CN106851216A - A kind of classroom behavior monitoring system and method based on face and speech recognition - Google Patents

A kind of classroom behavior monitoring system and method based on face and speech recognition Download PDF

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Publication number
CN106851216A
CN106851216A CN201710142279.0A CN201710142279A CN106851216A CN 106851216 A CN106851216 A CN 106851216A CN 201710142279 A CN201710142279 A CN 201710142279A CN 106851216 A CN106851216 A CN 106851216A
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teacher
student
classroom
facial expression
speech
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CN106851216B (en
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王鹏
张淑洁
石洁茹
宫晓君
温新
赵丽雯
张利会
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Shandong Normal University
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Shandong Normal University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/174—Facial expression recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20—Movements or behaviour, e.g. gesture recognition
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; 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

Abstract

The invention discloses a kind of classroom behavior monitoring system and method based on face and speech recognition, comprise the following steps：The video information of classroom middle school student, teacher is gathered by camera；The voice messaging of classroom middle school student, teacher is gathered by sound pick-up outfit；Main control processor is pre-processed to the student that receives, the video information of teacher, extracts student, the facial expression feature of teacher and behavioural characteristic；The voice messaging of student of the main control processor to receiving is processed, and extracts student's phonetic feature；The speech data information of teacher of the main control processor to receiving is processed, and extracts teacher's phonetic feature, calculates the score value of teachers ' teaching effect, teachers ' teaching is made according to score evaluates and provide guidance instruction.The present invention improves the accuracy and objectivity evaluated by the classroom behavior observation to teacher, student in classroom, can improve teaching method lifting quality of instruction.

Description

A kind of classroom behavior monitoring system and method based on face and speech recognition
Technical field
The invention mainly relates to a kind of classroom behavior monitoring system and method based on face and speech recognition.
Background technology
It is the important step of school's evaluation quality of instruction for classroom behavior monitoring, is fully understood by the level of teaching of teacher The reaction attended class with student, just can guarantee that high-quality teaching level.It is existing, for classroom behavior monitoring using student record or Teacher's person test simulation, the mode of teacher's observation supervision, this kind of mode can not give full play to the learning interest of student, it is impossible to comment The teaching efficiency of valency teacher, it is impossible to while realizing to student, the collection of the classroom behavior of teacher, analysis, record and evaluating.Cause How this, accurately sampled using based on face recognition technology and speech recognition technology come the classroom behavior to student and teacher With intellectual analysis and evaluation, realize that the expression behaviour of teaching classroom middle school student and teacher is observed and recorded, effectively improve Classroom teaching effect, the development in an all-round way for promoting student is the problem for being worth research and development.
The content of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the invention provides a kind of classroom row based on face and speech recognition It is monitoring system and method, Data Collection and assay is carried out in terms of assessment of students' behavior and teacher's behaviors evaluation two, The feedbacks such as praise and criticism of performance and teacher of the student on classroom on classroom are collected, and by data analysis, is evaluated and is learned Raw learning state and results of learning, while evaluating teachers ' teaching effect.
The technical solution adopted in the present invention is：
A kind of classroom behavior monitoring system based on face and speech recognition, including
Video Collection System, including installed in four, the classroom Omnidirection rotary pick-up head in corner and camera phase The image splitter that decoder even is connected with decoder, the video data information for gathering classroom middle school student, teacher；
Voice messaging acquisition system, including the sound pick-up outfit below student's desk and on dais, for gathering Classroom middle school student, the speech data information of teacher；
Main control processor, pre-processes to student, the video data information of teacher and voice messaging, extracts student, religion The facial expression feature and behavioural characteristic of teacher；
Analysis processor, student, the facial expression feature of teacher and behavioural characteristic is compared in standard form, and count Calculate phase reserved portion.
A kind of classroom behavior monitoring method based on face and speech recognition, comprises the following steps：
Step one, by installed in four, classroom corner camera gather classroom middle school student, teacher video counts it is believed that Breath；Classroom middle school student are gathered by the sound pick-up outfit below student's desk and on dais, the speech data of teacher is believed Breath；
After step 2, the student for collecting, the video data information of teacher are split through decoder decoding and image splitter, It is sent to main control processor；The student that to collect, the speech data information of teacher are sent to main control processor；
The video data information of the student of step 3, main control processor to receiving is pre-processed, and extracts the face of student Portion's expressive features and behavioural characteristic, are entered student's facial expression feature with student's facial expression standard form by analysis processor Row compares, and classroom middle school student's facial expression performance score is calculated according to comparative result, by students ' behavior feature and students ' behavior mark Quasi-mode plate is compared, and classroom middle school student's behavior expression score is calculated according to comparative result；
The video data information of the teacher of step 4, main control processor to receiving is pre-processed, and extracts the face of teacher Portion's expressive features and behavioural characteristic, by analysis processor by teacher's facial expression feature with and teacher's facial expression standard form It is compared, score of the teacher to student classroom performance facial expression reaction is calculated according to comparative result, by teacher's behaviors feature It is compared with teacher's behaviors standard form, the score that teacher is reacted student classroom expression behaviour is calculated according to comparative result；
The speech data information of the student of step 5, main control processor to receiving is processed, and extracts student's voice special Levy, train token sound template, student's phonetic feature is compared with token sound template, classroom is calculated according to comparative result In every student speech number of times and frequency, time limit of speech length and panel discussion when speech ratio；
The speech data information of the teacher of step 6, main control processor to receiving is processed, and extracts teacher's voice special Levy, calculate the score value of teachers ' teaching effect, and be compared with teachers ' teaching effect mean scores, when the score value is taught less than teacher When learning effect mean scores, prompting is sent；
Step 7：Main control processor is by classroom middle school student's facial expression and behavior expression score and teacher to student classroom The score of the reaction of performance facial expression and behavior reaction is integrated, and draws the classroom behavior total score of each student, and this is total Divide and be compared with the student classroom behavior average mark set in master controller, when the total score is average less than student classroom behavior Fraction, sends prompting；
Step 8：By student, the video data information of teacher, speech data information, each student classroom behavior total score Score value with teachers ' teaching effect is stored in the database of main control processor.
Further, the student, the video data information of teacher include student, the behavioural information of teacher and student, religion The facial expression information of teacher.
Further, in the step 3, student's facial expression feature template include iris center, inner eye corner point, Point and eyebrow exterior point in external eyes angle point, prenasale, nostril point, tragus point, subaurale, bicker point, crown point, eyebrow；Student's row Being characterized template includes raising one's hand, bows and take notes and new line is listened to the teacher.
Further, in the step 3, enter with standard form in the facial expression feature and behavioural characteristic for carrying out student Before row compares, first student's facial expression standard form and students ' behavior standard form assign and divided, student's face table It is absorbed in feelings standard form, glad expression is set as 10 points, cold and detached expression is set as 4 points, and agitation is set as 1 point；Students ' behavior Raised one's hand in standard form, bow take notes, the behavior listened to the teacher that comes back is set as 10 points, its be set as 0 point.
Further, in the step 4, teacher's facial expression standard form includes point and eyebrow in corners of the mouth radian, eyebrow Exterior point；The teacher's behaviors standard form is nodded number of times including teacher.
Further, in the step 4, enter with standard form in the facial expression feature and behavioural characteristic for carrying out teacher Before row compares, first teacher's facial expression standard form and teacher's behaviors standard form assign and divided, teacher's face table Expression is pleased in feelings standard form and is set as 10 points, discontented expression is set as 0 point, and remaining is assigned in intermediate range according to satisfaction Point, in the teacher's behaviors standard form according to teacher nod number of times carry out assign point.
Further, in the step 5, the speech number of times and frequency of student's phonetic feature including every class of student, every time Time limit of speech length and group make a speech ratio when talking about.
Further, the training token sound template specific method in the step 5 is：According to the instruction of each speaker Practice speech samples, through feature extraction, set up the token sound template of each speaker.
Further, in shown step 6, the specific method for calculating the score value of teachers ' teaching effect is：According to token sound The voice messaging of teacher is divided into several subsections by template, and its measure value is calculated using diversification meas urement method, according to Analysis processor Plays sound bank sets up speech assessment model, and the measure value of acquisition is converted into scientificity teaching efficiency Score value.
Compared with prior art, the beneficial effects of the invention are as follows：
(1) classroom behavior using camera and sound pick-up outfit to classroom middle school student, teacher carries out science, objectively adopts Sample, there is provided quantitative analysis data；Treatment is analyzed to the data for collecting by main control processor and analysis processor, is obtained The study input degree of student, and its results of learning is evaluated, available strategy can be taken correctly to draw based on the analysis result school Lead student actively to express, effectively improve classroom teaching effect, promote the development in an all-round way of student；
(2) facial expression feature and behavioural characteristic of student and standard form are compared by analysis processor and are beaten Point, the mode of traditional classroom observation is instead of, improve the accuracy and objectivity of evaluation；
(3) present invention is analyzed and evaluated by students ' behavior collected on classroom and classroom interactions' behavior, Teaching method lifting quality of instruction can be improved.
Brief description of the drawings
The Figure of description for constituting the part of the application is used for providing further understanding of the present application, and the application's shows Meaning property embodiment and its illustrated for explaining the application, does not constitute the improper restriction to the application.
Fig. 1 is the flow chart of the classroom behavior monitoring method based on face and speech recognition in the embodiment of the present invention；
Fig. 2 is that student's voice messaging collects process chart；
Fig. 3 is that teacher's voice messaging collects process chart；
Fig. 4 is the structured flowchart of the classroom behavior monitoring system based on face and speech recognition in the embodiment of the present invention.
Specific embodiment
It is noted that described further below is all exemplary, it is intended to provide further instruction to the application.Unless another Indicate, all technologies used herein and scientific terminology are with usual with the application person of an ordinary skill in the technical field The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singulative Be also intended to include plural form, additionally, it should be understood that, when in this manual use term "comprising" and/or " bag Include " when, it indicates existing characteristics, step, operation, device, component and/or combinations thereof.
In a kind of typical implementation method of the application, as Figure 1-3, a kind of classroom based on face and speech recognition Behavior monitoring method, comprises the following steps：
The video data information of classroom middle school student, teacher is gathered by the camera installed in four, classroom corner, it is described Student, the video data information of teacher include student, the behavioural information of teacher and student, the facial expression information of teacher；Pass through Sound pick-up outfit collection classroom middle school student below student's desk and on dais, the speech data information of teacher；
After the video data information of the student for collecting is split through decoder decoding and image splitter, it is sent at master control Reason device；The video data information of student of the main control processor to receiving is pre-processed, then carry out human facial expression recognition and Activity recognition；For human facial expression recognition, the different facial expression features for extracting student of face characteristic are first passed through, used during extraction Extracted based on student's facial expression standard form；Student's facial expression feature template includes iris center, inner eye corner Point and eyebrow exterior point in point, external eyes angle point, prenasale, nostril point, tragus point, subaurale, bicker point, crown point, eyebrow；For behavior Identification, first extracts the behavioural characteristic of student, and wherein behavioural characteristic is extracted and focuses primarily upon four limbs, head position, student's row Include raising one's hand for standard form, bow and take notes and new line is listened to the teacher；
The facial expression feature of student and behavioural characteristic that extract are analyzed and compared by analysis processor, first Student's facial expression standard form is assigned and is divided, absorbed in student's facial expression standard form, glad expression is set as 10 points, Cold and detached expression is set as 4 points, and agitation expression is set as 1 point；By analysis processor by student's facial expression feature and student face Portion's expression standard form is compared, and classroom middle school student's facial expression performance score is calculated according to comparative result；To students ' behavior Standard form carry out assign point, raised one's hand in students ' behavior standard form, bow take notes, the behavior listened to the teacher that comes back is set as 10 points； Students ' behavior feature is compared with students ' behavior standard form by analysis processor, according in comparative result calculating classroom Students ' behavior shows score；
After the video data information of the teacher for collecting is split through decoder decoding and image splitter, it is sent at master control Reason device；The video data information of teacher of the main control processor to receiving is pre-processed, based on teacher's facial expression master die Plate extracts the facial expression feature of teacher and extracts behavioural characteristic, wherein teacher's facial expression mark based on teacher's behaviors standard form Quasi-mode plate includes point and eyebrow exterior point in corners of the mouth radian, eyebrow；Teacher's behaviors standard form is nodded number of times including teacher；
The facial expression feature of teacher and behavioural characteristic that extract are analyzed and compared by analysis processor, first Teacher's facial expression standard form is assigned and is divided, expression pleased in teacher's facial expression standard form and is set as 10 points, be discontented with expression Be set as 0 point, remaining intermediate range according to satisfaction assign point, by analysis processor by teacher's facial expression feature with and Teacher's facial expression standard form is compared, and teacher is calculated to student classroom performance facial expression reaction according to comparative result Score；Then teacher's behaviors standard form assign point, entered according to teacher's number of times of nodding in the teacher's behaviors standard form Row is assigned and divided；Teacher's behaviors feature is compared with teacher's behaviors standard form by analysis processor, according to comparative result meter Calculate the score that teacher is reacted student classroom expression behaviour；
The student that to collect, the speech data information of teacher are sent to main control processor；Main control processor is to receiving The speech data information of student processed, student's phonetic feature is extracted based on speaker Recognition Technology, spoken according to each The training phonetic material of people, through feature extraction, sets up the token sound template of each speaker, obtains completing the voice mark of training Quasi-mode plate, student's phonetic feature is compared with token sound template；Student's phonetic feature includes the speech of every class of student Number of times and frequency, each time limit of speech length and group are made a speech ratio when talking about, and every in classroom is calculated according to comparative result Speech ratio when raw speech number of times and frequency, time limit of speech length and panel discussion；
The speech data information of teacher of the main control processor to receiving is processed, based on speech recognition technology, first Extract teacher's phonetic feature；Secondly, voice is split using audio segmentation algorithm according to the token sound template for having completed training It is several subsections, its measure value is calculated using diversification meas urement method according to different voice messagings；Finally, according to Standards for teachers sound bank sets up speech assessment model in analysis processor, and the measure value of acquisition is converted into scientificity teaching The score value of effect；Wherein, included in standards for teachers sound bank and learner answering questionses positive feedback and negative sense are fed back, positive feedback is back Answer correct, negative sense is fed back to erroneous answers.
Student classroom septum reset expression and behavior expression score and teacher are showed face by main control processor to student classroom Portion's expression reaction and the score of behavior reaction are integrated, and draw the classroom behavior total score of each student, and by the total score and master The student classroom behavior average mark set in controller is compared, when total score is less than student classroom behavior average mark, hair Go out prompting；
By student, the video data information of teacher, speech data information, the classroom behavior total score of each student and teacher religion The score value for learning effect is stored in the database of main control processor.
As shown in figure 4, a kind of classroom behavior monitoring system based on face and speech recognition, including
Video Collection System, including installed in four, the classroom Omnidirection rotary pick-up head in corner and camera phase The image splitter that decoder even is connected with decoder, collection classroom middle school student, the video data information of teacher；
Voice messaging acquisition system, including the sound pick-up outfit below student's desk and on dais, gather classroom Middle school student, the speech data information of teacher；
Main control processor, pre-processes to student, the video data information of teacher and voice messaging, extracts student, religion The facial expression feature and behavioural characteristic of teacher；
Analysis processor, student, the facial expression feature of teacher and behavioural characteristic is compared in standard form, and count Calculate phase reserved portion.
Although above-mentioned be described with reference to accompanying drawing to specific embodiment of the invention, not to present invention protection model The limitation enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme those skilled in the art are not Need the various modifications made by paying creative work or deformation still within protection scope of the present invention.

Claims (10)

1. a kind of classroom behavior monitoring system based on face and speech recognition, it is characterized in that, including
Video Collection System, including be connected with camera installed in four, the classroom Omnidirection rotary pick-up head in corner The image splitter that decoder is connected with decoder, the video data information for gathering classroom middle school student, teacher；
Voice messaging acquisition system, including the sound pick-up outfit below student's desk and on dais, for gathering classroom Middle school student, the speech data information of teacher；
Main control processor, pre-process to student, the video data information of teacher and voice messaging, extracts student, teacher Facial expression feature and behavioural characteristic；
Analysis processor, student, the facial expression feature of teacher and behavioural characteristic is compared in standard form, and calculate phase Reserved portion.
2. a kind of classroom behavior monitoring method based on face and speech recognition, it is characterized in that, comprise the following steps：
Step one, the video data information that classroom middle school student, teacher are gathered by the camera installed in four, classroom corner；It is logical Cross sound pick-up outfit collection classroom middle school student, the speech data information of teacher below student's desk and on dais；
After step 2, the student for collecting, the video data information of teacher are split through decoder decoding and image splitter, send To main control processor；The student that to collect, the speech data information of teacher are sent to main control processor；
The video data information of the student of step 3, main control processor to receiving is pre-processed, and extracts the facial table of student Feelings feature and behavioural characteristic, are compared student's facial expression feature with student's facial expression standard form by analysis processor Compared with according to comparative result calculating classroom middle school student's facial expression performance score, by students ' behavior feature and students ' behavior master die Plate is compared, and classroom middle school student's behavior expression score is calculated according to comparative result；
The video data information of the teacher of step 4, main control processor to receiving is pre-processed, and extracts the facial table of teacher Feelings feature and behavioural characteristic, by analysis processor by teacher's facial expression feature with and teacher's facial expression standard form carry out Compare, score of the teacher to student classroom performance facial expression reaction is calculated according to comparative result, by teacher's behaviors feature and religion Teacher's behavioral standard template is compared, and the score that teacher is reacted student classroom expression behaviour is calculated according to comparative result；
The speech data information of the student of step 5, main control processor to receiving is processed, and extracts student's phonetic feature, instruction Practice token sound template, student's phonetic feature is compared with token sound template, according to every in comparative result calculating classroom Speech ratio during speech number of times and frequency, time limit of speech length and the panel discussion of position student；
The speech data information of the teacher of step 6, main control processor to receiving is processed, and extracts teacher's phonetic feature, meter The score value of teachers ' teaching effect is calculated, and is compared with teachers ' teaching effect mean scores, when the score value is imitated less than teachers ' teaching During fruit mean scores, prompting is sent；
Step 7：Main control processor shows student classroom classroom middle school student's facial expression and behavior expression score and teacher Facial expression is reacted and the score of behavior reaction is integrated, and draws the classroom behavior total score of each student, and by the total score with The student classroom behavior average mark set in master controller is compared, when the total score is less than student classroom behavior average mark Number, sends prompting；
Step 8：By student, the video data information of teacher, speech data information, the classroom behavior total score of each student and religion The score value of teacher's teaching efficiency is stored in the database of main control processor.
3. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, institute State student, the video data information of teacher includes student, the behavioural information of teacher and student, the facial expression information of teacher.
4. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, institute State in step 3, student's facial expression standard form includes iris center, inner eye corner point, external eyes angle point, prenasale, nostril Point and eyebrow exterior point in point, tragus point, subaurale, bicker point, crown point, eyebrow；The students ' behavior standard form include raise one's hand, it is low Head is taken notes and new line is listened to the teacher.
5. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, institute In stating step 3, before the facial expression feature and behavioural characteristic for carrying out student are compared with standard form, first to student Facial expression standard form and students ' behavior standard form assign and divided, absorbed in student's facial expression standard form, high Emerging expression is set as 10 points, and cold and detached expression is set as 4 points, and agitation expression is set as 1 point；Raised one's hand in students ' behavior standard form, Bow take notes, the behavior listened to the teacher that comes back is set as 10 points.
6. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, institute State in step 4, teacher's facial expression standard form includes point and eyebrow exterior point in corners of the mouth radian, eyebrow；The teacher's behaviors mark Quasi-mode plate is nodded number of times including teacher.
7. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, institute In stating step 4, before the facial expression feature and behavioural characteristic for carrying out teacher are compared with standard form, first to teacher Facial expression standard form and teacher's behaviors standard form assign and divided, and expression is pleased in teacher's facial expression standard form It is set as 10 points, discontented expression is set as 0 point, remaining is assigned according to satisfaction in intermediate range and divides, the teacher's behaviors standard In template according to teacher nod number of times carry out assign point.
8. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, institute State in step 5, student's phonetic feature includes speech number of times and the frequency, each time limit of speech length and group of every class of student Made a speech when talking about ratio.
9. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, institute The training token sound template specific method stated in step 5 is：Training speech samples according to each speaker, carry through feature Take, set up the token sound template of each speaker.
10. a kind of classroom behavior monitoring method based on face and speech recognition according to claim 2, it is characterized in that, In shown step 6, the specific method for calculating the score value of teachers ' teaching effect is：According to token sound template by the voice of teacher Information is divided into several subsections, and its measure value is calculated using diversification meas urement method, according to analysis processor Plays Sound bank sets up speech assessment model, and the measure value of acquisition is converted into the score value of scientificity teaching efficiency.
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