Language-Model Light Effect Generation for Simple Customization
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Solution Overview
Problem
Traditional electronic devices lack user-friendly methods for customizing light effects, with existing customization options being complex and difficult to operate.
Innovation Solution
A device and method utilizing a language model to generate light effects based on user input text, automatically generating color and rhythm data to control a light-emitting module, reducing operational complexity and enhancing design diversity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional preset light effect modes are used, then device complexity is reduced, but adaptability and design diversity are limited
Solution Approach 1:
The system enables users to customize light effects through natural language input, where the language model automatically interprets user intent and generates corresponding light effect parameters. This self-service approach allows users to create personalized light effects without navigating complex settings menus, thus improving adaptability while maintaining operational simplicity.
Solution Approach 2:
A language model serves as an intermediary between the user's natural language input and the light effect control system. The model translates user descriptions into structured light effect parameters, bridging the gap between simple user input and the complex light effect generation process, thereby enhancing customization without increasing operational complexity.
2Adaptability or versatility
If independent light effect setting function is provided, then adaptability is improved, but ease of operation deteriorates due to complex operations
Solution Approach 1:
The patent replaces the traditional mechanical interaction model (clicking through menus, adjusting sliders, selecting from predefined options) with a natural language processing system. Users simply type or speak their desired light effect, and the language model converts this into actionable parameters, substituting complex manual operations with intuitive language-based control.
Solution Approach 2:
The system automatically generates light effect parameters based on user input without requiring users to manually configure multiple settings. The language model performs the entire configuration process autonomously, from interpreting user intent to generating final light effect parameters, making the system both adaptable and easy to operate.
3Ease of operation
If automated language model processing is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The language model serves multiple functions within the system: it interprets user intent, extracts key parameters, generates light effect configurations, and handles various input formats. This multi-functional approach consolidates what would otherwise require separate modules into a single versatile component, improving ease of operation while managing system complexity through functional integration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables easy customization of light effects through user input, improving user experience and design freedom by automating the generation of light effect data.
Implementation Method 1
The light-emitting module is electrically coupled to the processor, and is configured to generate the light effect based on the light effect data
Data Source
AI summary
A device for generating a light effect is provided. The device includes an input module configured to receive an input text, a processor, and a light-emitting module. The processor is configured to generate, with a language model, an abstract text corresponding to the input text, generate a scenario description text corresponding to the abstract text, generate at least one keyword corresponding to the scenario description text, and generate color data corresponding to the at least one keyword. The processor further generates, with the scenario description text and a preset symbol string as an input for the language model, a scenario symbol string corresponding to the scenario description text, and generates, with a preset algorithm, a number set corresponding to the scenario symbol string. The color data and the number set are combined to generate light effect data to control the light-emitting module to generate a light effect.