CN117253474B - Online examination cheating behavior detection system and detection method based on voice recognition - Google Patents
Online examination cheating behavior detection system and detection method based on voice recognition Download PDFInfo
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L17/00—Speaker identification or verification techniques
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
- G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
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Abstract
The invention relates to the technical field of internet online monitoring, in particular to an online examination cheating behavior detection system and method based on voice recognition; the method comprises the following steps: s1, collecting test paper information, collecting S2 test sound characteristics, identifying S3 test sound, determining a sound vector of an examinee by S4, and identifying S5 cheating behaviors; according to the invention, by constructing the keyword vector, whether the voice sent by the examinee is related to the examination content is rapidly judged, so that whether the examination has a question reading action is judged, after the examination has the question reading action, whether voice information related to the answer of the examination from other people exists is detected, if so, cheating actions that the examination has the question reading action and the answer is transmitted to the examination by other people beyond the view angle of the monitoring camera are determined. The effectiveness of the network invigilation is improved.
Description
Technical Field
The invention relates to the technical field of internet online monitoring, in particular to an online examination cheating behavior detection system and method based on voice recognition.
Background
Computer technology and internet technology are continuously deepened into various aspects of life of people, in the aspect of education, the internet technology gradually influences the development of education modes, and the online teaching mode gradually replaces the traditional classroom education mode to a certain extent; traditional examination modes are also gradually networked, so that great convenience is brought to people.
The networking of the examination brings convenience to teachers and examinees and a plurality of safety problems. On-line examination relies on internet technology and computer technology, and these technologies also provide the warm bed for the examinee to cheat, let the examinee have more cheating modes, for example: searching answers through the internet, searching for help through third party communication tools, etc. by referring to the data in the computer. How to enjoy the convenience of the examination, the problems of effectively preventing cheating of examinees and guaranteeing fairness and fairness of the examination need to be solved, so that the examination monitoring system becomes an important research topic.
The examination invigilating system mainly adopts a mode of combining video monitoring and manual invigilation, monitors examination of an examinee by installing a camera in an examination room or using a computer-side camera of the examinee, and then arranges invigilator invigilating pictures of the video side of the invigilating in the background in real time. An invigorator may need to pay attention to several tens of examination pictures at the same time, and although the examination pictures can prevent cheating of the examinee to a certain extent, the invigorator needs to consume great effort, and people need to judge which pictures have cheating behaviors, so that the workload is great, and certain cheating behaviors are difficult to find.
Especially for the low-sound questions of the examinee, other people can not easily and effectively recognize the cheating mode of giving out answers outside the view angle of the invigilation camera.
In the prior art, the technical means for detecting the cheating behavior by utilizing the video technology also exist:
the Chinese patent with publication number of CN112464793A discloses a method, a system and a storage medium for detecting cheating behaviors in online examination, and particularly discloses that a corrected face is taken as input, and a vision prediction model is used for predicting the vision direction of an examinee; and within the threshold value of the line of sight deviation time, if the line of sight angle of the examinee exceeds the threshold value of the line of sight deviation angle in more than half of the time, alarming. The invention uses the sight tracking technology to detect cheating behaviors of testees and can identify more cheating conditions. However, the prior art only proposes detection for the sight line deviation from the concept, does not specifically disclose how to detect, and the mentioned algorithm of the prior art has high requirement on calculation force and insufficient convenience; in addition, the prior art discloses a method for starting a pedestrian detection algorithm, judging whether a multi-person situation occurs in a picture, detecting the multi-person situation and alarming, and does not disclose a technical means of how to detect irrelevant persons in an examination area based on a plurality of cameras aiming at the situation that pedestrians abnormally intrude into the examination area; in addition, the prior art directly detects whether the deviation of the sight line angle of the examinee exceeds a threshold value of 12 degrees, the criterion of the constant value algorithm is single, and the misjudgment probability is high for scenes with different examination habits and different examination requirements.
Similarly, the chinese patent with publication number CN111539313a discloses a method and a system for detecting cheating behavior in examination, and specifically discloses collecting the region right in front of the examinee to obtain video data; then, according to the visual line moving range of the examinee and/or according to the video data analysis, the cheating behavior detection result is obtained, but the improvement on how to detect the abnormal behavior of the examinee is not provided from the algorithm level, and the problems of high requirements on hardware equipment and computing power and low applicability due to the dependence on the existing algorithm are also existed.
Disclosure of Invention
In order to solve the technical problem that cheating of testees cannot be accurately found due to online examination, the invention provides the following technical scheme:
a voice recognition-based online examination cheating behavior detection method comprises the following steps:
s1, collecting test paper information; grabbing test question text { (QW) i { (AW) and answer text i Establishing a test question answer corresponding table; wherein (QW) i Test question keywords (AW) representing the ith test question i Answer keywords for the ith test question are represented;
s2, collecting examination sound characteristics; the method comprises the steps that an examinee reads a given voice text according to requirements, an audio acquisition device acquires examinee voice characteristics { V }, wherein the voice characteristics { V } at least comprise loudness, tone, word interval, fundamental frequency and formants;
s3, examination voice recognition: collecting voice information in the examination process, and identifying the voice of the examinee based on the voice characteristics { V };
s4, determining a sound vector of the examinee; breaking sentences of test voice, capturing keywords in test of the identified test voice, latin alphabeticzing the keywords in test, determining ASCII codes according to an ASCII code table, and establishing ASCII code vectors in testMeanwhile, recognizing keywords of non-examinee voice, carrying out Latin alphabetization and determining ASCII codes of the keywords, and establishing ASCII code vectors in other tests>Wherein j and k are sentence-breaking subscripts respectively,ASCII code vector representing the keyword of the jth sentence in the examinee's voice, ++>ASCII code vector of the key word representing the kth sentence in the non-examinee voice;
s5, identifying cheating behaviors; based on the test question ASCII code vector setThe answer ASCII code vector set +.>ASCII code vector in test question answer corresponding table and test taker test>And other trial ASCII code vectors +.>The cheating behavior is identified.
Further, the step S1 includes:
s11, keyword (QW) of the ith test question i And answer keywords (AW) of the ith test question i Carrying out Latin alphabetization;
s12, based on an ASCII code comparison table, obtaining ASCII code sequences of Latin alphabetical keywords, establishing ASCII code sequence vectors based on the ASCII code sequences, and respectively obtaining test question ASCII code vector setsAnd answer ASCII code vector set->Wherein i is the subscript of the test question serial number, < ->And->Respectively representing test question ASCII code vectors and answer ASCII code vectors of the ith test questions;
s13, the test question ASCII code vector setSum answer ASCII code vector setAnd establishing a corresponding relation to obtain a test question answer corresponding table.
Further, the step S5 includes:
s51, grabbing ASCII code vector in testASCII code vector set for test questionsComparing, and determining whether a corresponding relation exists; if not, judging that no cheating behavior exists, and carrying out next round of detection; if yes, go to step S52;
s52, ASCII code vector set from test questionsASCII code vector in middle determination and test takerCorresponding test question ASCII code vector +.>Finding out the ASC corresponding to the test question based on the answer corresponding table of the test questionII code vector->Corresponding answer ASCII code vector->
S53, grabbing other ASCII code vectors in the testAnd the answer ASCII code vectorComparing, and judging whether the vector difference is larger than a preset threshold value; if yes, judging that no cheating behavior exists, and carrying out next round of detection; if yes, judging that cheating behaviors exist, and sending warning information to prison staff.
Further, the ASCII code is a standard ASCII code table.
Further, the ASCII code is an extended ASCII code table.
Further, the voice text in the step S2 includes keywords appearing in the test questions.
Further, the voice text in the step S2 includes keywords appearing in the answer.
The invention also provides an online examination cheating behavior detection system based on voice recognition, which comprises a computer-side camera, a voice acquisition module, a voice recognition module, a comparison module and a warning module;
the voice acquisition module is used for acquiring sound;
the voice recognition module is used for recognizing examinee voice and other voices;
the comparison module is used for carrying out cheating behavior identification;
the warning module is used for sending warning information to prisoner after detecting the cheating behavior.
The beneficial effects of the invention are as follows:
1. the invention recognizes the voice of the examination staff through the voice voiceprint characteristics, and avoids cheating misjudgment caused by low-voice question reading of the examinee.
2. According to the invention, by constructing the keyword vector, whether the voice sent by the examinee is related to the examination content is rapidly judged, so that whether the examination has a question reading action is judged, after the examination has the question reading action, whether voice information related to the answer of the examination from other people exists is detected, if so, cheating actions that the examination has the question reading action and the answer is transmitted to the examination by other people beyond the view angle of the monitoring camera are determined. The effectiveness of the network invigilation is improved.
3. The invention adopts the keyword vector method to detect, and can effectively aim at the 'simple reading' behavior in the examination cheating, namely, the behavior that examinees and answer transferring staff only read part of examination information in order to improve the efficiency and avoid being found.
4. After detecting abnormal behaviors of the examinee and the possibility of cheating, the invention notifies the prisoner to confirm; the misjudgment of the examinee due to equipment problems can be further prevented, meanwhile, the manpower can be greatly saved, and the pressure of the invigilator is reduced.
Drawings
Fig. 1 is a schematic flow chart of an online examination cheating behavior detection method based on voice recognition in the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
The embodiment discloses an online examination cheating behavior detection method based on voice recognition, which comprises the following steps:
s1, collecting test paper information; grabbing test question text { (QW) i { (AW) and answer text i Establishing a test question answer corresponding table; wherein (QW) i Test question keywords (AW) representing the ith test question i Answer keywords for the ith test question are represented;
s2, collecting examination sound characteristics; the method comprises the steps that an examinee reads a given voice text according to requirements, an audio acquisition device acquires examinee voice characteristics { V }, wherein the voice characteristics { V } at least comprise loudness, tone, word interval, fundamental frequency and formants;
s3, examination voice recognition: collecting voice information in the examination process, and identifying the voice of the examinee based on the voice characteristics { V };
s4, determining a sound vector of the examinee; breaking sentences of test voice, grabbing keywords in test of the identified test voice, latin alphabeticzing the keywords in test, determining ASCII codes according to the ASCII codes, and establishing ASCII code vectors in testMeanwhile, identifying test keywords of non-examinee voice, carrying out Latin alphabetization and determining ASCII codes of the test keywords, and establishing ASCII code vectors in other tests>Wherein j and k are sentence-breaking subscripts respectively,ASCII code vector representing the keyword of the jth sentence in the examinee's voice, ++>ASCII code vector of the key word representing the kth sentence in the non-examinee voice;
s5, identifying cheating behaviors; based on the test question ASCII code vector setThe answer ASCII code vector set +.>ASCII code vector in test question answer corresponding table and test taker test>And other trial ASCII code vectors +.>The cheating behavior is identified.
Further, the step S1 includes:
s11, keyword (QW) of the ith test question i And answer keywords { (AW) of the ith test question i Latin alphabetization;
s12, based on an ASCII code comparison table, obtaining ASCII code sequences of Latin alphabetical keywords, establishing ASCII code sequence vectors based on the ASCII code sequences, and respectively obtaining test question ASCII code vector setsAnd answer ASCII code vector set->Wherein i is the subscript of the test question serial number, < ->And->Respectively representing test question ASCII code vectors and answer ASCII code vectors of the ith test questions;
s13, the test question ASCII code vector setSum answer ASCII code vector setAnd establishing a corresponding relation to obtain a test question answer corresponding table.
Further, the step S5 includes:
s51, grabbing ASCII code vector in testASCII code vector set for test questionsComparing, and determining whether a corresponding relation exists; if not, judging that no cheating behavior exists, and carrying out next round of detection; if yes, go to step S52;
s52, ASCII code vector set from test questionsASCII code vector in middle determination and test takerCorresponding test question ASCII code vector +.>Based on the answer correspondence table of the test question, finding the ASCII code vector +.>Corresponding answer ASCII code vector->
S53, grabbing other ASCII code vectors in the testAnd the answer ASCII code vectorComparing, and judging whether the vector difference is larger than a preset threshold value; if yes, judging that no cheating behavior existsCarrying out next round of detection; if yes, judging that cheating behaviors exist, and sending warning information to prison staff.
Further, the ASCII code is a standard ASCII code table.
Further, the ASCII code is an extended ASCII code table.
Further, the voice text in the step S2 includes keywords appearing in the test questions.
Further, the voice text in the step S2 includes keywords appearing in the answer.
Example 2
The system for realizing the online examination cheating behavior detection based on voice recognition comprises a computer-side camera, a voice acquisition module, a voice recognition module, a comparison module and a warning module;
the voice acquisition module is used for acquiring sound;
the voice recognition module is used for recognizing examinee voice and other voices;
the comparison module is used for carrying out cheating behavior identification;
the warning module is used for sending warning information to prisoner after detecting the cheating behavior.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (7)
1. The online examination cheating behavior detection method based on voice recognition is characterized by comprising the following steps of:
s1, collecting test paper information; grabbing test question text { (QW) i { (AW) and answer text i Establishing a test question answer corresponding table; wherein (QW) i Test question keywords (AW) representing the ith test question i Answer keywords for the ith test question are represented;
s2, collecting examination sound characteristics; the method comprises the steps that an examinee reads a given voice text according to requirements, an audio acquisition device acquires examinee voice characteristics { V }, wherein the voice characteristics { V } at least comprise one or more of loudness, tone, word interval, fundamental frequency and formants;
s3, voice recognition of the examination; collecting voice information in the examination process, and identifying the voice of the examinee based on the voice characteristics { V };
s4, determining a sound vector of the examinee; breaking sentences of test voice, grabbing keywords in test of the identified test voice, latin alphabeticzing the keywords in test, determining ASCII codes according to the ASCII codes, and establishing ASCII code vectors in testMeanwhile, identifying test keywords of non-examinee voice, carrying out Latin alphabetization and determining ASCII codes of the test keywords, and establishing ASCII code vectors of the test keywords +.>Wherein j and k are each a punctuation subscript,/-, respectively>ASCII code vector representing the keyword of the jth sentence in the examinee's voice, ++>ASCII code vector of the key word representing the kth sentence in the non-examinee voice;
s5, identifying cheating behaviors; based on the test question ASCII code vector setThe answer ASCII code vector set +.>ASCII code vector in test question answer corresponding table and test taker test>And other trial ASCII code vectors +.>Identifying a cheating behavior;
the step S5 includes:
s51, grabbing ASCII code vector in testAnd test question ASCII code vector set +.>Comparing, and determining whether a corresponding relation exists; if not, judging that no cheating behavior exists, and carrying out next round of detection; if yes, go to step S52;
s52, ASCII code vector set from test questionsASCII code vector in middle determination and test takerCorresponding test question ASCII code vector +.>Based on the answer correspondence table of the test question, finding the ASCII code vector +.>Corresponding answer ASCII code vector->
S53, grabbing other ASCII code vectors in the testMix it with the answer ASCIII code vector->Comparing, and judging whether the vector difference is larger than a preset threshold value; if yes, judging that no cheating behavior exists, and carrying out next round of detection; if yes, judging that cheating behaviors exist, and sending warning information to prison staff.
2. The method for detecting online examination cheating behavior based on voice recognition according to claim 1, wherein the step S1 comprises:
s11, keyword (QW) of the ith test question i And answer keywords (AW) of the ith test question i Carrying out Latin alphabetization;
s12, based on an ASCII code comparison table, obtaining ASCII code sequences of Latin alphabetical keywords, establishing ASCII code sequence vectors based on the ASCII code sequences, and respectively obtaining test question ASCII code vector setsAnd answer ASCII code vector set->Wherein i is the subscript of the test question serial number, < ->And->Respectively representing test question ASCII code vectors and answer ASCII code vectors of the ith test questions;
s13, the test question ASCII code vector setSum answer ASCII code vector setAnd establishing a corresponding relation to obtain a test question answer corresponding table.
3. The method for detecting online examination cheating behavior based on voice recognition according to claim 1, wherein the ASCII code is a standard ASCII code table.
4. The method for detecting online examination cheating behavior based on voice recognition according to claim 1, wherein the ASCII code is an extended ASCII code table.
5. The method for detecting online test cheating behavior based on voice recognition according to claim 3 or 4, wherein the voice text in the step S2 includes keywords appearing in the test questions.
6. The method for detecting online test cheating behavior based on voice recognition according to claim 3 or 4, wherein the voice text in the step S2 includes keywords appearing in the answer.
7. An online examination cheating behavior detection system based on voice recognition is used for realizing the online examination cheating behavior detection method based on voice recognition according to any one of claims 1-6, and is characterized by comprising a computer-side camera, a voice acquisition module, a voice recognition module, a comparison module and a warning module;
the voice acquisition module is used for acquiring sound;
the voice recognition module is used for recognizing examinee voice and other voices;
the comparison module is used for carrying out cheating behavior identification;
the warning module is used for sending warning information to prisoner after detecting the cheating behavior.
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