Maritime English proficiency evaluation method, device, equipment and readable storage medium

Abstract

The present application relates to a method, device, equipment and readable storage medium for evaluating the level of maritime English. The method includes: showing a virtual scene corresponding to the maritime English teaching and training activity to the user; obtaining the audio information of the user's pronunciation training, calling the corresponding preset audio data and the audio information for comparative analysis on similarity, and obtaining a first evaluation result of the user's maritime English level based on the analysis result; obtaining the action information performed by the user based on the instructions of each ship operation training, and obtaining a second evaluation result of the user's maritime English level according to the number of times the user correctly completes the corresponding action; respectively assigning a first preset weight to the first evaluation result, assigning a second preset weight to the second evaluation result, and performing weighted calculation to obtain the evaluation result of the maritime English level, and at the same time, starting from pronunciation training and ship operation training to evaluate the level of maritime English, effectively avoiding the problem of inaccurate evaluation of the user's English level in the field of maritime English.

Description

Technical Field

[0001] The present application relates to the technical field of English training, and in particular to a method, device, equipment and readable storage medium for evaluating maritime English proficiency. Background Art

[0002] As a specialized field of English, Maritime English not only enables ship crews to communicate and work effectively with other ships, air traffic control and port management during international voyages, but also helps maritime workers better understand a lot of data, documents and technical information in the maritime field, thereby enhancing the competitiveness of crew members.

[0003] Currently, there are many methods and techniques for evaluating English proficiency, but there is almost no evaluation of maritime English, which needs to cope with special working environments. As a result, the user's level can only be considered from the English direction during maritime English training, while the importance of the English application environment in this field is ignored, resulting in inaccurate assessment of the user's English level in the field of maritime English. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, equipment and readable storage medium for evaluating maritime English proficiency in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for evaluating maritime English proficiency, comprising the following steps:

[0006] Virtual scenes corresponding to maritime English teaching and training activities are displayed to users through VR devices; virtual scenes are used to instruct users to perform pronunciation training and ship operation training;

[0007] Acquire audio information of the user's pronunciation training, call corresponding preset audio data and perform comparative analysis on the similarity with the audio information, and obtain a first evaluation result of the user's maritime English level based on the analysis result;

[0008] Acquire action information performed by the user based on the instructions of each ship operation training, determine whether the user correctly completes the corresponding action according to the preset action information corresponding to the ship operation training, and obtain a second evaluation result of the user's maritime English level according to the number of times the user correctly completes the corresponding action;

[0009] A first preset weight is respectively assigned to the first evaluation result, a second preset weight is assigned to the second evaluation result, and a weighted calculation is performed to obtain the evaluation result of the user's maritime English level.

[0010] In one embodiment, the step of obtaining audio information of the user performing pronunciation training further includes:

[0011] Creating a virtual ship driving command role for the user, as well as a virtual scene and a corresponding virtual character waiting for command, and instructing the user to command the virtual character to perform actions according to preset English spoken instructions, and obtaining the user's audio information in response to the user completing a spoken instruction; or,

[0012] Create any virtual character of a ship driver or engineer, and communicate with the user through the virtual character according to the driver and engineer contact system, instruct the user to answer according to the communication content, and obtain the user's audio information in response to the user completing a reply dialogue; or

[0013] A 3D model created based on the detailed maps of each cabin of the ship and a screen of indicating arrows are displayed to the user to instruct the user to read out English vocabulary corresponding to the details of each cabin according to the parts indicated by the arrows, and in response to the user completing the reading of an English word, the user's audio information is obtained.

[0014] In one embodiment, the step of calling the corresponding preset audio data and the audio information to perform a comparative analysis on similarity includes:

[0015] Extracting audio features of each frame of audio in the audio information to obtain a target audio feature group, and extracting audio features of each frame of audio of each preset audio data in a virtual scene corresponding to the audio information to obtain multiple comparison audio feature groups;

[0016] Establishing a target feature matrix according to each audio feature in the target audio feature group, and extracting each audio feature in each comparison audio feature group to establish a corresponding comparison feature matrix;

[0017] The target feature matrix is ​​compared with each comparison feature matrix in terms of similarity difference, the comparison feature matrix with the highest similarity is determined, and the corresponding preset audio data is called.

[0018] In one embodiment, the method further comprises:

[0019] Compare the target feature matrix corresponding to the audio information and the comparison feature matrix corresponding to the preset audio data respectively, and perform similarity analysis;

[0020] When the similarity is less than a first preset value, stop displaying the virtual scene to the user and play preset audio data to instruct the user to follow along;

[0021] If the similarity between the audio information obtained by the user after following the preset number of times and the preset audio data is still less than the first preset value, generating a third evaluation result of the user's maritime English proficiency;

[0022] A third preset weight is assigned to the third evaluation result and added to the weighted calculation of the maritime English proficiency evaluation result.

[0023] In one embodiment, the method further comprises:

[0024] Select and mark the audio information whose similarity with the preset audio data is less than a first preset value;

[0025] After the pronunciation training process is completed, prompt information is output to prompt the user to strengthen the training of the virtual scene corresponding to the marked audio information.

[0026] In one embodiment, the method further comprises:

[0027] Obtain the user's identity information;

[0028] In response to determining that the corresponding user identity is a teacher according to the identity information, synchronously obtaining the corresponding user's professional background information and academic background information through the school's teaching affairs system based on the identity information;

[0029] According to the user's work experience in the work background information and the user's academic qualifications in the academic background information, a corresponding preset bonus coefficient is assigned to the user's maritime English proficiency evaluation result;

[0030] The results of the maritime English proficiency assessment are optimized according to the preset bonus coefficient.

[0031] In one embodiment, the step of allocating a corresponding preset bonus coefficient to the user's maritime English proficiency evaluation result according to the user's work experience in the work background information and the user's academic qualifications in the academic background information includes:

[0032] In the case of a senior seafarer with working experience, the corresponding coefficients in the first preset coefficient range are allocated to the evaluation results of the maritime English level from high to low according to the user's level from high to low, and in the case of an ordinary seafarer with working experience, the second preset coefficient is allocated to the evaluation results of the maritime English level; wherein; the corresponding coefficients in the first preset coefficient range are all greater than the second preset coefficient;

[0033] According to the educational background of the user, the corresponding coefficients in the third preset coefficient range are allocated in descending order: doctoral student, graduate student, undergraduate, and junior college;

[0034] A corresponding coefficient in the first preset coefficient range or a second preset coefficient is selected, and a corresponding coefficient in the third preset coefficient range is selected as a preset addition coefficient to optimize the result of the maritime English proficiency evaluation.

[0035] In a second aspect, the present application also provides a device for evaluating maritime English proficiency, comprising:

[0036] The display module is used to display virtual scenes corresponding to maritime English teaching and training activities to users through VR devices; the virtual scenes are used to instruct users to perform pronunciation training and ship operation training;

[0037] A first analysis module is used to obtain audio information of a user performing pronunciation training, call corresponding preset audio data and perform a comparative analysis on the similarity with the audio information, and obtain a first evaluation result of the user's maritime English level based on the analysis result;

[0038] The second analysis module is used to obtain the action information performed by the user based on the instructions of each ship operation training, determine whether the user correctly completes the corresponding action according to the preset action information corresponding to the ship operation training, and obtain a second evaluation result of the user's maritime English level according to the number of times the user correctly completes the corresponding action;

[0039] The weighted calculation module is used to assign a first preset weight to the first evaluation result, assign a second preset weight to the second evaluation result, and perform weighted calculation to obtain the user's maritime English level evaluation result.

[0040] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method provided in the first aspect of the present application are implemented.

[0041] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present application.

[0042] The above-mentioned maritime English proficiency evaluation method, device, equipment and readable storage medium can display virtual scenes for pronunciation training and ship operation training to users through VR equipment, so that users can perform maritime English training in combination with the specific application environment of maritime English; wherein, during the pronunciation training process, the audio information obtained by the user's pronunciation training can be compared and analyzed according to the preset audio data corresponding to the pronunciation training dialogue plan set in advance to determine whether the user's pronunciation is accurate; then, the preset action information of the correct operation corresponding to the pre-set operation training is compared with the action information performed by the user to determine whether the user's ship operation training action is accurate; finally, a first preset weight is assigned to the first evaluation result obtained based on the pronunciation training, and a second preset weight is assigned to the second evaluation result obtained based on the transmission operation training, and a weighted calculation is performed to obtain the user's maritime English proficiency evaluation result, thereby simultaneously starting from pronunciation training and ship operation training based on English proficiency to evaluate the maritime English proficiency, effectively avoiding the problem of inaccurate English proficiency assessment of users in the field of maritime English. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 A schematic diagram of the overall steps of a method for evaluating maritime English proficiency in one embodiment;

[0045] Figure 2 A schematic diagram of the steps of calling a corresponding preset audio data method in one embodiment;

[0046] Figure 3 A schematic diagram of the steps of generating a third evaluation result of a user's maritime English proficiency in one embodiment;

[0047] Figure 4 The step of outputting a prompt in one embodiment is attempted;

[0048] Figure 5 A schematic diagram of the steps of evaluating a teacher in combination with identity information in one embodiment;

[0049] Figure 6 A schematic diagram of the steps of evaluating a teacher in combination with professional background information and academic background information in one embodiment;

[0050] Figure 7 FIG. 4 is a structural diagram of a device for evaluating maritime English proficiency in one embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0053] The first aspect of the present application provides a method for evaluating maritime English proficiency, such as Figure 1 As shown, it includes the following steps 202 to 208. Among them:

[0054] Step 202, showing the user a virtual scene corresponding to the maritime English teaching and training activity through a VR device; the virtual scene is used to instruct the user to perform pronunciation training and ship operation training.

[0055] The virtual scene may be a scene projected to the user through VR glasses or a display screen to instruct and guide the user to learn maritime English.

[0056] Specifically, users may include students and teachers.

[0057] Specifically, the virtual scene may be character dialogues and character actions in stages, as well as indicator marks for prompting the user to respond after the corresponding character dialogues and character actions are completed.

[0058] Furthermore, pronunciation training may include English commands, English conversations, and English reading training performed by users based on virtual scenes; ship operation training may be virtual operation training based on VR equipment performed by users under the guidance of virtual scenes.

[0059] Step 204, obtaining audio information of the user's pronunciation training, calling corresponding preset audio data and the audio information to perform a comparative analysis on similarity, and obtaining a first evaluation result of the user's maritime English level based on the analysis result.

[0060] Specifically, after the user performs pronunciation training according to guidance or instructions, the user's voice is collected to obtain audio information.

[0061] Furthermore, after collecting the sound, the preset audio data is compared and analyzed with the user's audio information. Since the virtual scene is preset, the content of the conversation that the user may make can be predetermined based on each specific screen in the virtual scene, thereby evaluating the user's conversation by means of the preset audio data. After collecting the audio information, the audio information and the preset audio data can be compared by sentence or by paragraph; the audio information can also be collected by sentence and compared with the preset audio data respectively.

[0062] Furthermore, the first evaluation result may be scored according to a preset rule, wherein the preset rule may be a scoring method determined according to the similarity between the audio information and the preset audio data, and the higher the similarity, the higher the first evaluation result.

[0063] Step 206, obtaining the action information performed by the user based on the instructions of each ship operation training, judging whether the user has correctly completed the corresponding action according to the preset action information corresponding to the ship operation training, and obtaining a second evaluation result of the user's maritime English level according to the number of times the user has correctly completed the corresponding action.

[0064] Specifically, it is possible to determine whether the user has completed the corresponding action through the virtual interaction between the virtual scene set in the VR device and the user's action; among them, the prior art fully records the use of algorithms and tracking devices, curvature sensors and other devices to project the user's actions into the virtual scene, and by tracking the user's arm movement angle, movement direction and distance after the instructions of the ship operation training are completed, as well as the degree of finger bending, etc., it is possible to determine whether the user has completed the ship operation as instructed. No further details will be given here.

[0065] Specifically, the second evaluation result and the first evaluation result use the same scoring system, that is, both are based on a 10-point system, both are based on a 100-point system, or both are based on other scoring systems.

[0066] Furthermore, the number of times the user correctly completes the corresponding action, excluding all the actions that need to be completed in the virtual scene, is multiplied by the value specified in the scoring system (i.e., multiplied by 10 for a 10-point system and 100 for a 100-point system) to obtain a second evaluation result.

[0067] Step 208, respectively assigning a first preset weight to the first evaluation result and a second preset weight to the second evaluation result, and performing weighted calculation to obtain the evaluation result of the user's maritime English proficiency.

[0068] Specifically, the setting of the first preset weight and the second preset weight can be determined according to the focus of the user to be assessed during the specific implementation process.

[0069] For example, if the focus of the assessed user is mainly on reading navigation-related documents, driving and engine room communication, etc., the setting value of the first preset weight is higher than the second preset weight; if the focus of the assessed user is mainly on ship driving and engine room maintenance, etc., the setting value of the second preset weight is higher than the first preset weight. It can also be set according to the scores of most students as users to improve the focus of user learning.

[0070] In an exemplary embodiment, the step of obtaining audio information of the user performing pronunciation training further includes:

[0071] Creating a virtual ship driving command role for the user, as well as a virtual scene and a corresponding virtual character waiting for command, and instructing the user to command the virtual character to perform actions according to preset English spoken instructions, and obtaining the user's audio information in response to the user completing a spoken instruction; or,

[0072] Create any virtual character of a ship driver or engineer, and communicate with the user through the virtual character according to the driver and engineer contact system, instruct the user to answer according to the communication content, and obtain the user's audio information in response to the user completing a reply dialogue; or

[0073] A 3D model created based on the detailed maps of each cabin of the ship and a screen of indicating arrows are displayed to the user to instruct the user to read out English vocabulary corresponding to the details of each cabin according to the parts indicated by the arrows, and in response to the user completing the reading of an English word, the user's audio information is obtained.

[0074] Specifically, the virtual scene can be a plurality of different scenes stored in the scene library, which are called according to the user's choice during the specific implementation process; when choosing to command a virtual character, the user needs to instruct the virtual character through standard nautical English pronunciation and professional system specifications, and the spoken language in response to the user's instructions is consistent with the preset audio data, and the virtual character completes the action in the scene, and after each oral instruction is completed, the sound collection device collects the completed oral instruction as audio information; when conducting training on the ship's engine room contact system, it is also possible to create a virtual character and conduct a guided dialogue with the user according to the driving and engine room contact system; and when it is necessary to examine the user's vocabulary, 3Dmax or other corresponding software can be used to perform step-by-step rendering from mapping to model, and model creation and delivery are both existing technologies and will not be repeated here.

[0075] Specifically, the cabin details include the engine room, cockpit, cargo hold and other cabin details. For example, the engine room also includes the main engine, auxiliary engine, oil separator, boiler, oil-water separator, air compressor, anchor windlass, capstan, steering gear, pump, pipeline, air conditioner, fresh water maker and other equipment's specific details, such as cross-section. When the user is answering the question, the surface of the cabin details can be peeled off layer by layer, and the details can be displayed to the user through scene switching, scene rotation and combined with arrow instructions, so as to guide the user to conduct word examination and learning in different directions.

[0076] In an exemplary embodiment, Figure 2 As shown, the step of calling the corresponding preset audio data and the audio information to perform a comparative analysis on the similarity includes the following steps 2042 to 2046. Among them:

[0077] Step 2042, extracting audio features of each frame of audio in the audio information to obtain a target audio feature group, and extracting audio features of each frame of audio of each preset audio data in a virtual scene corresponding to the audio information to obtain multiple comparison audio feature groups.

[0078] Specifically, the audio features may include Mel-Frequency Cepstral Coefficients (MFCC), spectrum envelopes, or short-time energy, which are not specifically limited herein.

[0079] Furthermore, in the feature extraction process, the sound signal can be divided into time windows and each window can be processed for extraction.

[0080] Step 2044: establish a target feature matrix according to each audio feature in the target audio feature group, and extract each audio feature in each comparative audio feature group to establish a corresponding comparative feature matrix.

[0081] Step 2046, compare the similarity difference between the target feature matrix and each comparison feature matrix, determine the comparison feature matrix with the highest similarity, and call the corresponding preset audio data.

[0082] The similarity between the feature vectors or matrices of two sounds is calculated by calculating the Euclidean distance or cosine similarity between the target feature matrix and each comparison feature matrix, so as to quantify the similarity between the target feature matrix and each comparison feature matrix.

[0083] It should be noted that for different virtual scenes, there may be multiple different scene dialogues, and the answers to the dialogue or response guidance in a certain virtual scene are not unique. Therefore, by presetting multiple answers, the flexibility of the user interaction process is increased, and then the similarity between the user audio information and the preset answers is judged to select the preset audio data that best matches the user's answer, and then the user's answer is analyzed, which can also more effectively analyze the accuracy of the user's answer.

[0084] In an exemplary embodiment, Figure 3 As shown, the method for evaluating the level of maritime English also includes the following steps 302 to 308. Among them:

[0085] Step 302 , respectively compare the target feature matrix corresponding to the audio information and the comparison feature matrix corresponding to the preset audio data, and perform similarity analysis.

[0086] Step 304: When the similarity is less than the first preset value, stop displaying the virtual scene to the user and play the preset audio data to instruct the user to follow along.

[0087] Specifically, after the first evaluation result is obtained based on the audio similarity calculation, in order to enable the user to effectively improve his or her English level, the user can be made aware of his or her own gaps and shortcomings by playing the preset audio data.

[0088] Furthermore, the first preset value can be reasonably set after multiple rounds of experiments in combination with the recognition capability of the device and the amount of pre-stored preset audio data, and no specific limitation is made here.

[0089] Step 306: If the similarity between the audio information obtained by the user after following the preset number of times and the preset audio data is still less than the first preset value, a third evaluation result of the user's maritime English level is generated.

[0090] Specifically, when the value is continuously less than the first preset value, it indicates that the user's English learning ability is weak, and the user's English learning ability is reflected by setting the third evaluation result.

[0091] Step 308, assigning a third preset weight to the third evaluation result and adding it to the weighted calculation of the maritime English proficiency evaluation result.

[0092] Specifically, the third preset weight may be smaller than the first preset weight and the second preset weight, so as to avoid the unfamiliarity with a certain system or vocabulary from excessively affecting the final maritime English proficiency evaluation result.

[0093] Specifically, the third preset weight is a negative number less than 1, and the scoring system of the third evaluation result is the same as that of the first evaluation result and the second evaluation result.

[0094] Furthermore, a third preset weight is assigned to the third evaluation result and added to the weighted calculation of the maritime English proficiency evaluation result, specifically including adding the product of the third preset weight and the third evaluation result to the maritime English proficiency evaluation result.

[0095] In an exemplary embodiment, Figure 4 As shown, the method for evaluating the level of maritime English also includes the following steps 402 to 404. Among them:

[0096] Step 402: Select and mark audio information whose similarity with the preset audio data is less than a first preset value.

[0097] Specifically, in the case of similarity comparison based on audio features, whether the answer is too different from the preset audio data or the standard of pronunciation is too different from the preset audio data, the result will be that the similarity of the comparison is less than the first preset value. Therefore, the audio information whose similarity compared with the preset audio data is less than the first preset value is used to indicate that the user's answer is not standard. Marking the audio information of this part will help users find out their own shortcomings in specific simulation scenarios.

[0098] Step 404: after the pronunciation training process is completed, output prompt information for prompting the user to strengthen the training of the virtual scene corresponding to the marked audio information.

[0099] Furthermore, outputting prompt information can more intuitively remind users to study.

[0100] In an exemplary embodiment, Figure 5 As shown, the method for evaluating the level of maritime English also includes the following steps 502 to 508. Among them:

[0101] Step 502, obtaining the user's identity information;

[0102] Specifically, identity information can be obtained based on the student or teacher's name and unique identity ID;

[0103] Exemplarily, it can be obtained by identifying a campus card or an electronic student card.

[0104] Step 504, in response to determining that the corresponding user identity is a teacher according to the identity information, the corresponding user's professional background information and academic background information are synchronously obtained through the school's educational affairs system based on the identity information.

[0105] Specifically, when the user is a teacher, since the assessment is for the Maritime English major, it indicates to a certain extent that the user may have sailing experience. Therefore, the user's work experience can be obtained through the academic affairs system, which helps to more accurately understand the user's Maritime English teaching ability.

[0106] Step 506, assigning a corresponding preset bonus coefficient to the user's maritime English proficiency evaluation result according to the user's work experience in the work background information and the user's academic qualifications in the academic background information.

[0107] Specifically, setting bonus coefficients for users according to their work experience and academic qualifications can more fairly verify their maritime English teaching ability, rather than limiting ability assessment to pronunciation training and ship operation training.

[0108] Furthermore, the bonus coefficient can be set specifically according to the direction of this assessment.

[0109] Specifically, if the direction of this assessment is mainly pronunciation training or ship operation training, a lower preset bonus coefficient will be set; if it is mainly based on the comprehensive level, a higher preset bonus coefficient will be set.

[0110] Exemplarily, the lower preset addition coefficient is 1.1, and the higher preset addition coefficient is 1.2-1.3.

[0111] Step 508, optimizing the maritime English proficiency evaluation result according to a preset bonus coefficient.

[0112] Specifically, the maritime English proficiency evaluation result can be optimized by multiplying the maritime English proficiency evaluation result by a bonus coefficient.

[0113] In an exemplary embodiment, Figure 6 As shown, the step of allocating a corresponding preset bonus coefficient to the user's maritime English proficiency evaluation result according to the user's work experience in the work background information and the user's academic background information includes the following steps 5062 to 5066. Among them:

[0114] Step 5062, when the working experience is that of a senior seafarer, the corresponding coefficients in the first preset coefficient range are allocated to the evaluation results of the maritime English level from high to low according to the user's level from high to low; when the working experience is that of an ordinary seafarer, the second preset coefficient is allocated to the evaluation results of the maritime English level; wherein; the corresponding coefficients in the first preset coefficient range are all greater than the second preset coefficients.

[0115] Specifically, senior seafarers include senior seafarers majoring in navigation technology or senior seafarers majoring in marine engineering.

[0116] Furthermore, in the case of working experience as a senior seafarer, a coefficient in a first preset coefficient range from high to low is assigned to the maritime English evaluation result according to the user level being captain, first mate, second mate, third mate or the user level being chief engineer, second engineer, second engineer, third engineer; wherein the first preset coefficient range includes multiple coefficients corresponding one-to-one to different user levels, and each coefficient is equidistant.

[0117] Step 5064, assign corresponding coefficients in the third preset coefficient range in descending order according to the user's educational background: doctoral candidate, graduate student, undergraduate, and associate degree.

[0118] Specifically, the third preset coefficient range includes a plurality of coefficients corresponding to different user levels one by one, and intervals between each coefficient are equal.

[0119] Step 5066, selecting a corresponding coefficient in the first preset coefficient range or a second preset coefficient, and selecting a corresponding coefficient in the third preset coefficient range as preset additive coefficients to optimize the maritime English proficiency evaluation result.

[0120] Specifically, the preset addition coefficient is used to optimize the evaluation result of the maritime English proficiency, that is, the preset addition coefficient is multiplied by the maritime English evaluation result.

[0121] Furthermore, a corresponding coefficient in the first preset coefficient range or a second preset coefficient is selected, and a corresponding coefficient in the third preset coefficient range is selected as a preset additional coefficient to optimize the result of the maritime English proficiency evaluation, that is, the corresponding coefficient in the first preset coefficient range or the second preset coefficient is multiplied by the maritime English evaluation result, and the corresponding coefficient in the third preset coefficient range is multiplied by the maritime English evaluation result.

[0122] Specifically, the corresponding coefficients in the first preset coefficient range, the second preset coefficient, and the corresponding coefficients in the third preset coefficient range are all set between 1 and 2 according to specific implementation conditions.

[0123] In an exemplary embodiment, in response to identifying the user as a teacher through identity information, the teacher's maritime English level is graded according to the maritime English evaluation result obtained by the teacher and the preset grade.

[0124] Specifically, the maritime English level can be divided into entry level, elementary level, intermediate level, advanced level and elite level from low to high according to the preset final score intervals of the maritime English evaluation results; among them: when the maritime English evaluation result of the user with the teacher identity is advanced or above, a prompt message is output that the user with the teacher identity is qualified to teach.

[0125] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0126] Based on the same inventive concept, the embodiment of the present application also provides a Maritime English proficiency evaluation device for implementing the Maritime English proficiency evaluation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the Maritime English proficiency evaluation device provided below can refer to the limitations of the Maritime English proficiency evaluation method above, and will not be repeated here.

[0127] In a second aspect, in an exemplary embodiment, Figure 7 As shown, the present application provides a maritime English proficiency evaluation device 700, the device comprising:

[0128] The display module 701 is used to display virtual scenes corresponding to the maritime English teaching and training activities to users through VR equipment; the virtual scenes are used to instruct users to perform pronunciation training and ship operation training;

[0129] The first analysis module 702 is used to obtain the audio information of the user's pronunciation training, call the corresponding preset audio data and the audio information to perform a comparative analysis on similarity, and obtain a first evaluation result of the user's maritime English level based on the analysis result;

[0130] The second analysis module 703 is used to obtain the action information performed by the user based on the instructions of each ship operation training, determine whether the user correctly completes the corresponding action according to the preset action information corresponding to the ship operation training, and obtain a second evaluation result of the user's maritime English level according to the number of times the user correctly completes the corresponding action;

[0131] The weighted calculation module 704 is used to assign a first preset weight to the first evaluation result, assign a second preset weight to the second evaluation result, and perform weighted calculation to obtain the user's maritime English proficiency evaluation result.

[0132] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method provided in the first aspect of the present application are implemented.

[0133] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present application.

[0134] Each module in the above-mentioned Maritime English training device based on virtual reality interaction can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0135] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0136] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0137] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for evaluating maritime English proficiency, characterized in that: The steps include: Displaying virtual scenes corresponding to maritime English teaching and training activities to users through VR devices; the virtual scenes are used to instruct users to perform pronunciation training and ship operation training; Acquiring audio information of the user performing the pronunciation training, calling corresponding preset audio data to perform a comparative analysis on similarity with the audio information, and obtaining a first evaluation result of the user's maritime English level based on the analysis result; The step of obtaining the audio information of the user performing the pronunciation training includes: creating a virtual ship driving command role for the user, as well as creating a virtual scene and a corresponding virtual character waiting for command, and instructing the user to command the virtual character to perform actions according to preset English spoken instructions, and obtaining the user's audio information in response to the user completing a spoken instruction; or, creating any virtual character of a ship driver or an engineer, and communicating with the user according to the driving and engine contact system through the virtual character, instructing the user to answer according to the communication content, and obtaining the user's audio information in response to the user completing a reply dialogue; or, showing the user a 3D model created based on the detailed map of each cabin of the ship and a picture of an indicating arrow, so as to instruct the user to read out English vocabulary corresponding to the details of each cabin of the ship according to the parts indicated by the arrows, and obtaining the user's audio information in response to the user completing the reading of an English word; The step of calling the corresponding preset audio data to conduct a comparative analysis on the similarity with the audio information includes: extracting the audio features of each frame of audio in the audio information to obtain a target audio feature group, and in a virtual scene corresponding to the audio information, obtaining multiple comparative audio feature groups from the audio features of each frame of audio of each preset audio data in a plurality of preset audio data; establishing a target feature matrix according to each audio feature in the target audio feature group, and extracting each audio feature in each comparative audio feature group to establish a corresponding comparative feature matrix; comparing the similarity difference between the target feature matrix and each comparative feature matrix, determining the comparative feature matrix with the highest similarity, and calling the corresponding preset audio data; Acquiring action information performed by the user based on the instructions of each ship operation training, judging whether the user correctly completes the corresponding action according to the preset action information corresponding to the ship operation training, and obtaining a second evaluation result of the user's maritime English level according to the number of times the user correctly completes the corresponding action; respectively assigning a first preset weight to the first evaluation result and a second preset weight to the second evaluation result, and performing weighted calculation to obtain the evaluation result of the user's maritime English level; Respectively comparing the target feature matrix corresponding to the audio information and the comparison feature matrix corresponding to the preset audio data, and performing similarity analysis; When the similarity is less than a first preset value, stop displaying the virtual scene to the user and play the preset audio data to instruct the user to follow along; If the similarity between the audio information obtained by the user after reading the preset number of times and the preset audio data is still less than the first preset value, generating a third evaluation result of the user's maritime English proficiency; A third preset weight is assigned to the third evaluation result and added to the weighted calculation of the maritime English proficiency evaluation result.

2. The method according to claim 1, characterized in that The method further comprises: Select and mark the audio information whose similarity with the preset audio data is less than a first preset value; After the pronunciation training process is completed, prompt information is output to prompt the user to strengthen the training of the virtual scene corresponding to the marked audio information.

3. The method according to claim 1, characterized in that The method further comprises: Obtain the user's identity information; In response to determining that the corresponding user identity is a teacher according to the identity information, synchronously obtaining the corresponding user's professional background information and academic background information through the school's educational affairs system based on the identity information; According to the user's work experience in the work background information and the user's academic qualifications in the academic background information, a corresponding preset bonus coefficient is assigned to the user's maritime English proficiency evaluation result; The maritime English proficiency evaluation result is optimized according to the preset bonus coefficient.

4. The method according to claim 3, characterized in that The step of allocating a corresponding preset bonus coefficient to the user's maritime English proficiency evaluation result according to the user's work experience in the work background information and the user's academic qualifications in the academic background information comprises: In the case where the working experience is that of a senior seafarer, the corresponding coefficients in the first preset coefficient range are allocated to the evaluation result of the maritime English level from high to low according to the user's level from high to low, and in the case where the working experience is that of an ordinary seafarer, the second preset coefficient is allocated to the evaluation result of the maritime English level; wherein; the corresponding coefficients in the first preset coefficient range are all greater than the second preset coefficient; According to the user's educational background, the corresponding coefficients in the third preset coefficient range are allocated in descending order: doctoral student, graduate student, undergraduate, and junior college; The corresponding coefficient in the first preset coefficient range or the second preset coefficient is selected, and the corresponding coefficient in the third preset coefficient range is selected as the preset addition coefficient to optimize the maritime English proficiency evaluation result.

5. A device for evaluating maritime English proficiency, characterized in that: Applied to the method according to any one of claims 1 to 4, the device comprises: A display module is used to display virtual scenes corresponding to maritime English teaching and training activities to users through VR devices; the virtual scenes are used to instruct users to perform pronunciation training and ship operation training; A first analysis module is used to obtain audio information of the user performing the pronunciation training, call the corresponding preset audio data and perform a comparative analysis on the similarity with the audio information, and obtain a first evaluation result of the user's maritime English level based on the analysis result; The second analysis module is used to obtain the action information performed by the user based on the instructions of each ship operation training, determine whether the user correctly completes the corresponding action according to the preset action information corresponding to the ship operation training, and obtain a second evaluation result of the user's maritime English level according to the number of times the user correctly completes the corresponding action; The weighted calculation module is used to assign a first preset weight to the first evaluation result, assign a second preset weight to the second evaluation result, and perform weighted calculation to obtain the evaluation result of the user's maritime English level.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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