Digital gift content generation and presentation method based on gift giving scene

Abstract

The invention discloses a gift giving scene-based digital gift content generation and presentation method. The method comprises the following steps of receiving a gift giving scene type and personalized content information input by a user; based on the scene type, a corresponding scene template is matched from a preset template library, and the scene template at least defines a visual style, a music style, a copywriting style and a content structure. According to the digital gift content generation and presentation method based on the gift giving scene provided by the invention, a user can automatically obtain high-quality gift content with emotional value only by inputting simple scene information; multi-modal content generation and binding are supported; the content can be dynamically updated or kept static, but the emotion layer can be updated along with time / behavior; the first-time touch ceremony feeling is supported, and the multi-time touch emotion is enhanced; nFC is used as an entity gift carrier to realize exclusive content access; and the long-term AI personalized recommendation capability is realized through user data and scene data precipitation.

Description

Technical Field

[0001] This invention relates to the field of digital content generation technology, and in particular to a method for generating and presenting digital gift content based on a gift-giving scenario. Background Technology

[0002] With the popularization of NFC tags, digital content generation, and AI technology, some souvenirs that can read music / text / web page content have emerged, but existing technologies have the following problems:

[0003] 1. Limited functionality and lack of emotional value:

[0004] Most existing NFC gifts only support opening a fixed URL directly, and cannot automatically generate matching content based on the gifting scenario and emotional needs.

[0005] 2. AI capabilities are too general and highly random:

[0006] Existing AI tools (such as image generation and video generation) require users to try repeatedly, and the generated results are uncontrollable, making them unsuitable for precise expression in gift-giving scenarios.

[0007] 3. Lack of scene generation capabilities:

[0008] Users have a variety of usage scenarios, such as expressing love, birthdays, coming-of-age ceremonies, friendships, and parent-child blessings. However, existing technologies cannot provide short videos, texts, and voice messages that are automatically generated based on scenario templates.

[0009] 4. Lack of content lifecycle management:

[0010] Gift content is usually fixed and cannot be updated, making it impossible to support multiple surprises for couples or fixed but time-sensitive content for milestones (coming-of-age ceremonies / birthdays).

[0011] 5. The user experience lacks a sense of ritual and emotional depth:

[0012] The existing solution simply opens the content without any emotional build-up or sense of ritual, and it also cannot automatically generate emotional prompts based on time or number of times the content has been opened.

[0013] Therefore, it is necessary to provide a scenario-driven, emotion-driven AI gift content system that can transform NFC physical gifts into digital carriers with emotional vitality, enhance the expressiveness and emotional value of gifts, and create experiential differentiation and technological barriers. Summary of the Invention

[0014] To address the aforementioned technical issues, this invention provides a digital gift system based on scenario-based templates, low-randomness AI generation, dynamic emotion enhancement, controllable content lifecycle, and NFC physical binding.

[0015] This invention provides a method for generating and presenting digital gift content based on gift-giving scenarios, comprising the following steps:

[0016] S1: Receives the gift-giving scenario type and personalized content information input by the user;

[0017] S2: Based on the scene type, match the corresponding scene template from the preset template library. The scene template defines at least a visual style, a music style, a copywriting style, and a content structure.

[0018] S3: Call the controllable multimodal generation engine to generate digital content that matches the scene based on the personalized content information and scene template. The generation engine has preset vertical generation capabilities, including character age evolution, occupational role projection and scene atmosphere enhancement.

[0019] S4: Call the emotional copy generation module, combine the scene sentence template with user input, and generate emotional copy that is appropriate for the scene;

[0020] S5: Determine the content binding strategy based on the gift content lifecycle type. Dynamic content types support multiple versions of content and automatically switch according to preset conditions, while node-type content types keep the content fixed but support the generation of dynamic emotion prompts.

[0021] S6: Bind the generated digital content, emotional copy, and lifecycle information as a content identifier and write it into the near-field communication (NFC) tag in the physical gift;

[0022] S7: When the recipient touches the NFC tag for the first time, a ritualistic transition animation is triggered and the digital content is displayed;

[0023] S8: When the recipient touches the NFC tag again, if it is dynamic content, the content version will be switched according to the rules; if it is node-type content, an emotion prompt will be generated to realize the emotion dynamics.

[0024] Preferably, the version switching of the dynamic content is automatically executed by the content lifecycle management module based on the date or the number of touches.

[0025] Preferably, when the node-type content is touched again, the emotion dynamic layer generation module generates an emotion prompt based on the time difference or the number of touches.

[0026] Preferably, the ritualistic transition animation is an envelope-opening animation with a duration of 1 to 1.5 seconds.

[0027] A digital gift content generation and presentation system based on gift-giving scenarios includes:

[0028] The scene template engine is used to select the corresponding scene template from the template library based on the scene type.

[0029] The controllable multimodal generation module is used to generate digital content based on user input and scene templates, and has the ability to generate age evolution, occupational projection and atmosphere enhancement.

[0030] The emotional copy generation module is used to generate emotional copy that matches the scene.

[0031] The content lifecycle management module is used to manage the lifecycle strategy of content, and supports multi-version switching of dynamic content and the generation of sentiment prompts for node content.

[0032] The emotion dynamic layer generation module is used to generate dynamic emotion prompts in node-type content displays;

[0033] The First Touch Ceremony Presentation module is used to trigger a ceremony animation and display content upon the first touch.

[0034] The data collection and preference learning module is used to record user behavior and preferences to optimize template selection and content recommendation.

[0035] The gift scenario AI Agent system is connected to the data acquisition and preference learning module. It is used to train based on the accumulated user data and scenario data to realize personalized content recommendation, generation strategy optimization and dynamic content planning. It includes a scenario-based content generation agent and a persona / zodiac attribute AI agent.

[0036] The NFC interaction module includes a writing end and a reading end. The writing end is used to write the content identifier generated in the cloud into the NFC tag. The reading end is used to read the content identifier in the NFC tag when touched and communicate with the cloud server to obtain the corresponding content, instructions or updates.

[0037] Preferably, the controllable multimodal generation module includes an age evolution generation submodule, used to generate age evolution images or videos based on portrait photos.

[0038] Preferably, the controllable multimodal generation module includes a future professional role generation submodule, used to generate a future image of a person wearing professional attire.

[0039] Preferably, the controllable multimodal generation module includes a scene atmosphere enhancement submodule, used to add visual lighting effects and music effects to the uploaded content.

[0040] Preferably, the emotional copywriting generation module generates at least one type of message or copywriting based on the scene sentence template, and supports dynamic copywriting generation based on time or number of touches.

[0041] Preferably, the data collection and preference learning module records user template selection, copywriting preferences, and opening behavior for personalized content recommendation and template strategy updates.

[0042] Compared with related technologies, the digital gift content generation and presentation method based on gift-giving scenarios provided by this invention has the following beneficial effects:

[0043] This invention provides a method for generating and presenting digital gift content based on gift-giving scenarios. Users only need to input simple scenario information to automatically obtain high-quality gift content with emotional value. It supports the generation and binding of multimodal content (images / videos / audio). The content can be dynamically updated or kept static, but the emotional layer can be updated with time / behavior. It supports the sense of ritual upon first touch and the enhancement of emotion upon repeated touches. It uses NFC as a physical gift carrier to achieve exclusive access to content. Through the accumulation of user data and scenario data, it achieves long-term AI personalized recommendation capabilities. Attached Figure Description

[0044] Figure 1 A schematic diagram of the digital gift content generation and presentation system based on gift-giving scenarios provided by the present invention;

[0045] Figure 2 This invention provides a flowchart for the generation and presentation of digital gift content based on gift-giving scenarios.

[0046] Figure 3 The present invention provides a flowchart for the generation, presentation, and reading of digital gift content based on a gift-giving scenario;

[0047] Figure 4 A flowchart for selecting digital gift content generation and presentation templates based on gift-giving scenarios provided by this invention;

[0048] Figure 5 A module diagram of a digital gift content generator for generating and presenting content based on gift-giving scenarios provided by this invention;

[0049] Figure 6 A diagram of a digital gift content generation and presentation text generator module based on gift-giving scenarios provided by this invention;

[0050] Figure 7 This invention provides a lifecycle management diagram for digital gift content generation and presentation based on gift-giving scenarios;

[0051] Figure 8 A flowchart for generating and presenting the emotional layer of digital gift content based on a gift-giving scenario, provided by this invention;

[0052] Figure 9 The flowchart of the data preference and recommendation engine for digital gift content generation and presentation based on gift-giving scenarios provided by this invention. Detailed Implementation

[0053] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0054] In the specific implementation process, such as Figures 1-9 As shown, a method for generating and presenting digital gift content based on a gift-giving scenario includes the following steps:

[0055] Step S1: Receive the gift-giving scenario type and personalized content information input by the user.

[0056] Users select the gift-giving scenario through terminal applications (such as mobile apps or web pages), such as "coming-of-age ceremony". At the same time, users upload personalized content, such as one or more photos of the recipient, a voice message or a text message.

[0057] Step S2: Based on the scene type, match the corresponding scene template from the preset template library.

[0058] The system's scene template engine calls the corresponding scene template from the template library based on the "coming-of-age ceremony" scene selected by the user. The template predefines a solemn and slightly futuristic visual style (such as dark blue tones and starry sky elements), inspirational music (such as grand orchestral fragments), and a formal and hopeful copywriting style. The template also specifies the content structure: the opening is an age evolution video, the middle section is a projection of future careers, and the ending is a message copywriting.

[0059] Step S3: Invoke the controllable multimodal generation engine to generate digital content that matches the scene.

[0060] The controllable multimodal generation engine receives photos uploaded by the user and scene templates determined in step S2, and then activates its vertical generation capabilities:

[0061] Age evolution generation: Based on the recipient's current photo, generate a short video showing the recipient gradually growing from infancy to their current adult appearance.

[0062] Career Role Projection Generation: Based on the "astronaut" dream that the user may select in step S1, generate a futuristic image or short video of the recipient wearing a spacesuit and in a space capsule background from the recipient's photo.

[0063] Scene Atmosphere Enhancement: The system automatically adds a "sparkling starlight" visual effect to the generated age evolution video and career projection images, and mixes in the background music determined in step S2 to enhance the solemn and futuristic atmosphere. After generation, the system provides 2-3 high-quality candidate contents for the user to choose from, ensuring the controllability and stability of the generated results.

[0064] Step S4: Call the emotional copy generation module to generate emotional copy that matches the scene.

[0065] The emotional copywriting generation module generates the final message copy based on the sentence template of the "coming-of-age ceremony" scenario (e.g., "Today, you officially step into the adult world. May you [user-inputted personality traits], in the future [user-inputted expectations]..."), and combined with the personality traits and expectations entered by the user in step S1. For example, "Today, you officially step into the adult world. May your perseverance and curiosity lead you to explore the endless stars and sea in the future."

[0066] Step S5: Determine the content binding strategy based on the gift content lifecycle type.

[0067] The user or system presets the "coming-of-age" gift as node-type content, and the content lifecycle management module determines the binding strategy accordingly: the digital content and emotional copy generated in steps S3 and S4 will be permanently fixed as core content, but at the same time, the system allows binding a dynamic emotional layer to the content, which will generate dynamic emotional prompts based on subsequent touch behavior and time information.

[0068] Step S6: Bind the generated content as a content identifier and write it to the NFC tag.

[0069] The system packages the finalized digital content (videos, pictures), emotional text, and lifecycle type (node ​​type) in the cloud and generates a unique content identifier (such as a URL or UUID). Then, through an NFC reader / writer device, the content identifier is written into a physical NFC tag, which is embedded or attached to a physical gift (such as a commemorative photo album or a customized ornament).

[0070] Step S7: The recipient touches the NFC tag for the first time, triggering a ritualistic display.

[0071] When the recipient first touches the NFC tag on the gift with an NFC-enabled mobile phone, see [link / reference]. Figure 3 The process is as follows:

[0072] The NFC interaction module reads the content identifier in the tag and requests the content from the cloud.

[0073] The first touch ceremony presentation module is triggered, playing a 1.2-second "opening the envelope" animation on the recipient's phone screen to create a sense of ritual for opening important letters.

[0074] Immediately after the animation ends, the digital content generated in steps S3 and S4 (such as videos of age evolution and photos of astronauts) and emotional text will be displayed in full screen.

[0075] Step S8: The recipient touches the NFC tag again to realize the dynamic emotion.

[0076] When a recipient touches the NFC tag multiple times at different times, the system presents different experiences:

[0077] If the content is preset to be dynamic (such as a surprise gift between couples), the content lifecycle management module will automatically switch the content version based on the number of touches. The first touch will display version one (a confession video), and the second touch will automatically switch to version two (another memory video).

[0078] In the node-based content scenario of this embodiment, the digital content itself remains unchanged (the same video showing age evolution and astronaut images are displayed each time). However, the emotion dynamic layer generation module generates a dynamic emotion prompt before or during the content display based on the time difference between the "gift-giving time" and the "current time," as well as the cumulative number of touches. For example:

[0079] The second touch prompts: "This is the second time you've reviewed this message for adulthood."

[0080] When touched on the 100th day after the gift is given, a prompt appears: "100 days have passed since you became an adult. May your original intention remain unchanged." This achieves a unique experience of "static content and dynamic emotions."

[0081] A digital gift content generation and presentation system based on gift-giving scenarios includes the following modules:

[0082] Scene template engine: As one of the core scheduling components of the system, it stores and manages templates for different scenes (confession, birthday, coming-of-age ceremony, etc.). When a user selects a scene, the engine can quickly match and call the corresponding template resources, providing constraints and guidance for subsequent generation.

[0083] Controllable Multimodal Generation Module: This module is the production center for digital content, and it further includes:

[0084] Age evolution generation submodule: Using a specially trained face age synthesis model, a single portrait is input and the output is a smooth age evolution sequence image or video.

[0085] The Future Professional Role Generation Submodule: Based on image segmentation, style transfer, and generative adversarial network (GAN) technologies, it merges the input portrait with a preset professional clothing template to generate a realistic future professional image.

[0086] Scene Atmosphere Enhancement Submodule: Adds particle lighting effects (such as candlelight and starlight) to images / videos using computer graphics algorithms, and intelligently mixes background music with the original audio and video uploaded by the user using audio processing technology.

[0087] The emotional copywriting generation module has a large number of built-in sentence templates and emotional dictionaries for different scenarios. It combines user-input keywords and uses natural language generation (NLG) technology to fill and optimize templates, and output copywriting that is appropriate for the context and full of emotion.

[0088] Content Lifecycle Management Module: This module maintains a content strategy table that defines the lifecycle rules for each gift type (dynamic / node). For dynamic content, it manages the switching logic of multiple content versions (such as by time or by day); for node content, it activates the emotional dynamic layer.

[0089] The emotion dynamic layer generation module has a built-in time calculator and touch counter. Based on the instructions of the content lifecycle management module, it calculates the time difference and counts the number of touches in real time, and selects or fine-tunes appropriate prompt text from the preset emotion prompt corpus to generate appropriate prompt text.

[0090] First Touch Ceremony Presentation Module: This module is tightly integrated with the client application and embeds lightweight animation resources such as "opening an envelope". When it receives the "first touch" command from the cloud, it immediately calls up the local animation resources to play, and then notifies the player to display the main content.

[0091] Data collection and preference learning module: During user usage, this module anonymously collects the user's final selected template, rating of the generated content, copy modification records, and opening behavior (such as viewing completion rate). This data is used to train the recommendation model, optimize the template selection strategy and generation quality of the scene template engine and the controllable multimodal generation module, and achieve personalized recommendations.

[0092] NFC interaction module: includes a writing end and a reading end. The writing end is used to write the content identifier generated in the cloud into the NFC tag. The reading end is used to read the content identifier in the NFC tag when touched and communicate with the cloud server to obtain the corresponding content, instructions or updates.

[0093] Gift-Giving Scenario AI Agent Intelligent System: This invention further includes an AI Agent intelligent system for gift content generation, user personality feature recognition, scenario-based behavior understanding, and dynamic recommendation. Through long-term data accumulation, user interaction feedback, and scenario-structured label training, this system gradually forms an intelligent service core that understands the gift-giving context, user emotions, and user attributes, thereby achieving higher-quality and more emotionally valuable content generation and recommendation capabilities.

[0094] AI Agent comprises two core sub-agents:

[0095] Scenario-driven GiftAI Agent.

[0096] This AI agent primarily serves gift-giving scenarios. By understanding the specific scenario selected by the user (such as a confession, birthday, anniversary, coming-of-age ceremony, parent-child activity, or friendship), it automatically generates content that best matches the atmosphere of the scenario. Its capabilities include:

[0097] Scene understanding ability: Automatically recognizes emotional tone, visual style, music style and text tone;

[0098] Multimodal generation capability scheduling: Based on the scene, it can call up capabilities such as age evolution video, future professional image generation, digital human generation, and scene lighting effect enhancement;

[0099] Data-driven content optimization: Automatically optimizes and generates templates and style selections based on platform historical data and user preferences;

[0100] Dynamic content planning capability: Automatically plans time-series content versions for scenarios such as couples and multiple surprises, and combines them with the NFC multi-version content mechanism to achieve long-term interactive experiences.

[0101] Personality / Zodiac AI Agent: This agent is used for personalized content recommendations for standardized products (such as zodiac keychains and persona figurines). Based on the user's selected zodiac or personality tags, it automatically generates daily content output that matches the user's attributes, including:

[0102] Daily dos and don'ts / lucky colors / mood reminders, etc.;

[0103] Healing quotes, stories, illustrations, or videos corresponding to astrological signs / personalities;

[0104] The ability to predict sentiment and provide personalized recommendations based on users' long-term behavior.

[0105] Through the two intelligent agents mentioned above, this invention forms an intelligent service system that differs from traditional content tools, enabling gift content to possess dynamic, long-term, personalized, and emotional companionship value, thereby significantly enhancing the product's competitive advantage.

[0106] Systematic long-term learning:

[0107] User preferences (copywriting style, color scheme, template selection);

[0108] Overall platform preferences (statistics on which templates are most popular);

[0109] The best combination of scene templates and copywriting;

[0110] In the future, it will be possible to automatically recommend the "best gift content".

[0111] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for generating and presenting digital gift content based on gift-giving scenarios, characterized in that, Includes the following steps: S1: Receives the gift-giving scenario type and personalized content information input by the user; S2: Based on the scene type, match the corresponding scene template from the preset template library. The scene template defines at least a visual style, a music style, a copywriting style, and a content structure. S3: Call the controllable multimodal generation engine to generate digital content that matches the scene based on the personalized content information and scene template. The generation engine has preset vertical generation capabilities, including character age evolution, occupational role projection and scene atmosphere enhancement. S4: Call the emotional copy generation module, combine the scene sentence template with user input, and generate emotional copy that is appropriate for the scene; S5: Determine the content binding strategy based on the gift content lifecycle type. Dynamic content types support multiple versions of content and automatically switch according to preset conditions, while node-type content types keep the content fixed but support the generation of dynamic emotion prompts. S6: Bind the generated digital content, emotional copy, and lifecycle information as a content identifier and write it into the near-field communication (NFC) tag in the physical gift; S7: When the recipient touches the NFC tag for the first time, a ritualistic transition animation is triggered and the digital content is displayed; S8: When the recipient touches the NFC tag again, if it is dynamic content, the content version will be switched according to the rules; if it is node-type content, an emotion prompt will be generated to realize the emotion dynamics.

2. The method according to claim 1, characterized in that, The version switching of the dynamic content is automatically executed by the content lifecycle management module based on the date or the number of touches.

3. The method according to claim 1, characterized in that, When the node-type content is touched again, the emotion dynamic layer generation module generates an emotion prompt based on the time difference or the number of touches.

4. The method according to claim 1, characterized in that, The ritualistic transition animation is an envelope-opening animation, lasting from 1 to 1.5 seconds.

5. A digital gift content generation and presentation system based on gift-giving scenarios, characterized in that, include: The scene template engine is used to select the corresponding scene template from the template library based on the scene type. The controllable multimodal generation module is used to generate digital content based on user input and scene templates, and has the ability to generate age evolution, occupational projection and atmosphere enhancement. The emotional copy generation module is used to generate emotional copy that matches the scene. The content lifecycle management module is used to manage the lifecycle strategy of content, and supports multi-version switching of dynamic content and the generation of sentiment prompts for node content. The emotion dynamic layer generation module is used to generate dynamic emotion prompts in node-type content displays; The First Touch Ceremony Presentation module is used to trigger a ceremony animation and display content upon the first touch. The data collection and preference learning module is used to record user behavior and preferences to optimize template selection and content recommendation. The gift scene AI Agent intelligent agent system is connected to the data collection and preference learning module and is used to train based on the accumulated user data and scene data to realize personalized content recommendation, generation strategy optimization and dynamic content planning. It includes contextualized content generation AI agents and persona / zodiac attribute AI agents; The NFC interaction module includes a writing end and a reading end. The writing end is used to write the content identifier generated in the cloud into the NFC tag. The reading end is used to read the content identifier in the NFC tag when touched and communicate with the cloud server to obtain the corresponding content, instructions or updates.

6. The system according to claim 5, characterized in that, The controllable multimodal generation module includes an age evolution generation submodule, which is used to generate age evolution images or videos based on portrait photos.

7. The system according to claim 5, characterized in that, The controllable multimodal generation module includes a future professional role generation submodule, which is used to generate a future image of a person wearing professional clothing.

8. The system according to claim 5, characterized in that, The controllable multimodal generation module includes a scene atmosphere enhancement submodule, which is used to add visual lighting effects and music effects to the uploaded content.

9. The system according to claim 5, characterized in that, The emotional copywriting generation module generates at least one type of message or copywriting based on scene sentence templates, and supports dynamic copywriting generation based on time or number of touches.

10. The system according to claim 5, characterized in that, The data collection and preference learning module records user template selection, copywriting preferences, and opening behavior, which are used for personalized content recommendation and template strategy updates.

Images