
After the background information between the assignment topic and the student's assignment topic answer is removed, execution continues at step 106.
And 106, determining the characters in the identified print character text line in the homework image as a homework subject, and determining the characters in the identified handwritten character text line in the homework image as a student homework subject answer.
And 108, finding out the correct answer of the homework title from the question bank by using the homework title, and comparing the found correct answer of the homework title with the confirmed answer of the homework title of the student, so as to judge the right and wrong answers of the homework title of the student and obtain the correction result of the homework image.
In step 108, the question bank stores the job question and the correct answer to the job question.
After the homework is modified, the condition of the homework can be counted according to the following processes:
(1) acquiring a correction result of the job images with the same class identification;
(2) counting the number of students with wrong homework subjects in the homework images with the same class identification;
(3) and feeding back the homework subjects with the number of wrongly made students in each homework subject reaching the number threshold value as the homework subjects to be explained to the teachers, so that the teachers explain the students about the homework subjects to be explained.
In summary, according to the homework approval method provided in this embodiment, after the homework image uploaded by the student is acquired, the text line of the homework image may be detected by using the neural network model, and the print character text line and the handwritten character text line of the homework image are determined; and then the homework images with the determined text lines are respectively input into a first font recognition model and a second font recognition model, the print character text lines and the handwritten character text lines in the homework images are recognized, the recognized print character text lines in the homework images are determined as homework topics, and the recognized handwritten character text lines in the homework images are determined as answers of the homework topics of students, so that the homework uploaded by the students is automatically corrected.
Example 2
Referring to fig. 2, a schematic structural diagram of a job correction device is shown, in this embodiment, a job correction device is provided, including:
the acquisition module 200 is used for acquiring homework images uploaded by students;
a determining module 202, configured to detect a text line of the job image by using a neural network model, and determine the text line of the job image; wherein the text line comprises: a line of print character text and a line of handwritten character text;
the processing module 204 is configured to input the job image with the determined text line into the first font recognition model and the second font recognition model, respectively, and recognize the text in the print font character text line and the text in the handwritten character text line in the job image;
the recognition module 206 is configured to determine the recognized characters in the text lines of the print characters in the job image as job titles, and determine the recognized characters in the text lines of the handwritten characters in the job image as answers of the job titles of students;
the correcting module 208 finds the correct answer of the homework topic from the topic library by using the homework topic, and compares the found correct answer of the homework topic with the determined answer of the homework topic of the student, so as to judge whether the answer of the homework topic of the student is wrong, and obtain a correcting result of the homework image.
Optionally, the apparatus further comprises:
the determining unit is used for determining the position relation between the homework topic and the answer of the student's homework topic;
and the processing unit is used for removing the background information between the homework topic and the student homework topic answer according to the determined position relationship between the homework topic and the student homework topic answer.
Optionally, the apparatus, the assignment image, includes a class identification of a class in which the student is located;
the device, still include:
an acquisition unit configured to acquire a revision result of the job images having the same class identification;
the statistical unit is used for counting the number of students with wrong homework subjects in the homework images with the same class identification;
and the feedback unit is used for feeding back the homework questions with the number of wrongly made students in each homework question reaching the number threshold value as the homework questions to be explained to the teacher, so that the teacher explains the homework questions to be explained to the students.
In summary, in the homework approval apparatus provided in this embodiment, after the homework image uploaded by the student is acquired, the neural network model may be used to detect the text line of the homework image, so as to determine the print character text line and the handwritten character text line of the homework image; and then the homework images with the determined text lines are respectively input into a first font recognition model and a second font recognition model, the print character text lines and the handwritten character text lines in the homework images are recognized, the recognized print character text lines in the homework images are determined as homework topics, and the recognized handwritten character text lines in the homework images are determined as answers of the homework topics of students, so that the homework uploaded by the students is automatically corrected.
Example 3
The present embodiment proposes a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the job batching method described in embodiment 1 above. For specific implementation, refer to method embodiment 1, which is not described herein again.
In addition, referring to the schematic structural diagram of an electronic device shown in fig. 3, the present embodiment further provides an electronic device, where the electronic device includes a bus 51, a processor 52, a transceiver 53, a bus interface 54, a memory 55, and a user interface 56. The electronic device comprises a memory 55.
In this embodiment, the electronic device further includes: one or more programs stored on the memory 55 and executable on the processor 52, configured to be executed by the processor for performing the following steps (1) to (5):
(1) acquiring homework images uploaded by students;
(2) detecting a text line of the operation image by using a neural network model, and determining the text line of the operation image; wherein the text line comprises: a line of print character text and a line of handwritten character text;
(3) respectively inputting the work image with the determined text line into a first font recognition model and a second font recognition model, and recognizing characters in the text line of the print font characters and characters in the text line of the handwriting font characters in the work image;
(4) determining characters in the identified text lines of the print characters in the homework image as homework questions, and determining characters in the text lines of the handwriting characters in the identified homework image as answers of the homework questions of students;
(5) and finding out the correct answer of the homework title from the question bank by using the homework title, and comparing the found correct answer of the homework title with the determined answer of the homework title of the student, so as to judge the right and wrong answers of the homework title of the student and obtain the correction result of the homework image.
A transceiver 53 for receiving and transmitting data under the control of the processor 52.
Where a bus architecture (represented by bus 51) is used, bus 51 may include any number of interconnected buses and bridges, with bus 51 linking together various circuits including one or more processors, represented by processor 52, and memory, represented by memory 55. The bus 51 may also link various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further in this embodiment. A bus interface 54 provides an interface between the bus 51 and the transceiver 53. The transceiver 53 may be one element or may be multiple elements, such as multiple receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. For example: the transceiver 53 receives external data from other devices. The transceiver 53 is used for transmitting data processed by the processor 52 to other devices. Depending on the nature of the computing system, a user interface 56, such as a keypad, display, speaker, microphone, joystick, may also be provided.
The processor 52 is responsible for managing the bus 51 and the usual processing, running a general-purpose operating system as described above. And memory 55 may be used to store data used by processor 52 in performing operations.
Alternatively, processor 52 may be, but is not limited to: a central processing unit, a singlechip, a microprocessor or a programmable logic device.
It will be appreciated that the memory 55 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 55 of the systems and methods described in this embodiment is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 55 stores elements, executable modules or data structures, or a subset thereof, or an expanded set thereof as follows: an operating system 551 and application programs 552.
The operating system 551 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, for implementing various basic services and processing hardware-based tasks. The application 552 includes various applications, such as a Media Player (Media Player), a Browser (Browser), and the like, for implementing various application services. A program implementing the method of an embodiment of the present invention may be included in the application 552.
In summary, the present embodiment provides a computer-readable storage medium and an electronic device, after a homework image uploaded by a student is acquired, a neural network model may be used to detect a text line of the homework image, so as to determine a print character text line and a handwritten character text line of the homework image; and then the homework images with the determined text lines are respectively input into a first font recognition model and a second font recognition model, the print character text lines and the handwritten character text lines in the homework images are recognized, the recognized print character text lines in the homework images are determined as homework topics, and the recognized handwritten character text lines in the homework images are determined as answers of the homework topics of students, so that the homework uploaded by the students is automatically corrected.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (8)
1. A job approval method, comprising:
acquiring homework images uploaded by students;
detecting a text line of the operation image by using a neural network model, and determining the text line of the operation image; wherein the text line comprises: a line of print character text and a line of handwritten character text;
respectively inputting the work image with the determined text line into a first font recognition model and a second font recognition model, and recognizing characters in the text line of the print font characters and characters in the text line of the handwriting font characters in the work image;
determining characters in the identified text lines of the print characters in the homework image as homework questions, and determining characters in the text lines of the handwriting characters in the identified homework image as answers of the homework questions of students;
and finding out the correct answer of the homework title from the question bank by using the homework title, and comparing the found correct answer of the homework title with the determined answer of the homework title of the student, so as to judge the right and wrong answers of the homework title of the student and obtain the correction result of the homework image.
2. The method of claim 1, further comprising, after the step of determining the identified lines of text of the print characters in the image of the assignment as assignments topics and the identified lines of text of the handwritten characters in the image of the assignment as assignments answers to assignments topics for students:
determining the position relation between the homework questions and the answers of the student homework questions;
and removing background information between the homework questions and the answers of the student homework questions according to the determined position relation between the homework questions and the answers of the student homework questions.
3. The method of claim 1, wherein the assignment image includes a class identification of a class in which the student is located;
the method further comprises the following steps:
acquiring a correction result of the job images with the same class identification;
counting the number of students with wrong homework subjects in the homework images with the same class identification;
and feeding back the homework subjects with the number of wrongly made students in each homework subject reaching the number threshold value as the homework subjects to be explained to the teachers, so that the teachers explain the students about the homework subjects to be explained.
4. An operation approval apparatus comprising:
the acquisition module is used for acquiring the homework images uploaded by students;
the determining module is used for detecting the text line of the operation image by utilizing a neural network model and determining the text line of the operation image; wherein the text line comprises: a line of print character text and a line of handwritten character text;
the processing module is used for respectively inputting the work image with the determined text line into the first font recognition model and the second font recognition model and recognizing the characters in the text line of the print font characters and the characters in the text line of the hand-written font characters in the work image;
the recognition module is used for determining the characters in the identified print character text lines in the operation image as operation questions and determining the characters in the identified handwritten character text lines in the operation image as operation question answers of students;
and the correction module is used for finding out the correct answer of the homework title from the question bank by using the homework title, and comparing the found correct answer of the homework title with the confirmed answer of the homework title of the student, so that the correct and wrong answers of the homework title of the student are judged, and the correction result of the homework image is obtained.
5. The apparatus of claim 4, further comprising:
the determining unit is used for determining the position relation between the homework topic and the answer of the student's homework topic;
and the processing unit is used for removing the background information between the homework topic and the student homework topic answer according to the determined position relationship between the homework topic and the student homework topic answer.
6. The apparatus of claim 4, wherein the assignment image includes a class identification of a class in which the student is located;
the device, still include:
an acquisition unit configured to acquire a revision result of the job images having the same class identification;
the statistical unit is used for counting the number of students with wrong homework subjects in the homework images with the same class identification;
and the feedback unit is used for feeding back the homework questions with the number of wrongly made students in each homework question reaching the number threshold value as the homework questions to be explained to the teacher, so that the teacher explains the homework questions to be explained to the students.
7. 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 method according to any one of the claims 1-3.
8. An electronic device comprising a memory, a processor, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor to perform the steps of the method of any of claims 1-3.
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