Reading evaluation method and device, electronic equipment and storage medium

Abstract

The invention discloses a reading evaluation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring user reading data; wherein the user reading data comprises user reading text data and user reading audio data corresponding to the user reading text data; inputting the user reading data into a reading evaluation model to obtain user reading evaluation data; and analyzing and processing the user reading evaluation data according to the reading pronunciation scoring rule, generating a user reading evaluation report, and displaying the user reading evaluation report through a visual interface. The method can quickly and accurately analyze the overall reading pronunciation condition of the testee, further assists the testee in correcting the reading pronunciation, and can be widely applied to the technical field of data processing.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a reading assessment method, device, electronic device and storage medium. Background Art

[0002] Reading aloud means reading an article or work clearly and loudly. It is a way of expression that converts text into spoken language, and accurate pronunciation can ensure that the audience correctly understands the content of the reading aloud. In the process of reading aloud, if the pronunciation is inaccurate, it may cause the audience to misunderstand or fail to understand the true intention of the article. In traditional reading aloud pronunciation evaluation schemes, they often rely on personal experience and subjective judgment, resulting in inconsistency and unfairness in the evaluation results, making the evaluation results unstable and difficult for users to improve their reading aloud pronunciation in a targeted manner.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the invention

[0004] The embodiments of the present application aim to solve at least one of the technical problems in the related art to a certain extent. To this end, the main purpose of the embodiments of the present application is to provide a reading assessment method, device, electronic device and storage medium, which can quickly and accurately analyze the overall reading pronunciation of the subject, and then assist the subject to correct the reading pronunciation.

[0005] To achieve the above purpose, one aspect of an embodiment of the present application provides a reading evaluation method, which includes the following steps:

[0006] Acquire user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data;

[0007] Inputting the user reading data into a reading evaluation model to obtain user reading evaluation data;

[0008] The user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rules to generate a user reading evaluation report, and the user reading evaluation report is displayed through a visual interface.

[0009] In some embodiments, inputting the user reading data into a reading evaluation model to obtain the user reading evaluation data includes:

[0010] Inputting the user's reading data into the reading evaluation model;

[0011] The reading evaluation model analyzes and processes the user's reading audio data according to the user's reading text data and preset model evaluation rules to obtain the user's reading evaluation data.

[0012] In some embodiments, the user reading evaluation data includes user evaluation tone data, user evaluation syllable data and user evaluation word pronunciation data, and the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rules to generate a user reading evaluation report, and the user reading evaluation report is displayed through a visual interface, including:

[0013] Analyzing and processing the user evaluation tone data in the user reading evaluation data according to the reading pronunciation scoring rule to obtain the tone accuracy rate corresponding to the user reading audio data;

[0014] Analyzing and processing the user evaluation syllable data in the user reading evaluation data according to the reading pronunciation scoring rule to obtain the syllable accuracy rate corresponding to the user reading audio data;

[0015] Analyze and process the user evaluation character pronunciation data in the user reading evaluation data according to the reading pronunciation scoring rule to obtain a weak Chinese character statistical set corresponding to the user reading audio data;

[0016] Generating the user reading evaluation report based on the tone accuracy rate, the syllable accuracy rate and the weak Chinese character statistical set;

[0017] The user reading evaluation report is displayed through a visual interface.

[0018] In some embodiments, the user-assessed tone data includes user-assessed tone and user-assessed tone score, and the user-assessed tone data in the user-reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule to obtain the tone accuracy rate corresponding to the user-reading audio data, including:

[0019] Classifying the user evaluation tones to obtain a plurality of user evaluation tone sets;

[0020] Counting the number of target user evaluation tones corresponding to each of the user evaluation tone sets;

[0021] The tone accuracy rate corresponding to the user-read audio data is calculated based on the number of target user-evaluated tones and the user-evaluated tone scores corresponding to each user-evaluated tone set.

[0022] In some embodiments, calculating the tone accuracy rate corresponding to the user reading audio data according to the number of target user evaluation tones and the user evaluation tone score corresponding to each user evaluation tone set includes:

[0023] Calculating the target set tone accuracy rate corresponding to each of the user evaluation tone sets according to the number of the target user evaluation tone sets corresponding to each of the user evaluation tone sets and the user evaluation tone scores;

[0024] The target set tone accuracy corresponding to each of the user evaluation tone sets is used as the tone accuracy corresponding to the user reading audio data.

[0025] In some embodiments, the user evaluation syllable data includes user evaluation syllables and user evaluation syllable scores, and the user evaluation syllable data in the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule to obtain the syllable accuracy corresponding to the user reading audio data, including:

[0026] Classifying the user evaluation syllables to obtain a plurality of user evaluation syllable sets;

[0027] Counting the number of target user evaluation syllables corresponding to each of the user evaluation syllable sets;

[0028] The syllable accuracy rate corresponding to the user-reading audio data is calculated based on the target user-evaluated syllable quantity and the user-evaluated syllable score corresponding to each user-evaluated syllable set.

[0029] In some embodiments, the user-evaluated character pronunciation data includes a character pronunciation score, and the user-evaluated character pronunciation data in the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule to obtain a weak Chinese character statistical set corresponding to the user reading audio data, including:

[0030] The character pronunciation scores in the user-evaluated character pronunciation data are statistically analyzed according to a preset character pronunciation threshold, and the weak Chinese character statistical set corresponding to the user's reading audio data is calculated.

[0031] To achieve the above purpose, another aspect of the embodiment of the present application provides a reading evaluation device, which includes the following modules:

[0032] A user reading data acquisition module, used to acquire user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data;

[0033] A user reading data evaluation module, used for inputting the user reading data into a reading evaluation model to obtain user reading evaluation data;

[0034] The user reading evaluation data analysis module is used to analyze and process the user reading evaluation data according to the reading pronunciation scoring rules, generate a user reading evaluation report, and display the user reading evaluation report through a visual interface.

[0035] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above-mentioned method when executing the computer program.

[0036] To achieve the above objective, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0037] The embodiments of the present application at least include the following beneficial effects: the present application provides a reading evaluation method, device, electronic device and storage medium, the scheme obtains user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data; the user reading data is input into the reading evaluation model to obtain the user reading evaluation data; the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule, a user reading evaluation report is generated, and the user reading evaluation report is displayed through a visual interface. The embodiment of the present application can quickly and accurately analyze the overall reading pronunciation of the subject by designing an auxiliary scoring rule for reading pronunciation. At the same time, the use of a unified reading pronunciation scoring rule ensures the consistency and fairness of the scoring, so that the user's reading at different times or different occasions can be objectively evaluated. The reading pronunciation scoring rule can also help the system more accurately identify the user's pronunciation errors or deficiencies. In addition, by displaying the generated user reading evaluation report through a visual interface, the subject can be assisted to correct the reading pronunciation in a targeted manner, so that the audience can correctly understand the content of the reading. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flowchart of the steps of a reading evaluation method provided in an embodiment of the present application;

[0039] Figure 2 It is a flowchart of a reading evaluation method provided in an embodiment of the present application;

[0040] Figure 3 It is a schematic diagram of a flow chart of syllable data analysis provided in an embodiment of the present application;

[0041] Figure 4 It is a flowchart of a tone data analysis provided in an embodiment of the present application;

[0042] Figure 5 It is a flow chart of a character pronunciation data analysis provided by an embodiment of the present application;

[0043] Figure 6 It is a structural schematic diagram of a reading evaluation device provided in an embodiment of the present application;

[0044] Figure 7 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are only examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the attached claims.

[0046] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0047] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0049] Reading aloud means reading an article or work clearly and loudly. It is a way of expression that converts text into spoken language, and accurate pronunciation can ensure that the audience correctly understands the content of the reading aloud. In the process of reading aloud, if the pronunciation is inaccurate, it may cause the audience to misunderstand or fail to understand the true intention of the article. In traditional reading aloud pronunciation evaluation schemes, they often rely on personal experience and subjective judgment, resulting in inconsistency and unfairness in the evaluation results, making the evaluation results unstable and difficult for users to improve their reading aloud pronunciation in a targeted manner.

[0050] In view of this, a method, device, electronic device and storage medium for evaluating reading aloud are provided in the embodiments of the present application. The scheme obtains user reading aloud data; wherein the user reading aloud data includes user reading aloud text data and user reading aloud audio data corresponding to the user reading aloud text data; the user reading aloud data is input into the reading aloud evaluation model to obtain the user reading aloud evaluation data; the user reading aloud evaluation data is analyzed and processed according to the reading aloud pronunciation scoring rule, a user reading aloud evaluation report is generated, and the user reading aloud evaluation report is displayed through a visual interface. The embodiment of the present application can quickly and accurately analyze the overall reading aloud pronunciation of the subject by designing an auxiliary scoring rule for reading aloud pronunciation. At the same time, the use of a unified reading aloud pronunciation scoring rule ensures the consistency and fairness of the scoring, so that the user's reading aloud at different times or different occasions can be objectively evaluated. The reading aloud pronunciation scoring rule can also help the system more accurately identify the user's pronunciation errors or deficiencies. In addition, by displaying the generated user reading aloud evaluation report through a visual interface, the subject can be assisted to correct the reading aloud pronunciation in a targeted manner, so that the audience can correctly understand the content of the reading aloud.

[0051] The reading and evaluation method provided in the embodiment of the present application relates to the field of data processing technology. The reading and evaluation method provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a car terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or it can be configured as a server cluster or a distributed system composed of multiple physical servers, and can also be configured to provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content De l ivery Network, content distribution network) and big data and artificial intelligence platforms and other basic cloud computing services. The cloud server, the server can also be a node server in the blockchain network; the software can be an application that implements the reading and evaluation method, etc., but is not limited to the above forms.

[0052] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs (personal computers), minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0053] See also Figure 1 , Figure 1 is an optional step flow chart of the reading evaluation method provided in the embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S103.

[0054] Step S101, obtaining user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data;

[0055] The reading evaluation method provided in the embodiment of the present application can be applied to smart terminals, such as mobile phones, etc. The reading pronunciation evaluation of the user can be realized by installing a reading evaluation application on the smart terminal.

[0056] The user reading data is data used by the user (tested person) to evaluate the reading pronunciation, and the user reading data includes the user reading text data and the user reading audio data corresponding to the user reading text data. The user reading text data is the material selected by the user to be evaluated; the user reading audio data is the audio data collected after the user reads the user reading text data. The reading pronunciation evaluation result can be obtained by analyzing and processing the audio data.

[0057] In the specific implementation, first, the user uses the reading evaluation application on the smart terminal to select the material that needs to be evaluated. When the user selects the material, the reading evaluation application will send the material text to the reading evaluation model, informing the reading evaluation model of the text content that needs to be evaluated; then, when the user starts reading aloud, the reading evaluation application collects the audio of the user's reading through the device microphone, collects the analog signal through the device microphone and inputs it into the audio mainboard, and then converts it into a digital signal through an analog-to-digital converter and inputs it into the device host. The reading evaluation application then obtains the digital information data on the device and sends it to the reading evaluation model, and the reading evaluation model performs the reading evaluation.

[0058] Step S102, inputting the user reading data into a reading evaluation model to obtain user reading evaluation data;

[0059] In some embodiments, step S102 may include: inputting the user's reading data into the reading evaluation model; analyzing and processing the user's reading audio data according to the user's reading text data and preset model evaluation rules through the reading evaluation model to obtain the user's reading evaluation data.

[0060] Among them, the reading evaluation model is an artificial intelligence model used to evaluate and provide feedback on the user's reading performance. The model can be constructed based on machine learning and deep learning technologies, and is trained by a large amount of historical reading data and corresponding evaluation labels. It can recognize and distinguish different voice features and evaluate the quality of reading accordingly. The reading evaluation model analyzes the user's reading audio data to evaluate their reading performance, such as pronunciation accuracy, fluency, intonation, rhythm, etc. It should be noted that the selection of the reading evaluation model is not limited in the embodiments of the present application. For the specific construction content and implementation principle of the reading evaluation model, the specific technical solution of the reading evaluation model in the relevant technology can be referred to and selected, and the embodiments of the present application will not be repeated here.

[0061] In an embodiment of the present application, by configuring a preset model evaluation rule in the reading evaluation model, the reading evaluation model can obtain the tone, tone score, syllable information, and word pronunciation score when analyzing and processing the user's reading audio data. Among them, the tone includes yinping, yangping, shangsheng, and qusheng; the tone score includes yinping tone score, yangping tone score, shangsheng tone score, and qusheng tone score; the syllable information includes initial consonants, finals, initial consonant scores, and final consonant scores. It should be noted that the preset model evaluation rule is a rule for training the reading evaluation model to identify the attribute description (tone, tone score, syllable information, word pronunciation score) of each word in the user evaluation text, which can be set according to the actual application situation, and the embodiment of the present application does not limit this.

[0062] The user reading evaluation data is the attribute description content (tone, tone score, syllable information, character pronunciation score) of each word in the user evaluation text data output by the reading evaluation model.

[0063] In Chinese Pinyin, a syllable is generally composed of an initial consonant, a final vowel and a tone. A Chinese syllable must contain a final vowel, but not necessarily an initial consonant. If there is an initial consonant, it is at the beginning, and the final vowel can be at the beginning or the end. The initial consonant is the consonant at the beginning of the syllable; the final vowel is the part after the initial consonant, including vowels and consonants; the tone indicates the pitch change of the syllable, such as yinping, yangping, shangsheng, qusheng, etc. The initial consonant, final vowel and tone are important components of pronunciation, and together constitute the syllables of Chinese, and form a rich voice system through different combinations and changes. The embodiment of the present application can accurately analyze the user's reading pronunciation by analyzing the syllable data.

[0064] Step S103: analyzing and processing the user reading evaluation data according to the reading pronunciation scoring rules, generating a user reading evaluation report, and displaying the user reading evaluation report through a visual interface.

[0065] Among them, the reading pronunciation scoring rules are a set of preset criteria used to evaluate the pronunciation quality of users when reading aloud. The reading pronunciation scoring rules include evaluation criteria for the correct pronunciation of phonemes, clarity of syllables, appropriateness of intonation, accuracy of rhythm, etc.

[0066] In the embodiment of the present application, it mainly includes evaluation criteria for tone data, syllable data and character pronunciation data. The reading pronunciation scoring rule is used to calculate the tone accuracy, syllable accuracy and weak Chinese character statistics corresponding to the u user evaluation audio data according to the preset statistical calculation rules and their calculation formulas.

[0067] The user reading evaluation data includes user evaluation tone data, user evaluation syllable data and user evaluation word pronunciation data.

[0068] The user-assessed tone data may include user-assessed tones and user-assessed tone scores, wherein the user-assessed tones include yinping tone, yangping tone, shangsheng tone and qusheng tone; and the user-assessed tone scores include yinping tone scores, yangping tone scores, shangsheng tone scores and qusheng tone scores.

[0069] The user-evaluated syllable data may include user-evaluated syllables and user-evaluated syllable scores, wherein the user-evaluated syllables include initial consonants and final consonants, and the user-evaluated syllable scores include initial consonant scores and final consonant scores.

[0070] For user-assessed character pronunciation data, it may include a character pronunciation score.

[0071] In some embodiments, step S103 may include: analyzing and processing the user evaluation tone data in the user reading evaluation data according to the reading pronunciation scoring rules to obtain the tone accuracy corresponding to the user reading audio data; analyzing and processing the user evaluation syllable data in the user reading evaluation data according to the reading pronunciation scoring rules to obtain the syllable accuracy corresponding to the user reading audio data; analyzing and processing the user evaluation word pronunciation data in the user reading evaluation data according to the reading pronunciation scoring rules to obtain the weak Chinese character statistical set corresponding to the user reading audio data; generating a user reading evaluation report based on the tone accuracy, syllable accuracy and weak Chinese character statistical set; and displaying the user reading evaluation report through a visual interface.

[0072] Among them, the tone accuracy rate refers to the ratio of the user's correctly pronounced tones during the reading process, which is calculated by comparing the user's tone pronunciation with the standard pronunciation. The syllable accuracy rate refers to the ratio of the user's correctly pronounced syllables during the reading process, which is calculated by comparing the user's syllable pronunciation with the standard pronunciation. The weak Chinese character statistical set refers to the set of Chinese characters that the system identifies as inaccurate or frequently incorrectly pronounced by the user after analyzing the user's reading data. It can help users practice the difficult-to-pronounce Chinese characters in a targeted manner, thereby improving the overall reading level.

[0073] The user reading evaluation report includes detailed analysis results of the user's reading performance, such as tone accuracy, syllable accuracy, and weak Chinese character statistics. In addition, the user reading evaluation report also includes specific scores, rankings, improvement trends, and personalized improvement suggestions.

[0074] As for the visual interface, it is a graphical user interface used to display the user's reading evaluation report. Through visual elements such as charts, colors, and graphics, the evaluation results are made more intuitive and easy to understand.

[0075] In some specific embodiments, the user evaluation tone data in the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rules to obtain the tone accuracy corresponding to the user reading audio data, which may include: classifying the user evaluation tones to obtain a number of user evaluation tone sets; counting the number of target user evaluation tones corresponding to each user evaluation tone set; and calculating the tone accuracy corresponding to the user reading audio data based on the number of target user evaluation tones corresponding to each user evaluation tone set and the user evaluation tone score.

[0076] In some specific embodiments, calculating the tone accuracy corresponding to the user's reading audio data based on the number of target user-evaluated tones corresponding to each user-evaluated tone set and the user-evaluated tone scores may include: calculating the target set tone accuracy corresponding to each user-evaluated tone set based on the number of target user-evaluated tones corresponding to each user-evaluated tone set and the user-evaluated tone scores; using the target set tone accuracy corresponding to each user-evaluated tone set as the tone accuracy corresponding to the user's reading audio data.

[0077] The user-evaluated tone set includes a yinping tone set, a yangping tone set, a shangsheng tone set, and a qusheng tone set.

[0078] For the target user-evaluated tone number, it is the number of user-evaluated tones that meet the target score threshold selected from the user-evaluated tone set. For example, assuming that the user-evaluated tone set is a yinping tone set, yinping tones with scores greater than or equal to 60 can be screened out from the yinping tone set, and finally the number of yinping tones with scores greater than or equal to 60 is counted as the target user-evaluated yinping number, which is used to calculate the yinping tone accuracy rate.

[0079] The target set tone accuracy is calculated based on the number of target user-evaluated tones corresponding to the user-evaluated tone set and the user-evaluated tone score. The target set tone accuracy includes the yinping tone accuracy, yangping tone accuracy, shangsheng tone accuracy, and qusheng tone accuracy, that is, the tone accuracy corresponding to the user's reading audio data includes the yinping tone accuracy, yangping tone accuracy, shangsheng tone accuracy, and qusheng tone accuracy.

[0080] Among them, the calculation formulas of the accuracy rate of Yinping tone, Yangping tone accuracy rate, Shangsheng tone accuracy rate and Qusheng tone accuracy rate are: Yinping tone accuracy rate = the number of Yinping with more than 60 points / the total number of Yinping; Yangping tone accuracy rate = the number of Yangping with more than 60 points / the total number of Yangping; Shangsheng tone accuracy rate = the number of Shangsheng with more than 60 points / the total number of Shangsheng; Qusheng tone accuracy rate = the number of Qusheng with more than 60 points / the total number of Qusheng. It should be noted that the score threshold (such as 60) can be set according to the actual application situation, and the embodiment of the present application does not limit this.

[0081] In some specific embodiments, the user evaluation syllable data in the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rules to obtain the syllable accuracy rate corresponding to the user reading audio data, which may include: classifying the user evaluation syllables to obtain several user evaluation syllable sets; counting the number of target user evaluation syllables corresponding to each user evaluation syllable set; and calculating the syllable accuracy rate corresponding to the user reading audio data based on the target number of user evaluation syllables corresponding to each user evaluation syllable set and the user evaluation syllable score.

[0082] Among them, the user evaluation syllable set includes an initial consonant set and a final consonant set. For the target user evaluation syllable number, it is the number of user evaluation syllables that meet the target score threshold selected from the user evaluation syllable set. Exemplarily, assuming that the user evaluation syllable set is an initial consonant set, initial consonants with a score greater than or equal to 60 can be screened out from the initial consonant set, and finally the number of initial consonants with a score greater than or equal to 60 is counted as the target user evaluation initial consonant number, which is used to calculate the initial consonant accuracy rate.

[0083] Among them, the syllable accuracy corresponding to the audio data read aloud by the user includes the accuracy of initial consonants and the accuracy of final consonants, and the calculation formulas of the accuracy of initial consonants and final consonants are: initial consonant accuracy = the number of initial consonants greater than 60 points / the total number of initial consonants, and the final consonant accuracy = the number of final consonants greater than 60 points / the total number of final consonants. It should be noted that the score threshold (such as 60) can be set according to the actual application situation, and the embodiment of the present application does not limit this.

[0084] In some specific embodiments, the user evaluation character pronunciation data in the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rules to obtain a statistical set of weak Chinese characters corresponding to the user reading audio data, which may include: performing statistical analysis on the character pronunciation scores in the user evaluation character pronunciation data according to a preset character pronunciation threshold, and calculating the statistical set of weak Chinese characters corresponding to the user reading audio data.

[0085] The preset character pronunciation threshold is a score threshold for screening weak Chinese characters. It can be set according to actual application conditions, and the embodiment of the present application does not limit this.

[0086] Among them, the weak Chinese character statistical set refers to the set of Chinese characters that the system identifies after analyzing the user's reading data, which are inaccurately pronounced or often wrong by the user, and can help the user to practice the difficult-to-pronounce Chinese characters in a targeted manner, thereby improving the overall reading level. The calculation formula of the weak Chinese character statistical set is: weak Chinese character statistical set = the number of Chinese characters with a pronunciation score of less than 60 points. It should be noted that the score threshold (such as 60) can be set according to the actual application situation, and the embodiment of the present application does not limit this.

[0087] Steps S101 to S103 shown in the embodiment of the present application are obtained by obtaining user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data; the user reading data is input into the reading evaluation model to obtain user reading evaluation data; the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule, a user reading evaluation report is generated, and the user reading evaluation report is displayed through a visual interface. The embodiment of the present application can quickly and accurately analyze the overall reading pronunciation of the subject by designing an auxiliary scoring rule for reading pronunciation. At the same time, the use of a unified reading pronunciation scoring rule ensures the consistency and fairness of the scoring, so that the user's reading at different times or different occasions can be objectively evaluated. The reading pronunciation scoring rule can also help the system more accurately identify the user's pronunciation errors or deficiencies. In addition, by displaying the generated user reading evaluation report through a visual interface, the subject can be assisted to correct the reading pronunciation in a targeted manner, so that the audience can correctly understand the content of the reading.

[0088] In order to explain the principle of the technical solution of the present invention in detail, the overall process of the present invention is described below in combination with some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and cannot be regarded as a limitation of the present invention.

[0089] In order to make the reading guidance system more standardized, a multi-dimensional data analysis report on the user's reading pronunciation can be formed after reading aloud. The embodiment of the present application proposes an auxiliary scoring rule system for reading aloud pronunciation. After the reading evaluation, the subject's overall tone pronunciation, initial consonant pronunciation, final vowel pronunciation and character pronunciation can be analyzed. The accuracy of the tone pronunciation, the accuracy of the initial consonant pronunciation, the accuracy of the final vowel pronunciation and the weak Chinese character set in the user's pronunciation can be effectively analyzed. After the user finishes reading and obtains the user's reading evaluation report, the pronunciation can be corrected according to the user's reading evaluation report.

[0090] See also Figure 2 , Figure 2 : is a flow chart of a reading evaluation method provided in an embodiment of the present application; the general flow chart of a reading evaluation method provided in an embodiment of the present application is as follows Figure 2As shown, first, the user uses the reading evaluation application on the smart terminal to select the material that needs to be evaluated and read it aloud. After the user selects the material, the reading evaluation application will send the material text to the reading evaluation model to inform the reading evaluation model of the text content that needs to be evaluated; then, when the user starts to read aloud, the reading evaluation application collects the audio of the user's reading through the device microphone, collects the analog signal through the device microphone and inputs it to the audio motherboard, and then converts it into a digital signal after being converted by an analog-to-digital converter and inputs it to the device host. The reading evaluation application then obtains the digital information data on the device and sends it to the reading evaluation model, and the reading evaluation model performs the reading evaluation; then it determines whether to end the reading. The evaluation process of the reading evaluation model is carried out. If the evaluation process of the reading evaluation model is not ended, the step of collecting audio data will continue to be returned. If the evaluation process of the reading evaluation model is ended, the user reading evaluation data obtained by the evaluation is returned to the reading module of the current reading evaluation application through the reading evaluation model. After the reading module receives the user reading evaluation data, it uses the data loop to count the character attributes of the user evaluation material, such as tone (yinping, yangping, shangsheng, qusheng), initial consonant, final vowel, and weak characters (such as the pronunciation score of the character is less than 60), and finally analyzes the tone accuracy, syllable accuracy and weak character statistics. After the data loop is completed, a user reading evaluation report can be output.

[0091] In a specific implementation, the overall process of the reading evaluation method includes the following four steps (step 1 to step 3), specifically:

[0092] Step 1: First, the user uses the reading evaluation application on the smart terminal to select the material to be evaluated. After the user selects the material, the reading evaluation application will send the material text to the reading evaluation model to inform the reading evaluation model of the text content that needs to be evaluated.

[0093] Step 2. When the user starts reading aloud, the reading evaluation application collects the audio of the user's reading through the device microphone, collects the analog signal through the device microphone and inputs it into the audio mainboard, and then converts it into a digital signal through the analog-to-digital converter and inputs it into the device host. The reading evaluation application then obtains the digital information data on the device and sends it to the reading evaluation model, which then performs the reading evaluation.

[0094] Step 3, when the user finishes reading aloud, the reading evaluation model is notified that the user has finished reading aloud, and the reading evaluation model returns the user reading evaluation data obtained by the evaluation to the reading module of the current reading evaluation application. After the reading module receives the user reading evaluation data, it will start to parse the data report of the user's reading aloud, specifically using the data loop to count the character attributes of the user evaluation material, such as tone (yinping, yangping, shangsheng, qusheng), initial consonant, final vowel, and weak words (such as the pronunciation score of the word is less than 60), and finally analyze to obtain the tone accuracy, syllable accuracy and weak word statistics. Among them, the specific calculation process of the tone accuracy, syllable accuracy and weak word statistics is as follows:

[0095] (1) Please refer to Figure 3 , Figure 3 is a schematic diagram of a syllable data analysis process provided by an embodiment of the present application; Figure 3 As shown, the calculation process of the syllable accuracy rate corresponding to the user's reading audio data is as follows: first, based on the text cycle of the user evaluation material, the first component of the syllable of each character attribute ( Figure 3 The "beginning part" shown in the figure is an initial consonant or a final. If it is an initial consonant, it is put into the initial consonant set (the initial consonants in the set do not need to be removed); if it is not an initial consonant, it is put into the final consonant set (the final consonants in the set do not need to be removed); in addition, the second component of the syllable ( Figure 3 The finals information of the "back part" shown in the figure is put into the finals set; then, the initials set is circulated, and if the initial score is greater than 60 points, the number of initials with scores greater than 60 points is increased by 1, the total number of initials with scores greater than 60 is counted, and the total number of initials with scores greater than 60 is divided by the total number of initials set to calculate the accuracy of the initials; at the same time, the finals set is circulated, and if the final score is greater than 60 points, the number of finals with scores greater than 60 points is increased by 1, the total number of finals with scores greater than 60 is counted, and the total number of finals with scores greater than 60 is divided by the total number of finals set to calculate the accuracy of the finals.

[0096] (2) Please refer to Figure 4 , Figure 4 is a flow chart of a tone data analysis provided in an embodiment of the present application; Figure 4As shown, the calculation process of the tone accuracy corresponding to the audio data read aloud by the user is: based on the text loop of the user evaluation material, firstly, the data sets of the four tones of yinping, yangping, shangsheng and qusheng are respectively counted according to the character attributes (tones); then, the set data with tone scores greater than 60 points are filtered out from the data sets of the four tones of yinping, yangping, shangsheng and qusheng; then, based on the total number of data sets of the four tones of yinping, yangping, shangsheng and qusheng and the number sets of tones greater than 60 points, the number sets greater than 60 points are divided by the respective total number, and the tone accuracy of each of the four tones (yinping tone accuracy, yangping tone accuracy, shangsheng tone accuracy and qusheng tone accuracy) is calculated respectively.

[0097] (3) Please refer to Figure 5 , Figure 5 is a flow chart of a character pronunciation data analysis provided by an embodiment of the present application; Figure 5 As shown, the calculation process of the weak Chinese character statistical set corresponding to the user's reading audio data is: based on the text loop of the user evaluation material, the set of Chinese characters with pronunciation scores less than 60 points are counted according to the character attributes (character pronunciation scores), and the weak Chinese characters are arranged in ascending order according to the pronunciation scores and presented to the user.

[0098] Finally, the user's tone accuracy, initial consonant accuracy, final vowel accuracy, and the set of Chinese characters with weaker pronunciation in the material read aloud can be fed back through a visual interface.

[0099] It should be pointed out that this embodiment only briefly illustrates the general process of the reading evaluation method. The detailed description of each step can refer to the relevant content in the aforementioned embodiment and will not be repeated here. It can be understood that the present invention is not limited to this.

[0100] The embodiment of the present application obtains user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data; inputs the user reading data into the reading evaluation model to obtain user reading evaluation data; analyzes and processes the user reading evaluation data according to the reading pronunciation scoring rule, generates a user reading evaluation report, and displays the user reading evaluation report through a visual interface. The embodiment of the present application can quickly and accurately analyze the overall reading pronunciation of the subject by designing an auxiliary scoring rule for reading pronunciation. At the same time, the use of a unified reading pronunciation scoring rule ensures the consistency and fairness of the scoring, so that the user's reading at different times or different occasions can be objectively evaluated. The reading pronunciation scoring rule can also help the system more accurately identify the user's pronunciation errors or deficiencies. In addition, by displaying the generated user reading evaluation report through a visual interface, it can assist the subject to correct the reading pronunciation in a targeted manner, so that the audience can correctly understand the content of the reading.

[0101] See also Figure 6 The present application also provides a reading evaluation device 600, which can implement the above reading evaluation method. The device 600 includes the following modules:

[0102] The user reading data acquisition module 601 is used to acquire the user reading data; wherein the user reading data includes the user reading text data and the user reading audio data corresponding to the user reading text data;

[0103] A user reading data evaluation module 602, used for inputting the user reading data into a reading evaluation model to obtain user reading evaluation data;

[0104] The user reading evaluation data analysis module 603 is used to analyze and process the user reading evaluation data according to the reading pronunciation scoring rules, generate a user reading evaluation report, and display the user reading evaluation report through a visual interface.

[0105] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0106] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned reading evaluation method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0107] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0108] See also Figure 7 , Figure 7 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0109] The processor 701 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.

[0110] The memory 702 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 702 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 702, and the processor 701 calls and executes the reading evaluation method of the embodiment of this application;

[0111] Input / output interface 703, used to implement information input and output;

[0112] Communication interface 704, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WI FI, Bluetooth, etc.);

[0113] A bus 705 that transmits information between the various components of the device (e.g., the processor 701, the memory 702, the input / output interface 703, and the communication interface 704);

[0114] The processor 701 , the memory 702 , the input / output interface 703 and the communication interface 704 are connected to each other in communication within the device via a bus 705 .

[0115] The embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned reading evaluation method is implemented.

[0116] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0117] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0118] The reading evaluation method, reading evaluation device, electronic device and storage medium provided by the embodiment of the present application obtain user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data; input the user reading data into the reading evaluation model to obtain the user reading evaluation data; analyze and process the user reading evaluation data according to the reading pronunciation scoring rule, generate a user reading evaluation report, and display the user reading evaluation report through a visual interface. The embodiment of the present application can quickly and accurately analyze the overall reading pronunciation of the subject by designing an auxiliary scoring rule for reading pronunciation. At the same time, the use of a unified reading pronunciation scoring rule ensures the consistency and fairness of the scoring, so that the user's reading at different times or different occasions can be objectively evaluated. The reading pronunciation scoring rule can also help the system more accurately identify the user's pronunciation errors or deficiencies. In addition, by displaying the generated user reading evaluation report through a visual interface, it can assist the subject to correct the reading pronunciation in a targeted manner, so that the audience can correctly understand the content of the reading.

[0119] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0120] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0121] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0122] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0123] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0124] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0125] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0126] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0128] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0129] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A reading assessment method, characterized in that: The method comprises the following steps: Acquire user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data; Inputting the user reading data into a reading evaluation model to obtain user reading evaluation data; The user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rules to generate a user reading evaluation report, and the user reading evaluation report is displayed through a visual interface.

2. The method according to claim 1, characterized in that The step of inputting the user reading data into a reading evaluation model to obtain the user reading evaluation data comprises: Inputting the user's reading data into the reading evaluation model; The reading evaluation model analyzes and processes the user's reading audio data according to the user's reading text data and preset model evaluation rules to obtain the user's reading evaluation data.

3. The method according to claim 1, characterized in that The user reading evaluation data includes user evaluation tone data, user evaluation syllable data and user evaluation word pronunciation data, and the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule to generate a user reading evaluation report, and the user reading evaluation report is displayed through a visual interface, including: Analyzing and processing the user evaluation tone data in the user reading evaluation data according to the reading pronunciation scoring rule to obtain the tone accuracy rate corresponding to the user reading audio data; Analyzing and processing the user evaluation syllable data in the user reading evaluation data according to the reading pronunciation scoring rule to obtain the syllable accuracy rate corresponding to the user reading audio data; Analyze and process the user evaluation character pronunciation data in the user reading evaluation data according to the reading pronunciation scoring rule to obtain a weak Chinese character statistical set corresponding to the user reading audio data; Generating the user reading evaluation report based on the tone accuracy rate, the syllable accuracy rate and the weak Chinese character statistical set; The user reading evaluation report is displayed through a visual interface.

4. The method according to claim 3, characterized in that The user evaluation tone data includes user evaluation tone and user evaluation tone score, and the user evaluation tone data in the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule to obtain the tone accuracy rate corresponding to the user reading audio data, including: Classifying the user evaluation tones to obtain a plurality of user evaluation tone sets; Counting the number of target user evaluation tones corresponding to each of the user evaluation tone sets; The tone accuracy rate corresponding to the user-read audio data is calculated based on the number of target user-evaluated tones and the user-evaluated tone scores corresponding to each user-evaluated tone set.

5. The method according to claim 4, characterized in that The step of calculating the tone accuracy rate corresponding to the user-read audio data according to the number of target user-evaluated tones and the user-evaluated tone scores corresponding to each user-evaluated tone set includes: Calculating the target set tone accuracy rate corresponding to each of the user evaluation tone sets according to the number of the target user evaluation tone sets corresponding to each of the user evaluation tone sets and the user evaluation tone scores; The target set tone accuracy corresponding to each of the user evaluation tone sets is used as the tone accuracy corresponding to the user reading audio data.

6. The method according to claim 3, characterized in that: The user evaluation syllable data includes user evaluation syllables and user evaluation syllable scores, and the user evaluation syllable data in the user reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule to obtain the syllable accuracy rate corresponding to the user reading audio data, including: Classifying the user evaluation syllables to obtain a plurality of user evaluation syllable sets; Counting the number of target user evaluation syllables corresponding to each of the user evaluation syllable sets; The syllable accuracy rate corresponding to the user-reading audio data is calculated based on the target user-evaluated syllable quantity and the user-evaluated syllable score corresponding to each user-evaluated syllable set.

7. The method according to claim 3, characterized in that The user-evaluated character pronunciation data includes a character pronunciation score, and the user-evaluated character pronunciation data in the user-reading evaluation data is analyzed and processed according to the reading pronunciation scoring rule to obtain a weak Chinese character statistical set corresponding to the user-reading audio data, including: The character pronunciation scores in the user-evaluated character pronunciation data are statistically analyzed according to a preset character pronunciation threshold, and the weak Chinese character statistical set corresponding to the user's reading audio data is calculated.

8. A reading evaluation device, characterized in that: The device comprises the following modules: A user reading data acquisition module, used to acquire user reading data; wherein the user reading data includes user reading text data and user reading audio data corresponding to the user reading text data; A user reading data evaluation module, used for inputting the user reading data into a reading evaluation model to obtain user reading evaluation data; The user reading evaluation data analysis module is used to analyze and process the user reading evaluation data according to the reading pronunciation scoring rules, generate a user reading evaluation report, and display the user reading evaluation report through a visual interface.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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