AI Effect Generation System for Text-to-Content Automation
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Solution Overview
Problem
Existing Internet-based tools for content creation and feature design, such as effect creation tools, require complex user interface operations and substantial domain knowledge, creating a high barrier to entry for effect creation and making the process overly time-consuming for beginner to intermediate level creators.
Innovation Solution
The use of artificial intelligence (AI) technologies to automatically generate effects based on text input from users, allowing for the creation of effects with little to no domain knowledge or experience, and reducing the time required for effect generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If complex user interface operations are used in effect creation tools, then effect creation capability is provided, but barrier to entry increases and operation complexity increases
Solution Approach 1:
The patent replaces complex mechanical UI operations with AI-based automated effect generation. Instead of requiring users to manually configure multiple parameters and interfaces, the system uses natural language processing to automatically generate effects, substituting complex mechanical operations with simpler linguistic interactions.
Solution Approach 2:
The patent introduces an AI model as an intermediary between the user's simple text input and the complex effect generation system. This intermediary translates user-friendly natural language into the complex parameters needed for effect creation, shielding users from the underlying complexity while maintaining full functionality.
2Adaptability or versatility
If complex user interface operations are used in effect creation tools, then effect creation capability is provided, but time required for effect generation increases
Solution Approach 1:
The patent replaces time-consuming manual UI operations with AI-based automated generation. The system processes natural language inputs and generates effects automatically, eliminating the need for users to spend time configuring complex interfaces and significantly reducing overall effect generation time.
Solution Approach 2:
The AI model performs preliminary processing by pre-computing and preparing effect parameters based on the user's text input. This preliminary action eliminates the need for users to manually configure multiple parameters, accelerating the overall effect generation process.
3Manufacturing precision
If complex user interface operations are required, then detailed effect control is achieved, but domain knowledge requirement increases
Solution Approach 1:
The patent introduces an AI model as an intermediary that translates simple user text inputs into precise effect parameters. This intermediary maintains the precision of effect control while eliminating the need for users to possess domain knowledge about complex parameters and configurations.
Solution Approach 2:
The patent substitutes mechanical parameter configuration with AI-based automated parameter generation. The system automatically determines and configures all necessary effect parameters based on natural language input, maintaining precision while eliminating the need for users to understand or configure these parameters manually.
Data Source
AI summary
The present disclosure describes techniques for automatically generating effects. A plurality of effect ideas may be generated by at least one trained machine learning model in response to receiving text input by a user. An effect idea may be decomposed into a plurality of components in response to selecting the effect idea. The effect idea may be among the plurality of effect ideas. Executable code may be generated based on decomposing the effect idea. The code may be executed by a predetermined effect creation tool to generate an effect. The generated effect may be output.