Artificial intelligence-based character analysis method, device and system and storage medium

Abstract

The invention discloses a character analysis method based on artificial intelligence. The method comprises the following steps: obtaining user dialogue content; a plurality of artificial intelligence models are constructed, and the plurality of artificial intelligence models comprise a management model and a plurality of scoring models; dividing the character into a plurality of dimensions, and distributing one dimension for each scoring model; inputting the user dialogue content into each scoring model, scoring the user dialogue content by each scoring model according to the distributed dimension, and outputting scoring results of multiple dimensions; and inputting the scoring results of the multiple dimensions into the management model, processing the scoring results of the multiple dimensions through the management model, and outputting a multi-dimensional character scoring report. According to the method, the multiple character dimensions are analyzed through the multiple artificial intelligence scoring models, the scoring report is output through the artificial intelligence management model, and the multi-dimensional character analysis result of the user can be accurately obtained.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology for personality analysis, specifically to a personality analysis method, device, system, and storage medium based on artificial intelligence. Background Technology

[0002] The origins of personality analysis in intelligent voice dialogue technology can be traced back to early explorations of the correlation between voice and personality traits, such as from traditional concepts like "reading faces to understand people" to the pursuit of character analysis methods in literature. With the development of artificial intelligence, the use of machine learning algorithms to infer personality traits has yielded significant results. It can improve user experience by analyzing user personality to communicate in a more relevant way; it can also optimize business services, helping companies adjust marketing strategies and improve customer service scripts based on customer personality, thereby increasing customer satisfaction and loyalty. This provides strong support for the effective application of intelligent voice dialogue in various fields, promoting more natural and personalized human-computer interaction. This application aims to provide a technical solution that can accurately analyze personality through user dialogue content. Summary of the Invention

[0003] In view of the above-mentioned prior art, the purpose of this invention is to provide a personality analysis method, device, system and storage medium based on artificial intelligence.

[0004] To achieve the above-mentioned technical objectives, the present invention adopts the following technical solution:

[0005] This invention provides a personality analysis method based on artificial intelligence, comprising the following steps:

[0006] Obtain user conversation content;

[0007] Construct multiple artificial intelligence models, including one management model and multiple scoring models;

[0008] Personality is divided into multiple dimensions, and one dimension is assigned to each rating model.

[0009] The user's dialogue content is input into each scoring model, and each scoring model scores the user's dialogue content according to the assigned dimensions, outputting multi-dimensional scoring results.

[0010] The scoring results from multiple dimensions are input into the management model, which processes the scoring results from multiple dimensions and outputs a multi-dimensional personality scoring report.

[0011] Furthermore, the aforementioned AI-based personality analysis method, in the step of inputting user dialogue content into various scoring models, whereby each scoring model scores the user dialogue content according to its assigned dimensions and outputs multi-dimensional scoring results, specifically includes:

[0012] Input the user's dialogue content into each rating model;

[0013] In a single scoring model, the user dialogue content is identified through each scoring model, and the identified user dialogue content is divided into multiple word groups;

[0014] Detect the frequency of keywords appearing in each word tuple corresponding to the assigned dimension;

[0015] Based on the frequency of keywords corresponding to the assigned dimension in each word tuple of the detected user dialogue content, output the score result for a single dimension;

[0016] Multiple scoring models output scoring results across multiple dimensions.

[0017] Specifically, the AI-based personality analysis method, in the step of outputting a single-dimensional score based on the frequency of keywords corresponding to the assigned dimension in each word tuple of the detected user dialogue content, includes:

[0018] The word tuple has 100 tokens, and the score of a single dimension is the frequency of the keyword corresponding to the assigned dimension for every 100 tokens divided by 100.

[0019] Preferably, the AI-based personality analysis method further includes, before the steps of inputting user dialogue content into various rating models, each rating model scoring the user dialogue content according to its assigned dimensions, and outputting multi-dimensional rating results:

[0020] The scoring model and management model are pre-trained;

[0021] Fine-tune the pre-trained scoring and management models.

[0022] Furthermore, the aforementioned AI-based personality analysis method, in the steps of inputting user dialogue content into various scoring models, each scoring model scoring the user dialogue content according to its assigned dimensions and outputting multi-dimensional scoring results, and inputting the multi-dimensional scoring results into the management model, processing the multi-dimensional scoring results through the management model, and outputting a multi-dimensional personality scoring report, specifically includes:

[0023] The user's dialogue content is input into multiple trained and fine-tuned scoring models. Each scoring model scores the user's dialogue content according to the assigned dimensions and outputs the scoring results of multiple dimensions after training and fine-tuning.

[0024] The scoring results of multiple dimensions after training and fine-tuning are input into the management model. The management model processes the scoring results of multiple dimensions and outputs a multi-dimensional personality scoring report.

[0025] Furthermore, the AI-based personality analysis method, after inputting the training-fine-tuned multi-dimensional scoring results into the management model, processing the multi-dimensional scoring results through the management model, and outputting a multi-dimensional personality scoring report, further includes:

[0026] The multi-dimensional personality scoring report is transmitted to the reviewer.

[0027] After the reviewer approves or adjusts the report, a new multi-dimensional personality score report is generated.

[0028] Furthermore, the AI-based personality analysis method, after the step of generating a new multi-dimensional personality score report following the review and approval or adjustment at the review end, also includes:

[0029] The scoring model was fine-tuned by using the data from the new multidimensional personality scoring report as a new training set.

[0030] The present invention also provides a personality analysis device based on artificial intelligence, the device comprising:

[0031] The content acquisition module is used to acquire user conversation content;

[0032] The artificial intelligence module is used to build multiple artificial intelligence models, including a management model and multiple scoring models.

[0033] The assignment module is used to divide personality into multiple dimensions and assign one dimension to each rating model.

[0034] The scoring module is used to input user dialogue content into various scoring models. Each scoring model scores the user dialogue content according to the assigned dimensions and outputs multi-dimensional scoring results.

[0035] The reporting module is used to input the rating results of multiple dimensions into the management model, and the management model processes the rating results of multiple dimensions to output a multi-dimensional personality rating report.

[0036] The present invention also provides an artificial intelligence-based personality analysis system, the system comprising at least one processor; and,

[0037] A memory communicatively connected to the at least one processor; wherein,

[0038] The memory stores instructions that can be executed by the at least one processor, which enables the at least one processor to perform the artificial intelligence-based personality analysis method described above.

[0039] A non-volatile computer-readable storage medium storing computer-executable instructions, which, when executed by one or more processors, cause the one or more processors to perform the aforementioned artificial intelligence-based personality analysis method.

[0040] Compared to existing technologies, this invention provides an artificial intelligence-based personality analysis method, comprising the following steps: acquiring user dialogue content; constructing multiple artificial intelligence models, wherein the multiple artificial intelligence models include a management model and multiple scoring models; dividing personality into multiple dimensions and assigning one dimension to each scoring model; inputting user dialogue content into each scoring model, each scoring model scoring the user dialogue content according to its assigned dimension, and outputting multi-dimensional scoring results; inputting the multi-dimensional scoring results into the management model, processing the multi-dimensional scoring results through the management model, and outputting a multi-dimensional personality scoring report. This invention analyzes multiple personality dimensions through multiple artificial intelligence scoring models and outputs a scoring report through an artificial intelligence management model, enabling a relatively accurate multi-dimensional personality analysis of users. Attached Figure Description

[0041] Figure 1 A flowchart of the personality analysis method based on artificial intelligence provided by the present invention.

[0042] Figure 2 A schematic diagram of the functional modules of the AI-based personality analysis device provided by the present invention.

[0043] Figure 3 A schematic diagram of the hardware structure of the AI-based personality analysis system provided by this invention. Detailed Implementation

[0044] In view of the shortcomings of the prior art, the purpose of this invention is to provide a personality analysis method, application server, system and storage medium based on artificial intelligence.

[0045] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0046] This invention can be applied to computer devices, which can install one or more applications to process related data. The computer device can be a terminal or a server. The terminal can be an electronic device with communication capabilities, such as a smartphone, tablet, laptop, desktop computer, personal digital assistant, or wearable device. The computer device includes a processor, non-volatile storage medium, internal memory, and a network interface connected via a system bus. The non-volatile storage medium of the computer device can store an operating system and a computer-readable program. When executed, the computer-readable program causes the processor to perform an underwriting difficulty prediction method. The processor of the computer device provides computing and control capabilities to support the operation of the entire computer device. The internal memory can store a computer-readable program, which, when executed by the processor, causes the processor to perform an underwriting difficulty prediction method. The network interface of the computer device is used for network communication, such as sending assigned tasks.

[0047] like Figure 1 As shown, this invention provides a personality analysis method based on artificial intelligence, comprising the following steps:

[0048] S1. Obtain user conversation content;

[0049] S2. Construct multiple artificial intelligence models, including one management model and multiple scoring models;

[0050] S3. Divide personality into multiple dimensions and assign one dimension to each rating model;

[0051] S4. Input the user dialogue content into each scoring model. Each scoring model scores the user dialogue content according to the assigned dimensions and outputs the scoring results of multiple dimensions.

[0052] S5. Input the rating results of multiple dimensions into the management model, process the rating results of multiple dimensions through the management model, and output a multi-dimensional personality rating report.

[0053] In this invention, the user dialogue content can be in text mode directly, or it can be dialogue text converted through speech recognition.

[0054] In this invention, artificial intelligence models such as CHAT-GPT, BERT, DEEPSEEK, RoBERTa, and ERNIE can be used. For example, fine-tuning BERT and its variants for sentiment analysis tasks allows for the capture of features related to emotions and personality, such as vocabulary and expressions, from text through pre-training semantic representation capabilities, thereby determining the author's emotional state or potential personality traits. RoBERTa, an optimized version of BERT, improves training methods and data processing, and can also be used in text tasks related to personality / sentiment analysis, exhibiting better robustness and accuracy, and more precisely extracting relevant information from the semantic perspective of the text. ERNIE, a knowledge-enhanced semantic representation model launched by Baidu, not only understands the surface semantics of text but also incorporates knowledge information. It has a greater advantage in personality / sentiment analysis when analyzing text content containing rich knowledge and cultural background, such as analyzing character personalities and related emotional expressions in literary works.

[0055] The natural language processing capabilities of large artificial intelligence models are used to statistically analyze the part-of-speech distribution, keyword density, and sentiment score of dialogue content.

[0056] This invention can utilize Gardner's theory of multiple intelligences and Jung's theory of eight personality types as psychological mappings.

[0057] This invention acquires user dialogue content; sets up multiple artificial intelligence models, including a management model and multiple scoring models; divides personality into multiple dimensions, assigning one dimension to each scoring model; inputs the user dialogue content into the multiple scoring models, with each scoring model scoring the user dialogue content according to its assigned dimension, outputting multi-dimensional scoring results; inputs the multi-dimensional scoring results into the management model, which processes and summarizes the multi-dimensional scoring results, outputting a multi-dimensional personality scoring report. This invention analyzes multiple personality dimensions through multiple artificial intelligence scoring models and outputs a scoring report through an artificial intelligence management model, enabling a relatively accurate multi-dimensional personality analysis of users.

[0058] The rating model can score from eight dimensions: extroverted sensing, introverted sensing, extroverted thinking, introverted thinking, extroverted feeling, introverted feeling, extroverted intuitive, and introverted intuitive. For example, the dimensions and some corresponding keywords are shown in the table below:

[0059]

[0060]

[0061] Furthermore, the personality analysis method based on artificial intelligence provided by this invention, in step S4, which involves inputting user dialogue content into each rating model, with each rating model scoring the user dialogue content according to its assigned dimensions, and outputting multi-dimensional rating results, specifically includes:

[0062] Input the user's dialogue content into each rating model;

[0063] In a single scoring model, the user dialogue content is identified through each scoring model, and the identified user dialogue content is divided into multiple word groups;

[0064] Detect the frequency of keywords appearing in each word tuple corresponding to the assigned dimension;

[0065] Based on the frequency of keywords corresponding to the assigned dimension in each word tuple of the detected user dialogue content, output the score result for a single dimension;

[0066] Multiple scoring models output scoring results across multiple dimensions.

[0067] Specifically, the personality analysis method based on artificial intelligence provided by this invention includes the following steps in the process of outputting a score for a single dimension based on the frequency of keywords corresponding to the assigned dimension in each word tuple of the detected user dialogue content:

[0068] The word tuple has 100 tokens, and the score for each dimension is the frequency of the keyword corresponding to the assigned dimension for every 100 tokens divided by 100. See the table below:

[0069]

[0070] For example, if rating model 1 scores the "extroverted intuition" dimension, and this rating model determines that users mention the keyword "creativity" 37 out of every 100 tokens, and users mention the keyword "exploration" 23 out of every 100 tokens, then the dimension score for the "extroverted intuition" single model is: P1 = (37 + 23) / 100 = 0.6 points.

[0071] Preferably, the personality analysis method based on artificial intelligence provided by the present invention further includes, before step S4, inputting user dialogue content into each rating model, each rating model rating the user dialogue content according to the assigned dimensions, and outputting rating results for multiple dimensions:

[0072] The scoring model and management model are pre-trained;

[0073] Fine-tune the pre-trained scoring and management models.

[0074] This invention uses a large-scale corpus to pre-train multiple large models, enabling each model to possess basic language understanding and generation capabilities.

[0075] This invention trains and fine-tunes multiple fundamental artificial intelligence models using existing theories of personality types and multiple intelligences in psychology. It scores models based on the frequency of occurrence of representative words, short phrases, and long sentences for each dimension within each theory. Furthermore, it assigns scoring dimensions to each model and unifies the scoring criteria during training and fine-tuning.

[0076] This invention utilizes multiple personality dimension scoring models to simultaneously and distributedly compare the consistency and contradictions of multi-turn dialogue records. In this invention, consistency and contradictions are determined by the accuracy of keyword extraction from the user's dialogue content by multiple scoring models. In this embodiment, multiple scoring models score the user's dialogue content on the same dimension (multiple models extract keywords and score based on keyword frequency within the same dimension), outputting multiple scoring results. If the difference between the highest and lowest scores does not exceed a preset score (which can be 0.1 points), the results are considered consistent. Conversely, if the difference between the highest and lowest scores exceeds the preset score (which can be 0.1 points), a contradiction in keyword judgment exists within that dimension.

[0077] Furthermore, the personality analysis method based on artificial intelligence provided by this invention, in step S4, which involves inputting user dialogue content into various scoring models, with each scoring model scoring the user dialogue content according to its assigned dimensions, and outputting multi-dimensional scoring results, specifically includes:

[0078] The user's dialogue content is input into multiple trained and fine-tuned scoring models. Each scoring model scores the user's dialogue content according to the assigned dimensions and outputs the scoring results of multiple dimensions after training and fine-tuning.

[0079] In step S5, which involves inputting the rating results from multiple dimensions into the management model, processing the rating results from multiple dimensions through the management model, and outputting a multi-dimensional personality rating report, the specific steps include:

[0080] The scoring results of multiple dimensions after training and fine-tuning are input into the management model. The management model processes the scoring results of multiple dimensions and outputs a multi-dimensional personality scoring report.

[0081] This invention employs multiple trained and fine-tuned large-scale artificial intelligence models to analyze and understand user dialogue records, and scores personality and emotions in the dimensions calculated by their respective large-scale models through dimensional scoring.

[0082] This invention can use the highest-rated model recognized in the field of artificial intelligence for training and fine-tuning the personality and emotion capture analysis. The highest-rated model can be selected from the top-ranked AI models in recognized leaderboards, such as ChatBot Arena (lmarena.ai). The trained and fine-tuned unified scoring standard data is also used to train this model, and it is then used to review and comprehensively analyze other large models responsible for scoring each dimension of personality and emotion. Specifically, for example, if the scoring model scores 0.6 points for dimension one of a one-on-one user conversation, and the review model also scores the same user conversation for dimension one, and the review model's score is 0.69 points, the review model's score is compared with the score of the first scoring model. If the difference does not exceed a preset score, for example, if the preset score is 0.1 points, |0.69-0.60|=0.09<0.1, that is, the difference does not exceed the preset score (not exceeding 0.1 points), then the scoring model is deemed acceptable. The scoring result of Type 1 is accurate; conversely, if the difference exceeds the preset score, for example, if the preset score is 0.1, and the scoring model scores the one-to-one user dialogue content for Dimension 1 as 0.6, and the review model also scores the user dialogue content for Dimension 1, if the review model's score is 0.71, the review model's score is compared with the scoring result of Type 1. If |0.71-0.60|=0.11>0.1, meaning the difference exceeds the preset score (more than 0.1), then the scoring result of Type 1 is determined to be contradictory. In this case, the review model modifies and adjusts the preset keywords of the scoring model, and then generates a modification report and sends it to the review end.

[0083] The management model of this invention analyzes and summarizes users' multi-dimensional personality and emotion reports.

[0084] Furthermore, the AI-based personality analysis method provided by this invention, after the steps of inputting the training-fine-tuned multi-dimensional scoring results into the management model, and the management model processing and summarizing the multi-dimensional scoring results to output a multi-dimensional personality scoring report, further includes:

[0085] The multi-dimensional personality scoring report is transmitted to the reviewer.

[0086] After the reviewer approves or adjusts the report, a new multi-dimensional personality score report is generated.

[0087] Furthermore, the AI-based personality analysis method provided by this invention, after the step of generating a new multi-dimensional personality score report following the review and approval or adjustment at the review end, further includes:

[0088] The scoring model was fine-tuned by using the data from the new multidimensional personality scoring report as a new training set.

[0089] This invention allows for periodic manual evaluation of the accuracy of report results and scores across various dimensions through the review process, enabling periodic reinforcement training and fine-tuning. This strengthens the learning mechanism, continuously optimizing the analysis algorithm through actual user interaction.

[0090] The artificial intelligence model of this invention extracts and determines whether words in user dialogue content belong to the corresponding dimension. For example, if 50 out of every 100 tokens in the user dialogue content mention the word "transformation," the scoring model extracts and determines it as a keyword related to "change." Since "change" is a keyword in the "extroverted intuition" dimension, the score for that dimension will increase. Human reviewers examine this scoring process. If they believe that the word "transformation" better reflects a strong empathy for the desired transformation, then this keyword should be added to the "extroverted affective" dimension and excluded from the "extroverted intuition" dimension. This adjusted keyword is then used as new training data to train the larger model.

[0091] This invention utilizes advanced natural language processing technology to achieve a deep understanding of complex dialogue content, providing multi-dimensional personality assessments, including extraversion, openness, and emotional stability. It also continuously improves the accuracy of emotion and personality analysis through distributed training of artificial intelligence models. Furthermore, this invention can dynamically optimize interaction strategies based on users' immediate feedback and long-term behavioral patterns.

[0092] like Figure 2 As shown, the present invention provides a personality analysis device based on artificial intelligence, the device comprising:

[0093] Content acquisition module 11 is used to acquire user conversation content;

[0094] Artificial intelligence module 12 is used to build multiple artificial intelligence models, including a management model and multiple scoring models;

[0095] The assignment module 13 is used to divide personality into multiple dimensions and assign one dimension to each rating model.

[0096] The scoring module 14 is used to input user dialogue content into each scoring model. Each scoring model scores the user dialogue content according to the assigned dimensions and outputs multi-dimensional scoring results.

[0097] The reporting module 15 is used to input the rating results of multiple dimensions into the management model, process the rating results of multiple dimensions through the management model, and output a multi-dimensional personality rating report.

[0098] Furthermore, the device also includes:

[0099] The training module is used to train the scoring model and the management model.

[0100] The module referred to in this invention is a series of computer program instruction segments capable of performing specific functions. It is more suitable than a program for the execution process of personality analysis methods based on artificial intelligence. For specific implementation methods of each module, please refer to the corresponding method embodiments mentioned above, which will not be repeated here.

[0101] Another embodiment of the present invention also provides a personality analysis system based on artificial intelligence, such as... Figure 3 As shown, system 10 includes:

[0102] One or more processors 110 and memory 120, Figure 3 The following description uses a processor 110 as an example. The processor 110 and the memory 120 can be connected via a bus or other means. Figure 2 Taking the example of a connection between China and Israel via a bus.

[0103] Processor 110 is used to perform various control logics of system 10, and can be a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), microcontroller, ARM (Acorn RISC Machine) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components. Furthermore, processor 110 can also be any conventional processor, microprocessor, or state machine. Processor 110 can also be implemented as a combination of computing devices, such as a combination of DSP and microprocessor, multiple microprocessors, one or more microprocessors combined with DSP and / or any other such configuration.

[0104] The memory 120, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions corresponding to the artificial intelligence-based personality analysis method in the embodiments of the present invention. The processor 110 executes various functional applications and data processing of the system 10 by running the non-volatile software programs, instructions, and units stored in the memory 120, thereby implementing the artificial intelligence-based personality analysis method in the above method embodiments.

[0105] The memory 120 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created according to the use of the system 10. Furthermore, the memory 120 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 120 may optionally include memory remotely located relative to the processor 110, and these remote memories may be connected to the system 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0106] One or more units are stored in memory 120. When executed by one or more processors 110, they perform the water supply proportional valve fault detection method in any of the above method embodiments, for example, performing the above-described... Figure 1 The method steps S101 to S103 are described in the text.

[0107] This invention provides a non-volatile computer-readable storage medium storing computer-executable instructions that are executed by one or more processors, for example, to perform the operations described above. Figure 1 The method steps S101 to S103 are described in the text.

[0108] As examples, non-volatile storage media can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) as external cache memory. By way of illustration and not limitation, RAM can be obtained in many forms such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM). The memory components or memories disclosed in the operating environment described herein are intended to include one or more of these and / or any other suitable types of memory.

[0109] In summary, this invention utilizes advanced natural language processing technology to achieve a deep understanding of complex dialogue content, providing multi-dimensional personality assessments, including extraversion, openness, and emotional stability. Furthermore, it leverages the analytical capabilities of a distributed-trained artificial intelligence model to continuously improve the accuracy of emotion and personality analysis. Additionally, this invention can dynamically optimize interaction strategies based on users' immediate feedback and long-term behavioral patterns.

[0110] It should be noted that there is no necessary order between the above steps. Those skilled in the art will understand from the description of the embodiments of the present invention that the above steps may have different execution orders in different embodiments, that is, they may be executed in parallel or in turn, etc.

[0111] The contents already described in this specification and accompanying drawings include examples of methods, apparatuses, systems, and media capable of providing fault detection for water proportional valves. Of course, it is not possible to describe every conceivable combination of elements and / or methods for the purpose of describing the various features of this disclosure, but it will be appreciated that many other combinations and substitutions of the disclosed features are possible. Therefore, it will be apparent that various modifications can be made to this disclosure without departing from the scope or spirit of this disclosure. Furthermore, or in alternatives, other embodiments of this disclosure may become apparent from consideration of this specification and accompanying drawings and from practice of this disclosure as presented herein. It is intended that the examples presented in this specification and accompanying drawings be considered illustrative rather than restrictive in all respects. Although specific terminology is used herein, it is used in a general and descriptive sense and is not intended for limiting purposes.

Claims

1. A personality analysis method based on artificial intelligence, characterized in that, Includes the following steps: Obtain user conversation content; Construct multiple artificial intelligence models, including one management model and multiple scoring models; Personality is divided into multiple dimensions, and one dimension is assigned to each rating model. The user's dialogue content is input into each scoring model, and each scoring model scores the user's dialogue content according to the assigned dimensions, outputting multi-dimensional scoring results. The scoring results from multiple dimensions are input into the management model, which processes the scoring results from multiple dimensions and outputs a multi-dimensional personality scoring report.

2. The personality analysis method based on artificial intelligence according to claim 1, characterized in that, The process involves inputting user dialogue content into various scoring models, each scoring model rating the user dialogue content according to its assigned dimensions, and outputting multi-dimensional rating results, including: Input the user's dialogue content into each rating model; The user dialogue content is identified using each of the aforementioned scoring models, and the identified user dialogue content is divided into multiple word groups. Detect the frequency of keywords appearing in each word tuple corresponding to the assigned dimension; Based on the frequency of keywords corresponding to the assigned dimensions in the detected user dialogue content, output the score result for a single dimension; Multiple scoring models output scoring results across multiple dimensions.

3. The personality analysis method based on artificial intelligence according to claim 2, characterized in that, The step of outputting a single-dimensional score result based on the frequency of keywords corresponding to the assigned dimension in the detected user dialogue content includes: The word tuple has 100 tokens, and the score of a single dimension is the frequency of the keyword corresponding to the assigned dimension for every 100 tokens divided by 100.

4. The personality analysis method based on artificial intelligence according to claim 1, characterized in that, Before the step of inputting user dialogue content into each scoring model, where each scoring model scores the user dialogue content according to its assigned dimensions, and outputs multi-dimensional scoring results, the method further includes: The scoring model and management model are pre-trained; Fine-tune the pre-trained scoring and management models.

5. The personality analysis method based on artificial intelligence according to claim 4, characterized in that, The process of inputting user dialogue content into each scoring model, and each scoring model scoring the user dialogue content according to the assigned dimensions, includes: The user's dialogue content is input into multiple trained and fine-tuned scoring models. Each scoring model scores the user's dialogue content according to the assigned dimensions and outputs the scoring results of multiple dimensions after training and fine-tuning. The process involves inputting the rating results from multiple dimensions into the management model, processing the rating results from these dimensions through the management model, and outputting a multi-dimensional personality rating report, including: The scoring results of multiple dimensions after training and fine-tuning are input into the management model. The management model processes the scoring results of multiple dimensions and outputs a multi-dimensional personality scoring report.

6. The personality analysis method based on artificial intelligence according to claim 5, characterized in that, After inputting the training-fine-tuned rating results of multiple dimensions into the management model, processing the rating results of the multiple dimensions through the management model, and outputting a multi-dimensional personality rating report, the method further includes: The multi-dimensional personality scoring report is transmitted to the reviewer. After the reviewer approves or adjusts the report, a new multi-dimensional personality score report is generated.

7. The personality analysis method based on artificial intelligence according to claim 6, characterized in that, After the reviewer approves or adjusts the report, and a new multi-dimensional personality rating report is generated, the following steps are also included: The scoring model was fine-tuned by using the data from the new multidimensional personality scoring report as a new training set.

8. A personality analysis device based on artificial intelligence, characterized in that, The device includes: The content acquisition module is used to acquire user conversation content; The artificial intelligence module is used to build multiple artificial intelligence models, including a management model and multiple scoring models. The assignment module is used to divide personality into multiple dimensions and assign one dimension to each rating model. The scoring module is used to input user dialogue content into various scoring models. Each scoring model scores the user dialogue content according to the assigned dimensions and outputs multi-dimensional scoring results. The reporting module is used to input the rating results of multiple dimensions into the management model, and the management model processes the rating results of multiple dimensions to output a multi-dimensional personality rating report.

9. A personality analysis system based on artificial intelligence, characterized in that, The system includes at least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the artificial intelligence-based personality analysis method according to any one of claims 1-7.

10. A non-volatile computer-readable storage medium, characterized in that, The non-volatile computer-readable storage medium stores computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the artificial intelligence-based personality analysis method according to any one of claims 1-7.

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