CN109670395A - A kind of student's focus monitoring method based on artificial intelligence - Google Patents
A kind of student's focus monitoring method based on artificial intelligence Download PDFInfo
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- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
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Abstract
Student's focus monitoring method based on artificial intelligence that the invention discloses a kind of characterized by comprising S1: the personal information of student, student and the face information of teacher and voice print matching are recorded in artificial intelligence platform；S2: the image and audio during student listens to the teacher are acquired；S3: pass through student's Image Acquisition student's action message；S4: student is acquired by student audio and is called the roll the time reacted to student by teacher；S5: collected every terms of information is for statistical analysis, and after discovery focus low student, Xiang Jiaoshi sends a warning；The present invention make teacher at school when do not need to spend a lot of time student reminded to listen to the teacher, ensure that teachers' instruction progress can carry out according to plan；The single problem of condition needed for overcoming monitoring focus, can comprehensively judge the focus of student；Also allow teacher teacher oneself determine when to remind theolog, ensure that the rhythm of attending class of teacher is not disturbed.
Description
Technical field
The present invention relates to teaching management field, especially a kind of student's focus monitoring method based on artificial intelligence.
Background technique
In classroom, teacher for classroom progress all carry out more rapidly, be easy to lose if attention of student is not concentrated
Leak important knowledge point；And teacher at school during, all scatterbrained students are hardly noticed, if teacher exists
The student that power is not concentrated often is pointed out during having gone up, the progress of attending class can be seriously affected；And pass through artificial intelligence technology
The real-time status that can effectively monitor each student that attends class can notify teacher when there is the too low student of focus in time,
Reduce the time of teacher position classroom discipline.
In the prior art, have by recognition of face carry out focus monitoring technical solution, the technical solution by whether
It can identify that complete face information judges that focus, this method have large error in monitoring and monitor reference quantity excessively
It is single, do not account for other external conditions.
Summary of the invention
Goal of the invention of the invention is: in view of the above problems, it is special to provide a kind of student based on artificial intelligence
Note degree monitoring method.The present invention solves the problems, such as that teacher cannot be concerned about the focus of each student；Also solve judgement
The more single problem of focus condition.
The technical solution adopted by the invention is as follows:
A kind of student's focus monitoring method based on artificial intelligence characterized by comprising
S1: the personal information of student, student and the face information of teacher and voice print matching are recorded in artificial intelligence platform；
S2: the image and audio during student listens to the teacher are acquired；
S3: pass through student's Image Acquisition student's action message；
S4: student is acquired by student audio and is called the roll the time reacted to student by teacher；
S5: collected every terms of information is for statistical analysis, and after discovery focus low student, Xiang Jiaoshi sounds an alarm letter
Breath.
Further, in step S1, student's personal information includes: name, gender, class and teacher.
Further, in step S2, the image acquired during student listens to the teacher and audio include:
S201: student's image is taken out by video file catching；
S202: the audio-frequency information in video file is extracted；
S203: the sound of teacher in the audio-frequency information extracted and student's sound are subjected to classification marker；
S204: the vocal print of the student marked and the student's vocal print being recorded in platform are compared, match is found
It is raw.
Further, in step S3, acquisition student's action message includes: acquisition student's rotary head number and rotary head amplitude
Data, acquisition student bow come back number data, acquire student's number of winks and frequency data.
Further, in step S4, the time that the student reacts includes: that student starts to make the sound of answer and goes out
The existing time and student makes the time for movement of standing up.
Further, described that collected every terms of information is for statistical analysis in step S5, when discovery focus is low
After student, sending a warning to responsible teacher includes:
S501: collected all data is subjected to statistic of classification；
S502: the data sorted out intersect comparing analysis；
S503: as the low student of discovery focus, then warning message is sent to teacher.
In conclusion by adopting the above-described technical solution, the beneficial effects of the present invention are:
1, the present invention is by artificial intelligence monitors student focus, make teacher at school when do not need to spend a lot of time and remind student
It listens to the teacher, ensure that teachers' instruction progress can carry out according to plan.
2, method of the invention overcomes the single problem of judgement monitoring focus condition, is become by all kinds of movements of student
Change, to the terms and conditions such as reaction time of calling the roll, comprehensively judges the focus of student.
3, the present invention can automatically prompt teacher, teacher can oneself when monitoring the low student of focus
It determines when to remind the student, ensure that the rhythm of attending class of teacher is not disturbed.
Detailed description of the invention
Examples of the present invention will be described by way of reference to the accompanying drawings, in which:
Fig. 1 is focus monitoring flow chart figure.
Fig. 2 is to acquire student to listen to the teacher the image and audio flow chart of process.
Fig. 3 is focus analysis flow chart diagram.
Specific embodiment
All features disclosed in this specification or disclosed all methods or in the process the step of, in addition to mutually exclusive
Feature and/or step other than, can combine in any way.
Any feature disclosed in this specification (including any accessory claim, abstract), unless specifically stated,
It is replaced by other equivalent or with similar purpose alternative features.That is, unless specifically stated, each feature is a series of
An example in equivalent or similar characteristics.
Embodiment 1
A kind of student's focus monitoring method based on artificial intelligence, as shown in Figure 1, comprising:
S1: the personal information of student, student and the face information of teacher and voice print matching are recorded in artificial intelligence platform；
In above-mentioned steps, student's personal information includes: name, gender, class and teacher；When typing student's face
After information and vocal print, face information, vocal print and personal information can be subjected to matched indicia, for the identification to pupilage；And
The face information and vocal print of typing teacher is mainly used for distinguishing with student's face information and vocal print, reduces error.
S2: the image and audio during student listens to the teacher are acquired；
In above-mentioned steps, the acquisition of image and audio is carried out by video, video can be acquired by all kinds of capture apparatus, be had
Body step is as shown in Figure 2, comprising:
S201: student's image is taken out by video file catching；
In above-mentioned steps, after being collected into video file, video middle school student image is identified, and will identify according to student's face information
To student matched with its personal information.
S202: the audio-frequency information in video file is extracted；
In above-mentioned steps, audio-frequency information can individually be extracted from video, include teacher's in the audio file extracted
The sound of sound and student.
S203: the sound of teacher in the audio-frequency information extracted and student's sound are subjected to classification marker；
In above-mentioned steps, the sound of teacher in audio file and the sound of student can be carried out by the vocal print recorded in step S1
It distinguishes, and marks respectively.
S204: the vocal print of the student marked and the student's vocal print being recorded in platform are compared, finds and matches
Student；
In above-mentioned steps, the sound of students different in audio file can be distinguished by vocal print and be provided with the student of record
Material is matched, and the student that matching is completed is marked respectively.
S3: pass through student's Image Acquisition student's action message；
In above-mentioned steps, the student's image grabbed out by step S201 can acquire the various actions information and number of student
According to specifically including:
The data for acquiring student's rotary head number and amplitude, may determine that student by the amplitude of student's rotary head number and single rotary head
Focus, when student is absorbed in teachers, head number of revolutions is less, only can teacher walk about live follow courseware change into
Row fine rotation, if rotary head number is excessive and amplitude is big, it can be determined that be absent minded.
Acquisition student bows the data of number of coming back, and for student during listening to the teacher, majority is only existed in new line state
Take notes when recording can the short time head is low, if student bows, number is more, and the state for time that keeps bowing every time is longer, then
It can determine whether to be absent minded.
Acquire student's number of winks and frequency data, under normal circumstances, one minute number of winks 10-20 times one point
Clock, when being absorbed in viewing equally thing, number of winks is at 8-10 times, if student's eyes are not concerned in teacher or courseware side
To, and one minute number of winks is lower than 8 times or when being higher than 20 times, it can be determined that attention of student is not concentrated.
S4: student is acquired by student audio and is called the roll the time reacted to student by teacher；
In above-mentioned steps, the sound of Faculty and Students can be collected respectively by step S2, when teacher tells a student's
After name, acquisition teacher make a sound corresponding student make a sound between time span may determine that student's focus, if
The shown time was less than 5 seconds, it can be determined that goes out attention of student and concentrates, may determine that attention of student was not concentrated if more than 5 seconds；?
In another embodiment, can also be made a sound by teacher student make stand up or other representative movement time judgement learn
Raw focus.
S5: collected every terms of information is for statistical analysis, after discovery focus low student, issues and warn to teacher
It notifies breath；
In above-mentioned steps, the metaideophone of student is monitored surely by the way that student's all data is compared, if discovery has
The low student of focus, it will alarm to teacher, specific steps are as shown in Figure 3, comprising:
S501: collected all data is subjected to statistic of classification；
In above-mentioned steps, by collected student's various actions behavioral data, time data etc. are classified, and are individually counted,
For carrying out the preliminary analysis of focus to single project.
S502: the data sorted out intersect comparing analysis；
In above-mentioned steps, each single datum is subjected to intersection comparison, make data analysis more comprehensively with it is perfect, reduce erroneous judgement
Probability.
S503: as the low student of discovery focus, then warning message is sent to teacher；
In above-mentioned steps, when judging that student's focus is low, warning message can be sent in time to teacher, make teacher can be with first
Time knows and reasonable arrangement time alarm student, will not influence teachers' instruction progress.
The present invention is monitored student's focus by artificial intelligence technology, effectively reduces teacher during giving lessons
The time for retracting attention of student ensure that teachers' instruction progress is unaffected；Work as simultaneously and has monitored student's focus
After reduction, teachers association obtains alarm and reminding, and teacher can voluntarily select to remind the time of student at this time, ensure that attending class for teacher
Progress is without interruption, will not influence quality of instruction.
The invention is not limited to specific embodiments above-mentioned.The present invention, which expands to, any in the present specification to be disclosed
New feature or any new combination, and disclose any new method or process the step of or any new combination.
Claims (6)
1. a kind of student's focus monitoring method based on artificial intelligence characterized by comprising
S1: the personal information of student, student and the face information of teacher and voice print matching are recorded in artificial intelligence platform；
S2: the image and audio during student listens to the teacher are acquired；
S3: pass through student's Image Acquisition student's action message；
S4: student is acquired by student audio and is called the roll the time reacted to student by teacher；
S5: collected every terms of information is for statistical analysis, and after discovery focus low student, Xiang Jiaoshi sounds an alarm letter
Breath.
2. student's focus monitoring method based on artificial intelligence as described in claim 1, which is characterized in that in step S1,
Student's personal information includes: name, gender, class and teacher.
3. student's focus monitoring method based on artificial intelligence as described in claim 1, which is characterized in that in step S2,
The image acquired during student listens to the teacher and audio include:
S201: student's image is taken out by video file catching；
S202: the audio-frequency information in video file is extracted；
S203: the sound of teacher in the audio-frequency information extracted and student's sound are subjected to classification marker；
S204: the vocal print of the student marked and the student's vocal print being recorded in platform are compared, match is found
It is raw.
4. student's focus monitoring method based on artificial intelligence as described in claim 1, which is characterized in that in step S3,
Acquisition student's action message includes: that the data for acquiring student's rotary head number and rotary head amplitude, acquisition student bow and come back time
The data of several data, acquisition student's number of winks and frequency.
5. student's focus monitoring method based on artificial intelligence as described in claim 1, which is characterized in that in step S4,
The time that the student reacts includes: that student starts to make the time that the sound of answer occurs and student makes movement of standing up
Time.
6. student's focus monitoring method based on artificial intelligence as described in claim 1, which is characterized in that in step S5,
It is described that collected every terms of information is for statistical analysis, after discovery focus low student, sounded an alarm to responsible teacher
Information includes:
S501: collected all data is subjected to statistic of classification；
S502: the data sorted out intersect comparing analysis；
S503: as the low student of discovery focus, then warning message is sent to teacher.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110090018A (en) * | 2019-05-06 | 2019-08-06 | 安徽建筑大学 | A kind of focus analysis system based on brain dateline band |
| CN110135380A (en) * | 2019-05-22 | 2019-08-16 | 东北大学 | A kind of classroom focus knowledge method for distinguishing based on Face datection |
| CN110225288A (en) * | 2019-05-09 | 2019-09-10 | 黄河 | A kind of information processing reforming unit |
| CN110443183A (en) * | 2019-07-31 | 2019-11-12 | 北京大米科技有限公司 | A kind of class state monitoring method, device, storage medium and server |
| CN111353920A (en) * | 2019-06-28 | 2020-06-30 | 鸿合科技股份有限公司 | Intelligent blackboard |
| CN116596719A (en) * | 2023-07-18 | 2023-08-15 | 江西科技学院 | Computer room computer teaching quality management system and method |
| CN117114938A (en) * | 2023-10-17 | 2023-11-24 | 北京布局未来教育科技有限公司 | Teaching demonstration method, system, terminal and storage medium based on artificial intelligence |
| CN117423131A (en) * | 2023-10-18 | 2024-01-19 | 广东融粤宝信息科技有限公司 | Remote education system based on cloud computing |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102340686A (en) * | 2011-10-11 | 2012-02-01 | 杨海 | Method and device for detecting attentiveness of online video viewer |
| CN106250822A (en) * | 2016-07-21 | 2016-12-21 | 苏州科大讯飞教育科技有限公司 | Student's focus based on recognition of face monitoring system and method |
| CN106599881A (en) * | 2016-12-30 | 2017-04-26 | 首都师范大学 | Student state determination method, device and system |
| CN108009754A (en) * | 2017-12-26 | 2018-05-08 | 重庆大争科技有限公司 | Method of Teaching Quality Evaluation |
| CN108021893A (en) * | 2017-12-07 | 2018-05-11 | 浙江工商大学 | It is a kind of to be used to judging that student to attend class the algorithm of focus |
| CN108108903A (en) * | 2017-12-26 | 2018-06-01 | 重庆大争科技有限公司 | Classroom teaching quality assessment system |
| CN108399376A (en) * | 2018-02-07 | 2018-08-14 | 华中师范大学 | Student classroom learning interest intelligent analysis method and system |
-
2018
- 2018-10-29 CN CN201811265516.3A patent/CN109670395A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102340686A (en) * | 2011-10-11 | 2012-02-01 | 杨海 | Method and device for detecting attentiveness of online video viewer |
| CN106250822A (en) * | 2016-07-21 | 2016-12-21 | 苏州科大讯飞教育科技有限公司 | Student's focus based on recognition of face monitoring system and method |
| CN106599881A (en) * | 2016-12-30 | 2017-04-26 | 首都师范大学 | Student state determination method, device and system |
| CN108021893A (en) * | 2017-12-07 | 2018-05-11 | 浙江工商大学 | It is a kind of to be used to judging that student to attend class the algorithm of focus |
| CN108009754A (en) * | 2017-12-26 | 2018-05-08 | 重庆大争科技有限公司 | Method of Teaching Quality Evaluation |
| CN108108903A (en) * | 2017-12-26 | 2018-06-01 | 重庆大争科技有限公司 | Classroom teaching quality assessment system |
| CN108399376A (en) * | 2018-02-07 | 2018-08-14 | 华中师范大学 | Student classroom learning interest intelligent analysis method and system |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110090018A (en) * | 2019-05-06 | 2019-08-06 | 安徽建筑大学 | A kind of focus analysis system based on brain dateline band |
| CN110225288A (en) * | 2019-05-09 | 2019-09-10 | 黄河 | A kind of information processing reforming unit |
| CN110135380A (en) * | 2019-05-22 | 2019-08-16 | 东北大学 | A kind of classroom focus knowledge method for distinguishing based on Face datection |
| CN110135380B (en) * | 2019-05-22 | 2023-07-11 | 东北大学 | Classroom concentration recognition method based on face detection |
| CN111353920A (en) * | 2019-06-28 | 2020-06-30 | 鸿合科技股份有限公司 | Intelligent blackboard |
| CN110443183A (en) * | 2019-07-31 | 2019-11-12 | 北京大米科技有限公司 | A kind of class state monitoring method, device, storage medium and server |
| CN116596719A (en) * | 2023-07-18 | 2023-08-15 | 江西科技学院 | Computer room computer teaching quality management system and method |
| CN116596719B (en) * | 2023-07-18 | 2023-09-19 | 江西科技学院 | Computer room computer teaching quality management system and method |
| CN117114938A (en) * | 2023-10-17 | 2023-11-24 | 北京布局未来教育科技有限公司 | Teaching demonstration method, system, terminal and storage medium based on artificial intelligence |
| CN117114938B (en) * | 2023-10-17 | 2024-02-23 | 北京布局未来科技发展有限公司 | Teaching demonstration method, system, terminal and storage medium based on artificial intelligence |
| CN117423131A (en) * | 2023-10-18 | 2024-01-19 | 广东融粤宝信息科技有限公司 | Remote education system based on cloud computing |
| CN117423131B (en) * | 2023-10-18 | 2024-08-27 | 山西易和学教育科技股份公司 | Remote education system |
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Application publication date: 20190423 |