Foreign Chinese education guidance system based on natural language processing

Abstract

The invention discloses a foreign Chinese education guidance system based on natural language processing, which relates to the technical field of education and comprises an input module, a natural language processing module, a knowledge database, a learning state analysis module, a teaching strategy generation module, a teaching content pushing module and an output module. The system generates personalized teaching strategies according to specific conditions of learners, provides personalized learning paths and teaching contents according to Chinese basis, learning objectives and learning styles of different learners, integrates rich resources such as Chinese vocabularies, grammar rules, cultural knowledge, example sentences and exercise questions, intelligently recommends according to the conditions of the learners, and improves the learning efficiency. According to the method, the utilization efficiency of teaching resources is improved, the learning behaviors and achievements of learners are tracked in real time, the learning progress and the Chinese language ability are comprehensively evaluated and presented in a visual mode, the interactivity and adaptability of teaching are enhanced, in addition, multi-modal teaching is achieved, and richer and more vivid learning experience is provided for the learners.

Description

Technical Field

[0001] The present invention relates to the field of educational technology, and particularly to a Chinese as a foreign language education guidance system based on natural language processing. Background Art

[0002] Traditional teaching methods have the problem of being highly mechanical, unable to provide personalized learning paths and teaching content according to the Chinese language basis, learning goals, and learning styles of different learners. At the same time, existing Chinese as a foreign language teaching resources are scattered, making it difficult for learners to find suitable learning resources. Moreover, traditional teaching fails to evaluate the learning progress and abilities of learners in a timely and accurate manner, and a single teaching mode is difficult to meet the diverse needs of learners. Summary of the Invention

[0003] The purpose of the present invention is to provide a Chinese as a foreign language education guidance system based on natural language processing to solve the above deficiencies in the prior art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A Chinese as a foreign language education guidance system based on natural language processing, including an input module, a natural language processing module, a knowledge database, a learning status analysis module, a teaching strategy generation module, a teaching content push module, and an output module; The input module receives and converts the natural language information input by the user terminal and transmits it to the natural language processing module; The natural language processing module performs preprocessing, lexical analysis, syntactic analysis, and semantic analysis on the natural language information from the input module, obtains the analysis result, and transmits the analysis result to the learning status analysis module; The learning status analysis module determines the current Chinese language level, learning progress, learning difficulties, and learning advantages of the learner according to the analysis result from the natural language processing module, obtains the determination result, and transmits the determination result to the teaching strategy generation module and the knowledge database respectively; The knowledge database stores Chinese as a foreign language knowledge, provides corresponding knowledge according to the requests of the teaching strategy generation module and the teaching content push module, and receives the determination result fed back by the learning status analysis module to update the database content; The teaching strategy generation module generates a personalized teaching strategy for the learner according to the determination result of the learning status analysis module and the content in the knowledge database, and transmits the personalized teaching strategy to the teaching content push module; The teaching content push module selects teaching content from the knowledge database according to the personalized teaching strategy generated by the teaching strategy generation module and transmits the selected teaching content to the output module; The output module sends the teaching content pushed by the teaching content push module to the user terminal in a visual form; The teaching strategy generation module includes a goal setting unit and a personalized strategy generation unit; The goal setting unit determines short-term and long-term teaching goals according to the judgment result of the learning status analysis module and the learning goals set by the user terminal; The personalized strategy generation unit selects corresponding teaching methods, teaching contents, and practice methods from the knowledge database according to the judgment result of the learning status analysis module, combines with the teaching goals set by the goal setting unit, constructs a decision model using the decision tree algorithm to generate personalized teaching strategies, and optimizes the model parameters through the genetic algorithm; The output end of the goal setting unit is connected to the input end of the personalized strategy generation unit.

[0005] Furthermore, the input module includes a text input unit and a voice input unit; The text input unit receives the natural language text input by the user terminal and converts it into natural language information; The voice input unit receives the voice information input by the user terminal and converts it into natural language information.

[0006] Furthermore, the natural language processing module includes a preprocessing unit, a lexical analysis unit, a syntactic analysis unit, and a semantic analysis unit; The preprocessing unit cleans, tokenizes, and tags the input natural language information, and transmits the processed natural language information to the lexical analysis unit; The lexical analysis unit identifies the words in the natural language information, determines their part of speech and tags them, and transmits the word information with part of speech tags to the syntactic analysis unit; The syntactic analysis unit analyzes the grammatical structure of the natural language information, generates a syntax tree, and transmits the syntax tree to the semantic analysis unit; The semantic analysis unit analyzes the semantic information of the natural language information, determines its meaning and context relationship, and summarizes to obtain the analysis result.

[0007] Furthermore, the input end of the preprocessing unit is respectively connected to the output ends of the text input unit and the voice input unit, and its output end is connected to the input end of the lexical analysis unit; The output end of the lexical analysis unit is connected to the input end of the syntactic analysis unit; The output end of the syntactic analysis unit is connected to the input end of the semantic analysis unit.

[0008] Furthermore, the learning status analysis module includes a level assessment unit, a progress tracking unit, a difficulty analysis unit, and an advantage discovery unit; The horizontal evaluation unit evaluates the current Chinese comprehensive level of the learner according to the analysis results of the natural language processing module, including vocabulary, grammar mastery, and listening, speaking, reading, and writing skills levels, classifies the learners, and calculates the specific level values of the learners; The progress tracking unit records the learning time, learning content, completed exercises and test situations of the learner, and analyzes the learning progress based on this; The difficulty analysis unit analyzes the learning difficulties of the learner by comparing the learner's performance in different types of learning tasks; The advantage discovery unit discovers the learner's advantageous areas according to the learner's performance in the learning process, and summarizes to obtain the judgment result.

[0009] Further, the input end of the horizontal evaluation unit is connected to the output end of the semantic analysis unit, and its output end is connected to the input end of the progress tracking unit; The output end of the progress tracking unit is connected to the input end of the difficulty analysis unit; The output end of the difficulty analysis unit is connected to the input end of the advantage discovery unit; The output end of the advantage discovery unit is connected to the input end of the target setting unit.

[0010] Further, the knowledge database includes a knowledge storage unit and a knowledge association unit; The knowledge storage unit stores Chinese as a foreign language knowledge, supports external input, and accepts update instructions from the user terminal and judgment results feedback by the learning status analysis module to complete the content update of Chinese as a foreign language knowledge; The knowledge association unit establishes the association relationship between different types of knowledge.

[0011] Further, the teaching content push module includes a content selection unit and a push management unit; The content selection unit selects corresponding Chinese vocabulary, grammar explanations, example sentences, cultural knowledge introductions, exercise questions, and test content from the knowledge database as teaching content according to the personalized teaching strategy generated by the personalized strategy generation unit; The push management unit determines the time, frequency, and order of pushing the teaching content according to the learning habits of the learner and the current learning scenario, and pushes the content to the output module.

[0012] Further, the output module includes a screen display unit and a voice output unit; The screen display unit transmits the teaching content to the user terminal in the form of digital signals; The voice output unit converts the teaching content into voice analog signals and transmits them to the user terminal.

[0013] Further, the input end of the knowledge storage unit is connected to the output end of the advantage discovery unit, and its output end is connected to the input end of the personalized strategy generation unit; The knowledge association unit and the knowledge storage unit are connected bidirectionally; The input end of the content selection unit is respectively connected to the output ends of the personalized strategy generation unit and the knowledge storage unit, and its output end is connected to the input end of the push management unit; The input ends of the screen display unit and the voice output unit are respectively connected to the output end of the push management unit.

[0014] Compared with the prior art, the Chinese as a foreign language education guidance system based on natural language processing provided by the present invention: 1. Through the learning status analysis module and the teaching strategy generation module, personalized teaching strategies are generated according to the specific situation of learners, providing personalized learning paths and teaching contents for different learners' Chinese foundations, learning goals and learning styles; 2. The knowledge database integrates rich resources such as Chinese vocabulary, grammar rules, cultural knowledge, example sentences and exercise questions, and intelligently recommends according to the situation of learners through the teaching content push module, improving the utilization efficiency of teaching resources; 3. The learning status analysis module real-time tracks the learning behaviors and achievements of learners, comprehensively evaluates the learning progress and Chinese language ability, and presents them in a visual way, solving the problem of learning evaluation and enhancing the interactivity and adaptability of teaching; 4. The output module realizes multi-modal teaching through the screen display unit and the voice output unit, providing a richer and more vivid learning experience for learners. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings.

[0016] Figure 1 It is the overall structure diagram provided by Embodiment 1 of the present invention; Figure 2 It is the structure diagram of the teaching strategy generation module provided by Embodiment 1 of the present invention; Figure 3 It is the structure diagram of the input module provided by Embodiment 2 of the present invention; Figure 4 It is the first partial structure diagram provided by Embodiment 2 of the present invention; Figure 5 It is the second partial structure diagram provided by Embodiment 2 of the present invention; Figure 6 Schematic diagram of the knowledge database structure provided in the third embodiment of the present invention; Figure 7 Schematic diagram of the teaching content push module structure provided in the third embodiment of the present invention; Figure 8 Schematic diagram of the output module structure provided in the third embodiment of the present invention; Figure 9 Partial schematic diagram provided in the third embodiment of the present invention; Figure 10 Overall schematic diagram provided in the third embodiment of the present invention.

[0017] 1. Input module; 11. Text input unit; 12. Voice input unit; 2. Natural language processing module; 21. Preprocessing unit; 22. Lexical analysis unit; 23. Syntactic analysis unit; 24. Semantic analysis unit; 3. Knowledge database; 31. Knowledge storage unit; 32. Knowledge association unit; 4. Learning status analysis module; 41. Proficiency assessment unit; 42. Progress tracking unit; 43. Difficulty analysis unit; 44. Advantage discovery unit; 5. Teaching strategy generation module; 51. Goal setting unit; 52. Personalized strategy generation unit; 6. Teaching content push module; 61. Content selection unit; 62. Push management unit; 7. Output module; 71. Screen display unit; 72. Voice output unit. Detailed implementation manners

[0018] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further introduced in detail below with reference to the accompanying drawings.

[0019] Embodiment 1:

[0020] Please refer to Figure 1 - Figure 2 , the Chinese as a foreign language education guidance system based on natural language processing, including an input module 1, a natural language processing module 2, a knowledge database 3, a learning status analysis module 4, a teaching strategy generation module 5, a teaching content push module 6 and an output module 7; The input module 1 receives and converts the natural language information input by the user terminal, and transmits it to the natural language processing module 2; The natural language processing module 2 performs preprocessing, lexical analysis, syntactic analysis and semantic analysis on the natural language information from the input module 1, obtains the analysis result, and transmits the analysis result to the learning status analysis module 4; The learning status analysis module 4 judges the current Chinese proficiency, learning progress, learning difficulties and learning advantages of the learner according to the analysis result from the natural language processing module 2, obtains the judgment result, and transmits the judgment result to the teaching strategy generation module 5 and the knowledge database 3 respectively; The knowledge database 3 stores the knowledge of teaching Chinese as a foreign language, provides corresponding knowledge according to the requests of the teaching strategy generation module 5 and the teaching content push module 6, and receives the judgment results fed back by the learning status analysis module 4 to update the database content; The teaching strategy generation module 5 generates personalized teaching strategies for learners according to the judgment results of the learning status analysis module 4 and the content in the knowledge database 3, and transmits the personalized teaching strategies to the teaching content push module 6; The teaching content push module 6 selects teaching content from the knowledge database 3 according to the personalized teaching strategies generated by the teaching strategy generation module 5, and transmits the selected teaching content to the output module 7; The output module 7 sends the teaching content pushed by the teaching content push module 6 to the user terminal in a visual form; The teaching strategy generation module 5 includes a goal setting unit 51 and a personalized strategy generation unit 52; The goal setting unit 51 determines short-term and long-term teaching goals according to the judgment results of the learning status analysis module 4 and the learning goals set by the user terminal; The personalized strategy generation unit 52 selects corresponding teaching methods, teaching content, and practice methods from the knowledge database 3 according to the judgment results of the learning status analysis module 4, combines the teaching goals set by the goal setting unit 51, constructs a decision model using the decision tree algorithm to generate personalized teaching strategies, and optimizes the model parameters through the genetic algorithm; The output end of the goal setting unit 51 is connected to the input end of the personalized strategy generation unit 52.

[0021] Specific implementation method: The decision tree algorithm includes the following steps: For a data set with categories , the probability of the category appearing is , and the information entropy is: ; Given the feature set , has different values , is in the feature set with the value of the subset, and are the number of samples of the data set and the subset respectively, and the conditional entropy is: ; Information gain is the difference between information entropy and conditional entropy, and is used to measure the contribution degree of the feature set to the data set for classification; ; For a data set with categories, the Gini index is: ; .

[0022] The process of constructing a decision tree is as follows: Input the data set and the feature set , calculate the information entropy of the data set ; For each feature , calculate the information gain , and select the feature with the largest information gain as the splitting feature of the current node; According to the value of , divide into multiple subsets , and recursively call the above steps for each subset to construct subtrees until the stopping condition is met; The genetic algorithm includes the following steps: Set the population size to , and represent an individual as . Each individual is a potential solution in the problem solution space and is composed of a set of genes; The fitness function is used to measure the quality of an individual , and the goal is to find an individual that makes reach the optimal; Generate an initial population using a random method, where represents the state of the th individual at the initial moment; Calculate the fitness value of each individual in the population . The quality of an individual is linearly correlated with ; Calculate the probability that each individual is selected; Cumulative probability , and randomly generate a number between , if , then select the individual to enter the next generation population; Let the crossover probability be , for the two selected parent individuals and , with probability perform crossover; If single-point crossover is adopted, randomly select a crossover point , generate two offspring individuals and , where , , and are the gene lengths of individuals and ; Let the mutation probability be , for each gene in the individual , with probability perform mutation; After selection, crossover and mutation operations, a new generation population is obtained, and the fitness evaluation, selection, crossover and mutation operations are repeated until the termination condition is met; The termination condition can be reaching the maximum number of iterations , or the fitness value of the optimal individual in the population has no obvious change within successive generations.

[0023] Example 2: Please refer to Figure 3 - Figure 5 , this example provides a technical solution based on Example 1: The input module 1 includes a text input unit 11 and a voice input unit 12; The text input unit 11 receives the natural language text input by the user terminal and converts it into natural language information; The voice input unit 12 receives the voice information input by the user terminal and converts it into natural language information.

[0024] The natural language processing module 2 includes a preprocessing unit 21, a lexical analysis unit 22, a syntactic analysis unit 23 and a semantic analysis unit 24; The preprocessing unit 21 cleans, tokenizes and tags the input natural language information, and transmits the processed natural language information to the lexical analysis unit 22; The lexical analysis unit 22 identifies the words in the natural language information, determines their part of speech and tags them, and transmits the word information with part of speech tags to the syntactic analysis unit 23; The syntactic analysis unit 23 analyzes the grammatical structure of natural language information, generates a syntax tree, and transmits the syntax tree to the semantic analysis unit 24; The semantic analysis unit 24 analyzes the semantic information of natural language information, determines its meaning and context relationship, and summarizes to obtain the analysis result.

[0025] The input end of the preprocessing unit 21 is respectively connected to the output ends of the text input unit 11 and the voice input unit 12, and its output end is connected to the input end of the lexical analysis unit 22; The output end of the lexical analysis unit 22 is connected to the input end of the syntactic analysis unit 23; The output end of the syntactic analysis unit 23 is connected to the input end of the semantic analysis unit 24.

[0026] Specific implementation manner: The lexical analysis unit 22 can determine the part of speech of words and mark them by using the maximum entropy model algorithm. The syntactic analysis unit 23 can generate a syntax tree by using the probabilistic context-free grammar algorithm. The semantic analysis unit 24 can determine the meaning and context relationship of natural language information by using the word vector algorithm combined with the deep learning semantic analysis algorithm. All of the above are existing technologies and will not be elaborated here.

[0027] The learning status analysis module 4 includes a level evaluation unit 41, a progress tracking unit 42, a difficulty analysis unit 43, and an advantage discovery unit 44; The level evaluation unit 41 evaluates the current Chinese comprehensive level of the learner according to the analysis result of the natural language processing module 2, including vocabulary, grammar mastery degree, and listening, speaking, reading, and writing skill levels, classifies the learner, and calculates the specific level value of the learner; The progress tracking unit 42 records the learning time, learning content, completed exercises and test situations of the learner, and analyzes the learning progress based on this; The difficulty analysis unit 43 analyzes the learning difficulties of the learner by comparing the learner's performance in different types of learning tasks; The advantage discovery unit 44 discovers the advantage areas of the learner according to the learner's performance in the learning process, and summarizes to obtain the judgment result.

[0028] The input end of the level evaluation unit 41 is connected to the output end of the semantic analysis unit 24, and its output end is connected to the input end of the progress tracking unit 42; The output end of the progress tracking unit 42 is connected to the input end of the difficulty analysis unit 43; The output end of the difficulty analysis unit 43 is connected to the input end of the advantage discovery unit 44; The output end of the advantage discovery unit 44 is connected to the input end of the target setting unit 51.

[0029] Specific implementation manner: The horizontal evaluation unit 41 can classify learners by using a clustering algorithm, calculate the specific level value of learners by using a rule-based evaluation algorithm, the progress tracking unit 42 can analyze the learning progress by using a time series analysis algorithm, the difficulty analysis unit 43 can analyze the learning difficulties of learners by using an association rule mining algorithm, and the advantage discovery unit 44 can discover the advantageous fields of learners by using a comparative analysis algorithm. All of the above are existing technologies and will not be elaborated here.

[0030] Embodiment III: Please refer to Figure 6 - Figure 10 , and this embodiment provides a technical solution based on Embodiment II: The knowledge database 3 includes a knowledge storage unit 31 and a knowledge association unit 32; The knowledge storage unit 31 stores Chinese as a foreign language knowledge, supports external input, and accepts update instructions from the user terminal and judgment results fed back by the learning status analysis module 4 to complete the content update of the Chinese as a foreign language knowledge; The knowledge association unit 32 establishes an association relationship between different types of knowledge.

[0031] The teaching content push module 6 includes a content selection unit 61 and a push management unit 62; The content selection unit 61 selects corresponding Chinese vocabulary, grammar explanations, example sentences, cultural knowledge introductions, practice questions, and test content from the knowledge database 3 as teaching content according to the personalized teaching strategy generated by the personalized strategy generation unit 52; The push management unit 62 determines the time, frequency, and order of pushing the teaching content according to the learning habits of the learners and the current learning scenario, and pushes the content to the output module 7.

[0032] The output module 7 includes a screen display unit 71 and a voice output unit 72; The screen display unit 71 transmits the teaching content to the user terminal in the form of digital signals; The voice output unit 72 converts the teaching content into voice analog signals and transmits them to the user terminal.

[0033] The input end of the knowledge storage unit 31 is connected to the output end of the advantage discovery unit 44, and its output end is connected to the input end of the personalized strategy generation unit 52; The knowledge association unit 32 is connected to the knowledge storage unit 31 in a two-way manner; The input end of the content selection unit 61 is respectively connected to the output ends of the personalized strategy generation unit 52 and the knowledge storage unit 31, and its output end is connected to the input end of the push management unit 62; The input ends of the screen display unit 71 and the voice output unit 72 are respectively connected to the output end of the push management unit 62.

[0034] Specific implementation method: The knowledge association unit 32 can adopt a knowledge graph construction algorithm to establish the association relationship between different types of knowledge, and the push management unit 62 can adopt a recommendation algorithm based on user behavior analysis to push teaching content. Both of the above are existing technologies and will not be elaborated here.

[0035] Working principle: The user inputs natural language information into the system through the text input unit 11 or the voice input unit 12 of the input module 1. After the preprocessing unit 21 in the natural language processing module 2 cleans, segments, and marks the input information, the lexical analysis unit 22 identifies the vocabulary and determines the part of speech and tags, the syntactic analysis unit 23 constructs a syntax tree, and the semantic analysis unit 24 analyzes the semantic information, determines the meaning and context relationship, and finally summarizes the analysis results and transmits them to the learning status analysis module 4. The proficiency evaluation unit 41 of the learning status analysis module 4 evaluates the comprehensive Chinese proficiency of the learner based on the analysis results and classifies and calculates the values. The progress tracking unit 42 records the learning time and other situations to analyze the progress. The difficulty analysis unit 43 compares the task performance to find the difficulties, and the advantage discovery unit 44 mines the advantageous areas. The judgment results are summarized. On the one hand, the judgment results are transmitted to the teaching strategy generation module 5, and on the other hand, they are transmitted to the knowledge database 3. The target setting unit 51 of the teaching strategy generation module 5 combines the judgment results with the user-set learning goals to determine short-term and long-term teaching goals. The personalized strategy generation unit 52 selects content from the knowledge database 3 according to the judgment results and the set goals, constructs a decision model using the decision tree algorithm and optimizes it through the genetic algorithm, and generates personalized teaching strategies and transmits them to the teaching content push module 6. The knowledge storage unit 31 of the knowledge database 3 stores the knowledge of teaching Chinese as a foreign language and can accept external inputs, user update instructions, and feedback from the learning status analysis module 4 to update the content. The knowledge association unit 32 establishes knowledge association relationships. The content selection unit 61 of the teaching content push module 6 selects teaching content from the knowledge database 3 according to the personalized teaching strategies. The push management unit 62 determines the push time, frequency, and order according to the learner's habits and scenarios and then transmits them to the output module 7. The screen display unit 71 of the output module 7 sends the teaching content in the form of digital signals, and the voice output unit 72 converts the teaching content into voice analog signals and sends them to the user terminal, thus completing the information flow and function realization of the entire teaching guidance process and achieving personalized teaching Chinese as a foreign language guidance service.

[0036] Only certain exemplary embodiments of the present invention have been described by way of illustration above. Without doubt, for those of ordinary skill in the art, the described embodiments can be modified in various different ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A Chinese as a Foreign Language Education Guidance System based on natural language processing, characterized in that: It includes an input module (1), a natural language processing module (2), a knowledge database (3), a learning status analysis module (4), a teaching strategy generation module (5), a teaching content push module (6) and an output module (7); The input module (1) receives and converts natural language information input by a user terminal, and transmits it to the natural language processing module (2); The natural language processing module (2) performs preprocessing, lexical analysis, syntactic analysis and semantic analysis on the natural language information from the input module (1), obtains analysis results, and transmits the analysis results to the learning state analysis module (4); The learning status analysis module (4) determines the learner's current Chinese proficiency, learning progress, learning difficulties and learning advantages based on the analysis results from the natural language processing module (2), obtains a determination result, and transmits the determination result to the teaching strategy generation module (5) and the knowledge database (3) respectively; The knowledge database (3) stores knowledge of Chinese as a foreign language, provides corresponding knowledge according to the requests of the teaching strategy generation module (5) and the teaching content push module (6), and receives the judgment results fed back by the learning status analysis module (4) to update the database content; The teaching strategy generation module (5) generates a personalized teaching strategy for the learner based on the judgment result of the learning state analysis module (4) and the content in the knowledge database (3), and transmits the personalized teaching strategy to the teaching content push module (6); The teaching content push module (6) selects teaching content from the knowledge database (3) according to the personalized teaching strategy generated by the teaching strategy generation module (5), and transmits the selected teaching content to the output module (7); The output module (7) sends the teaching content pushed by the teaching content pushing module (6) to the user terminal in a visual form; The teaching strategy generation module (5) comprises a target setting unit (51) and a personalized strategy generation unit (52); The target setting unit (51) determines short-term and long-term teaching targets according to the judgment result of the learning state analysis module (4) and the learning target set by the user terminal; The personalized strategy generation unit (52) selects corresponding teaching methods, teaching contents and exercise methods from the knowledge database (3) according to the judgment result of the learning state analysis module (4) and the teaching objectives set by the goal setting unit (51), constructs a decision model using a decision tree algorithm to generate a personalized teaching strategy, and optimizes the model parameters using a genetic algorithm; An output end of the target setting unit (51) is connected to an input end of the personalized strategy generating unit (52).

2. The Chinese as a foreign language teaching and guidance system based on natural language processing according to claim 1 is characterized in that: The input module (1) comprises a text input unit (11) and a voice input unit (12); The text input unit (11) receives the natural language text input by the user terminal and converts it into natural language information; The voice input unit (12) receives voice information input by a user terminal and converts it into natural language information.

3. The Chinese as a foreign language teaching and guidance system based on natural language processing according to claim 2 is characterized in that: The natural language processing module (2) comprises a preprocessing unit (21), a vocabulary analysis unit (22), a syntactic analysis unit (23) and a semantic analysis unit (24); The preprocessing unit (21) cleans, segments and marks the input natural language information, and transmits the processed natural language information to the vocabulary analysis unit (22); The vocabulary analysis unit (22) identifies vocabulary in natural language information, determines its part of speech and marks it, and transmits the vocabulary information with the part of speech mark to the syntax analysis unit (23); The syntactic analysis unit (23) analyzes the grammatical structure of the natural language information, generates a grammatical tree, and transmits the grammatical tree to the semantic analysis unit (24); The semantic analysis unit (24) analyzes the semantic information of the natural language information, determines its meaning and contextual relationship, and summarizes the analysis results.

4. The Chinese as a foreign language teaching and guidance system based on natural language processing according to claim 3 is characterized in that: The input end of the preprocessing unit (21) is connected to the output ends of the text input unit (11) and the speech input unit (12) respectively, and its output end is connected to the input end of the vocabulary analysis unit (22); The output end of the vocabulary analysis unit (22) is connected to the input end of the syntactic analysis unit (23); The output end of the syntactic analysis unit (23) is connected to the input end of the semantic analysis unit (24).

5. The system for teaching Chinese as a foreign language based on natural language processing according to claim 4 is characterized in that: The learning status analysis module (4) comprises a level assessment unit (41), a progress tracking unit (42), a difficulty analysis unit (43) and an advantage discovery unit (44); The level assessment unit (41) assesses the learner's current comprehensive Chinese level, including vocabulary, grammar mastery, and listening, speaking, reading and writing skills, based on the analysis results of the natural language processing module (2), classifies the learner, and calculates the learner's specific level value; The progress tracking unit (42) records the learner's learning time, learning content, completed exercises and test results, so as to analyze the learning progress; The difficulty analysis unit (43) analyzes the learner's learning difficulties by comparing the learner's performance in different types of learning tasks; The advantage discovery unit (44) discovers the learner's advantage areas based on the learner's performance during the learning process, and summarizes the judgment results.

6. The Chinese as a foreign language teaching and guidance system based on natural language processing according to claim 5 is characterized in that: The input end of the level assessment unit (41) is connected to the output end of the semantic analysis unit (24), and the output end of the level assessment unit (41) is connected to the input end of the progress tracking unit (42); The output end of the progress tracking unit (42) is connected to the input end of the difficulty analysis unit (43); The output end of the difficulty analysis unit (43) is connected to the input end of the advantage discovery unit (44); An output end of the advantage discovery unit (44) is connected to an input end of the target setting unit (51).

7. The Chinese as a foreign language teaching and guidance system based on natural language processing according to claim 6 is characterized in that: The knowledge database (3) comprises a knowledge storage unit (31) and a knowledge association unit (32); The knowledge storage unit (31) stores Chinese as a foreign language knowledge, supports external input, and accepts update instructions from a user terminal and judgment results fed back by a learning state analysis module (4) to complete content updates of the Chinese as a foreign language knowledge; The knowledge association unit (32) establishes associations between different types of knowledge.

8. The system for teaching Chinese as a foreign language based on natural language processing according to claim 7 is characterized in that: The teaching content push module (6) comprises a content selection unit (61) and a push management unit (62); The content selection unit (61) selects corresponding Chinese vocabulary, grammar explanation, example sentences, cultural knowledge introduction, exercise questions and test content from the knowledge database (3) as teaching content according to the personalized teaching strategy generated by the personalized strategy generation unit (52); The push management unit (62) determines the time, frequency and sequence of pushing the teaching content according to the learner's learning habits and current learning scenario, and pushes the content to the output module (7).

9. The system for teaching Chinese as a foreign language based on natural language processing according to claim 8, characterized in that: The output module (7) comprises a screen display unit (71) and a voice output unit (72); The screen display unit (71) transmits the teaching content to the user terminal in the form of digital signals; The voice output unit (72) converts the teaching content into a voice simulation signal and transmits it to the user terminal.

10. The Chinese as a foreign language teaching and guidance system based on natural language processing according to claim 9 is characterized in that: The input end of the knowledge storage unit (31) is connected to the output end of the advantage discovery unit (44), and the output end thereof is connected to the input end of the personalized strategy generation unit (52); The knowledge association unit (32) and the knowledge storage unit (31) are bidirectionally connected; The input end of the content selection unit (61) is connected to the output ends of the personalized strategy generation unit (52) and the knowledge storage unit (31) respectively, and the output end is connected to the input end of the push management unit (62); Input ends of the screen display unit (71) and the voice output unit (72) are respectively connected to the output end of the push management unit (62).

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