Intelligent teaching real-time interaction platform

Abstract

The invention discloses an intelligent teaching real-time interaction platform, and relates to the technical field of real-time teaching interaction.The intelligent teaching real-time interaction platform is characterized in that a user ID is converted into a string of digital identities, and password characters are generated by a random digital sequence with the same digits as that generated by a system through a docking algorithm; similarly, password characters are generated according to the user ID of the student and the random number sequence, and if the password characters generated by the root audio interception unit are consistent, the target data transmitted by the audio interception unit are received, so that it can be effectively ensured that the student after identity verification can speak, and the user experience is improved. The related equipment can realize the input of the algorithm only through one USB flash disk, so that the method is simple and effective, and the cost is low; meanwhile, harassment of irrelevant personnel can be avoided; teaching plan information representing a teaching plan of a teacher and text information representing teaching text content are obtained and subjected to word segmentation processing, and key segmented words and explanation segmented words are obtained according to the coincidence degree; then audio data in the target data are analyzed, and if the audio data contain any key segmented word or explanation segmented word, the audio data are automatically marked as corresponding reminding voice and conventional voice; the voice which does not belong to the teaching content part can be automatically filtered, and the purity of the classroom environment is ensured.

Description

Technical Field

[0001] This invention belongs to the field of real-time interactive teaching technology, specifically a smart teaching real-time interactive platform. Background Technology

[0002] The intelligent teaching real-time interactive platform is a core tool for the digital transformation of education. It aims to reconstruct the traditional teaching process by integrating technologies such as artificial intelligence, real-time communication, and big data analytics, achieving intelligent collaboration and instant feedback across the entire "teaching-learning-assessment-management" process. Its core value lies in breaking through the limitations of time and space, enhancing the sense of presence in teaching, and driving personalized learning.

[0003] Currently, real-time interactive teaching platforms are generally implemented using online conferencing or similar platforms. This presents several problems: if the room number of an online classroom is known to others, non-attending students may join, disrupting classroom discipline and potentially even affecting the quality of teaching. Mute students, on the other hand, prevents real-time interaction with students, and the public chat is also easily affected. Furthermore, due to the differences in students' learning environments, many non-teaching voice messages may be output, thus impacting the quality of teaching. Based on these issues, this application provides a solution. Summary of the Invention

[0004] This invention aims to solve at least one of the technical problems existing in the prior art; Therefore, this invention proposes a smart teaching real-time interactive platform, including... The audio capture unit on the student's device is used to acquire audio data containing real-time voice representing student interaction during the teacher's lecture and target data including user IDs. It converts the user IDs into a string of digital identities and generates password characters using a docking algorithm with a random number sequence of the same length generated by the system. The data acquisition unit is used to acquire lesson plan information representing teachers' lesson plans and text information representing teaching text content, and to perform word segmentation on the two, obtaining key word segments and explanation word segments based on the degree of overlap; The comprehensive analysis unit is used to generate password characters based on the student's user ID and random number sequence. If the password characters generated by the root audio extraction unit are consistent, it receives the target data transmitted by the audio extraction unit and analyzes the audio data in the target data. If the audio data contains any key words or explanatory words, it automatically marks them as the corresponding reminder voice and regular voice.

[0005] Furthermore, the specific method for analyzing audio data is as follows: When no audio is detected at a set time interval, the audio data is divided into a single voice segment, thus obtaining several single voice segments. The text is processed by converting a single voice message to text. If it only contains explanatory words, it is marked as regular voice; if it contains key words, it is marked as reminder voice. This process yields all regular and reminder voice messages.

[0006] Furthermore, the time interval can be preset by the administrator.

[0007] Furthermore, the time interval is determined in the following way: For each user ID, the interval between each individual voice recording is obtained after confirmation and marked as the standard interval. Based on the screening condition that the absolute value of the difference between the standard interval and its mean does not exceed the preset value X1, the standard intervals are screened out. If the proportion of the standard intervals smaller than the mean that are screened out does not exceed the preset proportion B1, then the minimum value of the remaining standard intervals after screening is marked as the set duration interval. Otherwise, the median of the minimum and maximum values ​​of the standard intervals that are less than the mean will be marked as the set time interval.

[0008] Furthermore, the comprehensive analysis unit is used to mark voices that are not marked as regular voices or reminder voices as questionable voices.

[0009] Furthermore, the comprehensive analysis unit is used to transmit questionable audio to the judgment unit via the filtering unit, where the teacher can choose whether to play it.

[0010] Furthermore, the comprehensive analysis unit is used to transmit the regular voice and the reminder voice through the filtering unit to the output unit for output.

[0011] Furthermore, the method for converting a user ID into a digital identity is as follows: The user ID retains the numbers, the Chinese characters are converted into Pinyin letters, and each Pinyin letter is replaced by its ordinal number in the 26 Pinyin alphabet to obtain a digital identity.

[0012] Furthermore, the docking algorithm is as follows: Perform an XOR operation on the digital identity and a random number sequence, and the output number is the password character.

[0013] Furthermore, the docking algorithm is as follows: Compare the digital identity with a random sequence of numbers, and mark the sequence of numbers that are the same as the password character.

[0014] Compared with the prior art, the beneficial effects of the present invention are: This invention converts a user ID into a string of digital identity, and generates a password character using a matching algorithm with a random number sequence of the same length generated by the system. Similarly, a password character is generated based on the student's user ID and the random number sequence. Only if the password character generated by the audio interception unit matches the password character generated by the audio interception unit will the target data transmitted by the audio interception unit be received. This effectively ensures that only students who have been authenticated can speak. Moreover, the equipment involved can realize the algorithm input with just a USB flash drive, which is simple, effective, and inexpensive. At the same time, it can avoid interference from irrelevant personnel. The system acquires lesson plan information and teaching text content representing the teacher's lesson plan, and performs word segmentation on both. Based on the degree of overlap, it obtains key word segments and explanation word segments. Then, it analyzes the audio data in the target data. If the audio data contains any key word segments or explanation word segments, it automatically marks them as the corresponding reminder voice and regular voice. It can automatically filter out voices that do not belong to the teaching content, ensuring the purity of the classroom environment. Attached Figure Description

[0015] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1 This application provides a smart teaching real-time interactive platform; As an embodiment of this application, it specifically includes: The audio capture unit on the student's device is used to acquire audio data containing real-time voice representing student interaction during the teacher's lecture and target data including user IDs. It converts the user IDs into a string of digital identities and generates password characters using a docking algorithm with a random number sequence of the same length generated by the system. The data acquisition unit is used to acquire lesson plan information representing teachers' lesson plans and text information representing teaching text content, and to perform word segmentation on the two, obtaining key word segments and explanation word segments based on the degree of overlap; The comprehensive analysis unit is used to generate password characters based on the student's user ID and random number sequence. If the password characters generated by the root audio extraction unit are consistent, it receives the target data transmitted by the audio extraction unit and analyzes the audio data in the target data. If the audio data contains any key words or explanatory words, it automatically marks them as the corresponding reminder voice and regular voice.

[0018] As a second embodiment of this application, it includes: The audio capture unit is used to capture the audio of all users involved and automatically record target data including audio data and user IDs. The audio data is real-time voice during real-time interaction in smart teaching and is promptly sent out via microphone connection. The audio capture unit is used to transmit the target data to the comprehensive analysis unit; Meanwhile, the data acquisition unit is used to acquire the teaching information for this lesson. The teaching information includes the teacher's lesson plan and teaching text. The lesson plan refers to the PPT or other filing documents specified by the teacher, and the teaching text refers to the teaching content taught by the corresponding teacher in this lesson. The data acquisition unit is used to analyze teaching information, and the specific analysis method is as follows: First, obtain all the text content in the teaching plan and mark it as teaching plan information. At the same time, obtain the text in the teaching text and mark it as text information. The lesson plan information is segmented into words. This segmentation process is an existing technology, and to avoid redundancy, it will not be described in detail here. After processing, several words are obtained and they are marked as lesson plan words. The lesson plan segmentation is processed by removing regular words. Regular words are words preset by the administrator, such as "normal" and "for example". Alternatively, some meaningless function words in existing technology can be used, such as "Harbin Institute of Technology's discontinued word library contains 1973 Chinese function words", to obtain the remaining segmented words and mark them as teaching core segmented words. Then, the same processing is performed on the text information to obtain several text kernel word segments; Then, the overlapping content of the teaching kernel segmentation and the text kernel segmentation is marked as the key segmentation, and the other is marked as the explanation segmentation; The data acquisition unit is used to transmit key word segments and explanatory word segments to the comprehensive analysis unit; The comprehensive analysis unit is used to automatically acquire the audio data from the target data when target data is detected, and to perform playback analysis on it. The specific playback analysis method is as follows: First, the audio data is acquired and automatically segmented. The segmentation method is as follows: when no audio input is detected for more than a set time interval, the previous audio is divided into a single voice, resulting in several single voices. The specific value of the set time interval mentioned here is set by the administrator. Select any single audio message, process it into text, and mark the resulting content as the converted text. If the converted text only contains explanatory words, the audio is marked as regular audio; if the converted text contains key words, it is marked as reminder audio; the rest are marked as questionable audio. After analyzing all individual audio clips, all regular audio, reminder audio, and questionable audio clips are obtained.

[0019] The comprehensive analysis unit is used to transmit the regular voice and the reminder voice to the filtering unit, and the filtering unit is used to transmit the regular voice and the reminder voice to the output unit; Another embodiment can also be provided here, as Embodiment Three of this application, in which the audio data is segmented in the following way: The audio data and user IDs were obtained from the target data. Then, the user IDs were analyzed. The specific analysis method was as follows: The time interval between each confirmed single voice recording by the person corresponding to the user ID is obtained and marked as the standard interval Gi, i=1,...,n, indicating that there are n+1 voice recordings corresponding to n standard intervals; The mean P of Gi is automatically obtained. Using the filtering condition |Gi-P|≤X1, where X1 is a preset value, Gi is filtered and those that do not meet the condition are deleted. After deleting Gi once, recalculate the mean of the remaining Gi and filter Gi using the same filtering criteria. Repeat this process until all Gi meet the filtering criteria. Then, obtain the Gi that was filtered out because it satisfies P-Gi>X1, obtain the ratio of its number to n, and mark it as the average ratio. When the average ratio exceeds the set ratio B1, the average of the minimum and maximum values ​​of the filtered Gi that satisfies P-Gi>X1 is marked as the set time interval of the corresponding user ID. If the average ratio does not exceed the set ratio B1, the minimum value of the remaining Gi after filtering will be automatically marked as the set time interval of the corresponding user ID. As a fourth embodiment of this application, the filtering unit is used to transmit the suspicious voice to the determination unit, and the determination unit is used to perform a second determination on the received suspicious voice. The specific method of the second determination is as follows: Questionable audio recordings need to be verified by the teacher before a decision is made on whether to play them. If they can be played, they will be played automatically; otherwise, they will be deleted and blocked. As a fifth embodiment of this application, this application also requires that when the audio acquisition unit enters a teaching platform created by the teacher, such as a live meeting convened by a conference number or other online teaching classroom, its identity needs to be verified. Only after the verification is successful can the target data acquired by the audio acquisition unit be transmitted to the comprehensive analysis unit. The specific verification method is as follows: When a user enters the created instant teaching platform, the user ID of the student will be automatically obtained. Then, the digital part involved will be retained, and if the text part is involved, it will be converted into the pinyin of the text; Convert each single letter of the text pinyin into a number according to its order among the 26 pinyin letters to obtain the digital identity representing the user ID; At this time, the number of digits of the digital identity will be automatically obtained, and a random number sequence with the corresponding number of digits will be generated. The random number sequence can take any number from 1 to 9; At the same time, the random number sequence will be transmitted to the student's device. Here, the device is generally a computer, and the student needs to insert a specified peripheral device. The specified peripheral device stores a docking algorithm, and the comprehensive analysis unit is also set with a corresponding docking algorithm; The docking algorithm is used to process the digital identity and the random number sequence to generate a string of password characters. If the password characters generated by the student's device are the same as those generated after the comprehensive analysis unit finishes processing, it means that the student's identity is correct at this time, and the audio acquisition unit is allowed to access the comprehensive analysis unit; otherwise, access is not allowed and audio cannot be transmitted; The docking algorithm here is: Perform an exclusive OR operation on each digit in the digital identity and the random number sequence, and output a password character composed of 0s and 1s with the same number of digits; Specific examples are as follows: If the student's user ID is Zhang San0012; then it first needs to be converted to zhangsan0012, and its corresponding digital identity is 2681147191140012. At this time, a random number sequence needs to be randomly generated. Assuming it is 2481847593147032, the password character output after the exclusive OR operation is 0100100101001010; If the password characters processed by the student's device and the comprehensive analysis unit are both the above password characters, it means that the student's identity verification is passed, and the collected target data can be transmitted to the comprehensive analysis unit. At this time, the comprehensive analysis unit receives the target data; otherwise, the comprehensive analysis unit does not receive the target data; Of course, as Embodiment 6 of this application, this embodiment is implemented on the basis of Embodiment 5. The difference is that the docking algorithm is different. Here it is: Retain each digit with the same value and delete the digits with different values in the digital identity and the random number sequence, and output the password character; Using this method will make the password character shorter; The example is as follows: If the student's user ID is Zhang San 0012, then it needs to be converted to zhangsan0012 first. The corresponding digital identity is 2681147191140012. At this time, a random number sequence needs to be generated randomly. Suppose it is 2481847593147032. Then the password character output after the exclusive OR operation is 2814791402.

[0020] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A smart teaching real-time interactive platform, characterized in that, include: The audio capture unit on the student's device is used to acquire audio data containing real-time voice representing student interaction during the teacher's lecture and target data including user IDs. It converts the user IDs into a string of digital identities and generates password characters using a docking algorithm with a random number sequence of the same length generated by the system. The data acquisition unit is used to acquire lesson plan information representing teachers' lesson plans and text information representing teaching text content, and to perform word segmentation on the two, obtaining key word segments and explanation word segments based on the degree of overlap; The comprehensive analysis unit is used to generate password characters based on the student's user ID and random number sequence. If the password characters generated by the root audio extraction unit are consistent, it receives the target data transmitted by the audio extraction unit and analyzes the audio data in the target data. If the audio data contains any key words or explanatory words, it automatically marks them as the corresponding reminder voice and regular voice.

2. The intelligent teaching real-time interactive platform according to claim 1, characterized in that, The specific method for analyzing audio data is as follows: When no audio is detected at a set time interval, the audio data is divided into a single voice segment, thus obtaining several single voice segments. The text is processed by converting a single voice message to text. If it only contains explanatory words, it is marked as regular voice; if it contains key words, it is marked as reminder voice. This process yields all regular and reminder voice messages.

3. The intelligent teaching real-time interactive platform according to claim 2, characterized in that, The set interval is preset by the administrator.

4. The intelligent teaching real-time interactive platform according to claim 2, characterized in that, The set duration interval is determined in the following way: For each user ID, the interval between each individual voice recording is obtained after confirmation and marked as the standard interval. Based on the screening condition that the absolute value of the difference between the standard interval and its mean does not exceed the preset value X1, the standard intervals are screened out. If the proportion of the standard intervals smaller than the mean that are screened out does not exceed the preset proportion B1, then the minimum value of the remaining standard intervals after screening is marked as the set duration interval. Otherwise, the median of the minimum and maximum values ​​of the standard intervals that are less than the mean will be marked as the set time interval.

5. The intelligent teaching real-time interactive platform according to claim 2, characterized in that, The comprehensive analysis unit is used to mark voices that are not marked as regular voices or reminder voices as questionable voices.

6. The intelligent teaching real-time interactive platform according to claim 1, characterized in that, The comprehensive analysis unit is used to transmit questionable audio to the judgment unit via the filtering unit, where the teacher can choose whether to play it.

7. The intelligent teaching real-time interactive platform according to claim 1, characterized in that, The integrated analysis unit is used to transmit regular voice and reminder voice through the filtering unit to the output unit for output.

8. The intelligent teaching real-time interactive platform according to claim 1, characterized in that, The method to convert a user ID into a digital identity is as follows: The user ID retains the numbers, the Chinese characters are converted into Pinyin letters, and each Pinyin letter is replaced by its ordinal number in the 26 Pinyin alphabet to obtain a digital identity.

9. The intelligent teaching real-time interactive platform according to claim 1, characterized in that, The docking algorithm is as follows: Perform an XOR operation on the digital identity and a random number sequence, and the output number is the password character.

10. A smart teaching real-time interactive platform according to claim 1, characterized in that, The docking algorithm is as follows: Compare the digital identity with a random sequence of numbers, and mark the sequence of numbers that are the same as the password character.

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