Personalized communication scheme generation method and device based on personality self-adaption

Abstract

The invention discloses a personality self-adaption-based personalized communication scheme generation method and device, and the method comprises the steps: receiving a communication scene inputted by a user, and extracting the personality features of the user and the personality features of an interaction object; according to the personality characteristics of the user and the personality characteristics of the interaction object, a behavior disorder diagnosis report is generated in combination with a personality disorder rule base; generating a scene simulation interaction task according to the behavior disorder diagnosis report, and sending the scene simulation interaction task to the user for interaction; collecting interaction data of finishing the scene simulation interaction task by the user, and comparing the interaction data with risk points in the behavior disorder diagnosis report to obtain a comparison result; and an intervention instruction is generated according to a comparison result, and the non-adaptive behavior or psychological state glide of the user is intervened and corrected in real time according to the intervention instruction, so that a final communication scheme is generated, and the behavior change efficiency and continuous motivation of the user in multiple fields such as interpersonal communication, sales, fitness training, learning and growth and the like are improved.

Description

Technical Field

[0001] This application relates to the field of human-computer interaction technology, specifically to a method and apparatus for generating personalized communication schemes based on personality adaptation. Background Technology

[0002] With the rapid development of artificial intelligence and human-computer interaction technologies, various intelligent coaching systems (such as online learning platforms, sales and fitness guidance apps, and communication training tools) have been widely applied in skills training, habit formation, and behavior improvement. These systems typically provide users with instruction, feedback, and motivation based on pre-set course content, standardized training processes, or general behavioral models. However, existing systems still have significant limitations in achieving personalized and in-depth behavioral intervention, mainly in the following aspects:

[0003] First, existing systems mostly adopt a "one-size-fits-all" approach to content delivery and training, lacking in-depth identification and modeling of individual user differences, especially personality traits, psychological motivations, and behavioral patterns. Most systems only provide simple feedback based on surface-level behavioral data, failing to address the underlying psychological factors influencing behavior (such as core desires, emotional response patterns, and decision-making preferences). This results in a disconnect between training content and the user's true psychological state, making it difficult to achieve an effective transition from "knowing" to "doing."

[0004] Secondly, existing technologies generally suffer from the problem of "separation of knowledge and contextual application." Systems often focus on knowledge transmission or skill demonstration, but lack highly realistic scenario simulation and real-time behavioral guidance mechanisms. When users enter real-world scenarios after theoretical learning, they often fail to effectively apply what they have learned due to tension, habitual reactions, or psychological barriers. The system, however, cannot provide timely and accurate psychological and behavioral support at this critical juncture, thus affecting the transformation and consolidation of training results.

[0005] Furthermore, the incentive and feedback mechanisms of existing systems mostly remain superficial, such as points rewards, achievement badges, and generic encouraging statements, failing to connect with users' deeper psychological motivations (such as their needs for security, control, and recognition). This external incentive approach has a short-lived effect and is unlikely to stimulate users' sustained intrinsic motivation, especially when users encounter setbacks, reach plateaus, or face psychological resistance; in these cases, the system's support is very limited.

[0006] In terms of personality modeling and multimodal data analysis, although some studies have attempted to infer user traits through questionnaires or simple interaction data, their modeling dimensions are limited, data sources are restricted, and they fail to dynamically link user personality traits with specific behavioral barriers. Furthermore, existing systems often neglect the modeling of traits of "others" in the interaction (e.g., communication partners, task environment), leading to significant deviations between training scenarios and real-world situations, thus reducing the relevance and transferability of training.

[0007] In summary, current coaching apps, online courses, and traditional consulting commonly suffer from problems such as "disconnect between knowledge and application," "uniformity," and "ineffective motivation." The theoretical knowledge and methods learned by users often fail to be effectively applied in real-world situations due to their inherent personality patterns (internal behavioral response stereotypes), resulting in poor learning outcomes and lack of sustained action. Summary of the Invention

[0008] To address this issue, this application provides a method and apparatus for generating personalized communication solutions based on personality adaptation, in order to solve the problems of poor learning effectiveness and action persistence in existing technologies.

[0009] To achieve the above objectives, this application provides the following technical solution:

[0010] Firstly, a method for generating personalized communication solutions based on personality adaptation includes:

[0011] Step 1: Receive user input regarding the communication scenario;

[0012] Step 2: Extract user personality traits and interaction object personality traits from the communication scenario based on the pre-constructed two-way personality model;

[0013] Step 3: Generate a behavioral disorder diagnosis report based on the user's personality traits and the personality traits of the interactive object, combined with a pre-built personality disorder rule base;

[0014] Step 4: Generate a scenario simulation interactive task based on the behavioral disorder diagnosis report and send it to the user for interaction;

[0015] Step 5: Collect interaction data of the user completing the scenario simulation interaction task through voice, text or body movements, and compare the interaction data with the risk points in the behavioral disorder diagnosis report to obtain the comparison results;

[0016] Step 6: Generate intervention instructions based on the comparison results, and intervene and correct the user's maladaptive behaviors or decline in psychological state in real time according to the intervention instructions, thereby generating the final communication plan.

[0017] Preferably, the method further includes retrieving and recommending the most relevant strategy entries to the user from a pre-built strategy database based on the behavioral disorder diagnosis report.

[0018] Preferably, it also includes: recording user behavior data from each interaction, the number of times obstacles were overcome, and the final task success rate, and constructing a dynamic evolution model about the user's specific abilities; the dynamic evolution model is used to quantitatively evaluate the user's improvement at a certain behavioral obstacle, and autonomously plan and recommend the next task sequence based on the improvement.

[0019] Preferably, in step 2, the user's personality traits can also be obtained through standardized psychological scales or user historical interaction behavior data.

[0020] Preferably, in step 3, the behavioral disorder diagnostic report includes: the user's core psychological desires, deep fears, and the resulting maladaptive behaviors under the specified target task.

[0021] Preferably, in step 5, when comparing the interaction data with the risk points in the behavioral disorder diagnosis report, a multi-dimensional, continuous, and probabilistic comparison is performed.

[0022] Preferably, in step 6, the intervention instruction is a personalized message that directly addresses the user's core desires or deep-seated fears.

[0023] Secondly, a personalized communication solution generation device based on personality adaptation includes:

[0024] The communication scenario receiving module is used to receive communication scenarios input by the user.

[0025] The personality feature extraction module is used to extract user personality features and interaction object personality features from the communication scenario based on a pre-built two-way personality model.

[0026] The behavioral disorder diagnosis report generation module is used to generate a behavioral disorder diagnosis report based on the user's personality characteristics and the personality characteristics of the interactive object, and in combination with a pre-built personality disorder rule base.

[0027] The scenario simulation interaction task generation module is used to generate scenario simulation interaction tasks based on the behavioral disorder diagnosis report and send them to the user for interaction;

[0028] The risk comparison module is used to collect interaction data of users completing the scenario simulation interaction task through voice, text or body movements, and compare the interaction data with the risk points in the behavioral disorder diagnosis report to obtain the comparison results;

[0029] The communication plan generation module is used to generate intervention instructions based on the comparison results, and to intervene and correct the user's maladaptive behavior or decline in psychological state in real time based on the intervention instructions, thereby generating the final communication plan.

[0030] Thirdly, a computer device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method for generating personalized communication schemes based on personality adaptation.

[0031] Fourthly, a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for generating a personalized communication scheme based on personality adaptation.

[0032] Compared with the prior art, this application has at least the following beneficial effects:

[0033] Based on further analysis and research of existing technical problems, this application provides a personalized communication solution generation method based on personality adaptation. It receives communication scenarios input by users and extracts user and interaction object personality characteristics from these scenarios using a two-way personality model. Based on these characteristics and combined with a personality disorder rule base, a behavioral disorder diagnostic report is generated. A scenario-based interactive task is generated from the diagnostic report and sent to the user for interaction. Interaction data from the completed scenario-based interactive task is collected and compared with risk points in the behavioral disorder diagnostic report to obtain comparison results. Intervention instructions are generated based on these results, and real-time intervention and correction are implemented to address the user's maladaptive behaviors or declining psychological state, thus generating the final communication solution. This application, through the deep integration of personality psychological analysis, multimodal behavior recognition, scenario-based simulation, and real-time psychological intervention, truly achieves a shift from a "one-size-fits-all" approach to a "personalized approach," and from "knowledge transfer" to "behavioral internalization," thereby improving the effectiveness and sustained motivation of users in behavioral change across multiple fields such as interpersonal communication, sales, fitness training, and learning and growth. Attached Figure Description

[0034] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0035] Figure 1 A basic flowchart of the personalized communication solution generation method based on personality adaptation provided in Embodiment 1 of this application;

[0036] Figure 2 A flowchart illustrating the judgment process for the personalized communication solution generation method based on personality adaptation provided in Embodiment 1 of this application;

[0037] Figure 3 A flowchart for generating a behavioral disorder diagnostic report provided in Embodiment 1 of this application;

[0038] Figure 4 This is a flowchart of a scenario simulation interactive task provided in Embodiment 1 of this application;

[0039] Figure 5 This is a flowchart of the actual comparison process provided in Embodiment 1 of this application;

[0040] Figure 6 A flowchart for generating a case obstacle diagnosis report provided in Embodiment 1 of this application;

[0041] Figure 7 This is a flowchart of feature vectorization for a case obstacle diagnosis report provided in Embodiment 1 of this application;

[0042] Figure 8 This is a flowchart of the training for predicting and responding to the other party's reaction, provided in Embodiment 1 of this application.

[0043] Figure 9 This is a flowchart of the case training loop provided in Embodiment 1 of this application;

[0044] Figure 10 This is a flowchart illustrating the interactive process of an example from Embodiment 1 of this application.

[0045] Figure 11 The complete flowchart of the case provided in Embodiment 1 of this application. Detailed Implementation

[0046] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0047] In the description of this application: unless otherwise stated, "a plurality of" means two or more. The terms "first," "second," "third," etc., in this application are intended to distinguish the objects referred to and do not have any special meaning in terms of technical connotation (e.g., they should not be construed as an emphasis on importance or order). Expressions such as "including," "comprising," and "having" also mean "not limited to" (certain units, components, materials, steps, etc.).

[0048] The terms used in this application, such as "upper," "lower," "left," "right," and "middle," are generally used to indicate the general relative positional relationship for the purpose of intuitive understanding by referring to the accompanying drawings, and are not absolute limitations on the positional relationship in the actual product.

[0049] Example 1

[0050] This embodiment provides a personalized communication solution generation method based on personality adaptation. This method uses multimodal data analysis, personality modeling, and scenario simulation to provide personalized training for users' behavioral abilities (including but not limited to interpersonal communication, sales, fitness training, knowledge learning, etc.), thereby generating personalized communication solutions for each user and improving the effectiveness and sustained motivation of users in behavioral changes in multiple fields such as interpersonal communication, sales, fitness training, and learning and growth.

[0051] Please see Figure 1 and Figure 2 This embodiment provides a method for generating personalized communication solutions based on personality adaptation, including:

[0052] S1: Communication scenario involving receiving user input;

[0053] Specifically, the communication scenarios input by users include, but are not limited to, interpersonal communication, sales, fitness training, and knowledge learning.

[0054] S2: Extract user personality traits and interaction object personality traits from the communication scenario based on a pre-built two-way personality model;

[0055] Specifically, this embodiment will pre-construct a personality characteristic data model (i.e., a two-way personality model) of "our side" (i.e., the system user) and "the other side" (the communication object or task target), and deduce the behavioral obstacles (i.e., bottlenecks) that users may encounter when achieving specific goals based on the logic of the two-way personality model.

[0056] In this step, the "our" personality trait data model uses multimodal perception data and AI algorithms to quantitatively assess dimensions such as the system user's personality traits (e.g., conscientiousness, openness, neuroticism), communication style, decision-making preferences, and emotional sensitivity, thereby generating our personality traits (i.e., user personality traits). Alternatively, user personality traits can be obtained through standardized psychological scales and user historical interaction behavior data (e.g., APP usage habits, communication records). Preferably, user personality traits can be represented using vectors or other methods.

[0057] In interpersonal communication scenarios, the "other party's" personality trait data model is primarily implemented technically as follows: With authorization, the system collects text, voice, and video data of the "other party" during communication through a multimodal perception unit. A deep learning model is then used to extract language style, acoustic features, facial expressions, and body language characteristics to infer their personality traits (i.e., the personality traits of the interacting party). A supplementary implementation allows users to manually input and label the "other party's" personality traits using a preset tagging system to calibrate the AI's inference results. Preferably, the personality traits of the interacting party can also be represented using vectors or other methods.

[0058] It should be noted that in this embodiment, the personality characteristics of the interactive object can be directly input, that is, the known personality characteristics of the other party can be directly input. For example, the personality characteristics of the other party can be measured by scales or other means, or the characteristics can be inferred by the user's self-description of the other party's behavior.

[0059] S3: Generate a behavioral disorder diagnosis report based on the user's personality traits and the personality traits of the person interacting with the user, and in conjunction with a pre-built rule base for personality disorders;

[0060] Specifically, this embodiment incorporates a computational engine that matches the personality traits of "our side" with those of "the other side" (or the target), refers to a predefined "personality disorder" rule base (e.g., a highly neurotic personality's obstacle when encountering setbacks is "a tendency to give up"), and outputs a structured "behavioral disorder diagnostic report," such as... Figure 3 As shown in the report, this behavioral disorder diagnostic report clearly identifies the user's core psychological desires, deep-seated fears, and the resulting maladaptive behaviors under the specified target task.

[0061] S4: Generate a scenario simulation interactive task based on the behavioral disorder diagnosis report and send it to the user for interaction;

[0062] Specifically, this step, based on the behavioral disorder diagnostic report, generates an interactive script (communication scenario) containing roles, goals, and initial dialogue, or a sequential, dynamically adjusted task list (sales / fitness / learning scenario). In other words, this step generates scenario-based interactive tasks based on the behavioral disorder diagnostic report. Users interact with the system in real time through voice, text, or body language to complete the scenario-based interactive task, such as... Figure 4 As shown.

[0063] It should be noted that in this embodiment, the obstacle diagnosis report is converted into a computable feature vector library before the simulation training begins.

[0064] S5: Collect interaction data of users completing scenario simulation interaction tasks through voice, text or body movements, and compare the interaction data with the risk points in the behavioral disorder diagnosis report to obtain the comparison results;

[0065] Specifically, while users complete scenario simulation interaction tasks, multimodal perception synchronously collects users' interaction data, and compares the collected user interaction data with the risk points in their "behavioral disorder diagnosis report" to obtain the comparison results.

[0066] It should be noted that in this embodiment, during the actual comparison, it is not necessarily necessary to compare all the information; it may only be a single mode, such as comparing only the language mode. Figure 5 As shown.

[0067] S6: Generate intervention instructions based on the comparison results, and intervene and correct the user's maladaptive behavior or decline in psychological state in real time according to the intervention instructions, thereby generating the final communication plan.

[0068] Specifically, this step will generate intervention instructions based on the comparison results. These intervention instructions are not simple lectures, but personalized information that directly addresses the core desires or deep-seated fears of the individual.

[0069] In other words, once this step detects a match or predicts a high risk, it will immediately generate and push a precise behavioral / psychological intervention instruction. This intervention instruction essentially initiates a multi-round dialogue with the user, prompting them to think critically through words that resonate with their feelings, and using conversational coaching technology to help them overcome obstacles. You can think of it as an AI coach training the user; the intervention instruction is essentially giving the AI ​​coach guidance on how to communicate with the user.

[0070] This step is essentially a dynamic pattern matching method, which compares the user's real-time behavioral data stream with a pre-diagnosed mental disorder feature database in a multi-dimensional, continuous, and probabilistic manner, thereby achieving accurate identification at the moment the disorder is triggered.

[0071] In this embodiment, steps S4 to S6 provide the user with a simulated interactive environment (interpersonal communication) / personalized task guidance (sales / fitness / learning, etc.) that is highly consistent with the environmental model, for practicing or executing specific scenarios, and in the process, real-time intervention and correction are performed on the user's maladaptive behavior or decline in psychological state.

[0072] This embodiment provides a personalized communication solution generation method based on personality adaptation, which also includes strategy generation and capability evolution. Strategy generation and capability evolution provide users with an executable strategy library and dynamically update their capability profile based on their training / execution records, intelligently planning subsequent tasks. Specifically, it includes:

[0073] Strategy Database Construction: This embodiment also includes a structured strategy database, which stores communication strategies, motivational phrases, task design methods, etc., corresponding to different combinations of personality traits and different obstacles;

[0074] Strategy Recommendation Engine: Based on the behavioral disorder diagnosis report, this engine retrieves and recommends the most relevant strategy items to the user from the strategy database;

[0075] Capability Evolution Modeling: This embodiment records user behavior data from each interaction, the number of times obstacles are overcome, and the final task success rate. The core invention of capability evolution is to construct a dynamic evolution model of a user's specific capabilities using this historical data. This dynamic evolution model can quantitatively assess the degree of improvement a user makes at a particular behavioral obstacle and, based on this, autonomously plan and recommend the next task sequence, thereby achieving a personalized, spiraling, and progressive capability development loop.

[0076] The personalized communication solution generation method based on personality adaptation provided in this embodiment is actually a self-training method to help users identify and overcome subconscious communication barriers. This method uses AI dialogue to deeply explore the user's true "blockages" (psychological obstacles) and helps users complete psychological rehearsals before real communication through scenario simulation training, achieving a transformation from "having concerns" to "being willing".

[0077] The method provided in this embodiment will be further illustrated below with specific examples:

[0078] Case Study: Legacy Problem Barriers

[0079] Scene input (e.g.) Figure 6 , Figure 7 (As shown):

[0080] User: "I'm going to talk to Mr. Li about a new project collaboration tomorrow, but the project I was in charge of last time has been delayed."

[0081] Our characteristics: High conscientiousness, moderate neuroticism, avoidant attachment;

[0082] Other characteristics: results-oriented, direct communication style.

[0083] AI-guided dialogue example (e.g.) Figure 8 , Figure 9 , Figure 10 and Figure 11 (as shown)

[0084] AI: "I noticed you mentioned the project delay last time. How do you feel about that now?"

[0085] User: "I feel a little guilty, and I'm worried that Mr. Li will still remember this."

[0086] AI: "If Mr. Li really brings this up, what are you most worried about?"

[0087] User: "I'm worried that he'll think I'm unreliable and won't want to cooperate."

[0088] AI: "Behind this worry, isn't there a part of it that you yourself feel 'I didn't do a good job'?"

[0089] User: "Indeed...I've never formally discussed the reasons for the delay with him."

[0090] AI: "This is your core obstacle—unresolved guilt. We need to help you untangle this knot in your heart first."

[0091] This embodiment provides a personalized communication solution generation method based on personality adaptation. It accurately locates the user's core behavioral obstacles (blockages) in specific scenarios by using the personality characteristic data of the user and the person interacting with them. These blockages are rooted in the user's deep-seated personality psychology (core desires and deep fears). Through AI-driven simulation exercises or task guidance, it applies personalized, psychologically-focused real-time feedback and incentives to help users overcome internal resistance, correct behavioral patterns, and ultimately achieve substantial improvement and internalization of abilities.

[0092] In summary, the personalized communication solution generation method based on personality adaptation provided in this embodiment has the following advantages:

[0093] 1. From "General" to "Individual": Completely break free from the limitations of standardized content and achieve "one-on-one" precision coaching based on the user's deep personality.

[0094] 2. From "Knowledge" to "Behavior": The core objective is to facilitate actual behavioral change, rather than simply imparting knowledge. By using simulation and real-time intervention, the barriers between "learning" and "application" are broken down.

[0095] 3. From "external incentives" to "internal motivation": Incentive and feedback mechanisms directly target users' core psychological motivations, generating stronger and more lasting behavioral drive.

[0096] 4. High scalability: Its underlying "personality-checkpoint-intervention" technical architecture is universal and can be quickly replicated and applied to multiple fields that require behavioral intervention, such as communication, sales, fitness, education, and career development, and has extremely high commercial value and market potential.

[0097] Example 2

[0098] This embodiment provides a personalized communication solution generation device based on personality adaptation, including:

[0099] The communication scenario receiving module is used to receive communication scenarios input by the user.

[0100] The personality feature extraction module is used to extract user personality features and interaction object personality features from the communication scenario based on a pre-built two-way personality model.

[0101] The behavioral disorder diagnosis report generation module is used to generate a behavioral disorder diagnosis report based on the user's personality characteristics and the personality characteristics of the interactive object, and in combination with a pre-built personality disorder rule base.

[0102] The scenario simulation interaction task generation module is used to generate scenario simulation interaction tasks based on the behavioral disorder diagnosis report and send them to the user for interaction;

[0103] The risk comparison module is used to collect interaction data of users completing the scenario simulation interaction task through voice, text or body movements, and compare the interaction data with the risk points in the behavioral disorder diagnosis report to obtain the comparison results;

[0104] The communication plan generation module is used to generate intervention instructions based on the comparison results, and to intervene and correct the user's maladaptive behavior or decline in psychological state in real time based on the intervention instructions, thereby generating the final communication plan.

[0105] For details on the specific implementation of each module in a personality-adaptive personalized communication scheme generation device, please refer to the above description of the limitations of a personality-adaptive personalized communication scheme generation method, which will not be repeated here.

[0106] Example 3

[0107] This embodiment provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the method for generating personalized communication schemes based on personality adaptation.

[0108] Example 4

[0109] This embodiment provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method for generating personalized communication schemes based on personality adaptation.

[0110] The technical features of the above embodiments can be combined in any way (as long as there is no contradiction in the combination of these technical features). For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described; these embodiments not explicitly written should also be considered to be within the scope of this specification.

Claims

1. A method for generating personalized communication solutions based on personality adaptation, characterized in that, include: Step 1: Receive user input regarding the communication scenario; Step 2: Extract user personality traits and interaction object personality traits from the communication scenario based on the pre-constructed two-way personality model; Step 3: Generate a behavioral disorder diagnosis report based on the user's personality traits and the personality traits of the interactive object, combined with a pre-built personality disorder rule base; Step 4: Generate a scenario simulation interactive task based on the behavioral disorder diagnosis report and send it to the user for interaction; Step 5: Collect interaction data of the user completing the scenario simulation interaction task through voice, text or body movements, and compare the interaction data with the risk points in the behavioral disorder diagnosis report to obtain the comparison results; Step 6: Generate intervention instructions based on the comparison results, and intervene and correct the user's maladaptive behaviors or decline in psychological state in real time according to the intervention instructions, thereby generating the final communication plan.

2. The method for generating personalized communication solutions based on personality adaptation according to claim 1, characterized in that, Also includes: Based on the behavioral disorder diagnosis report, the most relevant strategy entries are retrieved from a pre-built strategy database and recommended to the user.

3. The method for generating personalized communication solutions based on personality adaptation according to claim 1, characterized in that, Also includes: Record user behavior data for each interaction, number of times obstacles are overcome, and final task success rate, and construct a dynamic evolution model for specific user abilities; the dynamic evolution model is used to quantitatively evaluate the degree of improvement of the user at a certain behavioral obstacle, and autonomously plan and recommend the next task sequence based on the degree of improvement.

4. The method for generating personalized communication solutions based on personality adaptation according to claim 1, characterized in that, In step 2, the user's personality traits can also be obtained through standardized psychological scales or user historical interaction behavior data.

5. The method for generating personalized communication solutions based on personality adaptation according to claim 1, characterized in that, In step 3, the behavioral disorder diagnostic report includes: the user's core psychological desires, deep fears, and the resulting maladaptive behaviors under the specified target task.

6. The method for generating personalized communication solutions based on personality adaptation according to claim 1, characterized in that, In step 5, the comparison between the interactive data and the risk points in the behavioral disorder diagnosis report is performed in a multi-dimensional, continuous, and probabilistic manner.

7. The method for generating personalized communication solutions based on personality adaptation according to claim 1, characterized in that, In step 6, the intervention instruction is a personalized message that directly addresses the user's core desires or deep-seated fears.

8. A personalized communication solution generation device based on personality adaptation, characterized in that, include: The communication scenario receiving module is used to receive communication scenarios input by the user. The personality feature extraction module is used to extract user personality features and interaction object personality features from the communication scenario based on a pre-built two-way personality model. The behavioral disorder diagnosis report generation module is used to generate a behavioral disorder diagnosis report based on the user's personality characteristics and the personality characteristics of the interactive object, and in combination with a pre-built personality disorder rule base. The scenario simulation interaction task generation module is used to generate scenario simulation interaction tasks based on the behavioral disorder diagnosis report and send them to the user for interaction; The risk comparison module is used to collect interaction data of users completing the scenario simulation interaction task through voice, text or body movements, and compare the interaction data with the risk points in the behavioral disorder diagnosis report to obtain the comparison results; The communication plan generation module is used to generate intervention instructions based on the comparison results, and to intervene and correct the user's maladaptive behavior or decline in psychological state in real time based on the intervention instructions, thereby generating the final communication plan.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

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

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