Chat-Based Character Generation for Easier Virtual Customization
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Solution Overview
Problem
Customization of virtual content, such as characters or objects, in interactive titles is often complex and time-consuming, overwhelming users, especially children, leading to unsatisfactory experiences and disengagement due to the difficulty in navigating numerous customization options.
Innovation Solution
A system utilizing chat-based communications interpreted by a machine learning model to generate custom virtual content, such as characters, by identifying and predicting virtual characteristics from user input, and presenting the custom content through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual input customization is provided with numerous options, then customization precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The patent replaces manual mechanical navigation through customization menus with an automated natural language processing system. Users speak or type their desired character characteristics, and the machine learning model automatically interprets this input to generate customization parameters, eliminating the need for users to manually navigate complex menu structures while maintaining high customization precision.
Solution Approach 2:
The system enables self-service customization by allowing users to directly express their customization desires through natural language. The machine learning model automatically processes this input and generates the appropriate customization settings without requiring user intervention in the technical selection process, making the system serve itself in interpreting and implementing customization requests.
2Adaptability or versatility
If numerous customization options are provided, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent introduces a natural language processing intermediary between the user and the complex customization system. Users communicate their preferences in simple natural language, and the intermediary model translates this into the appropriate customization parameters for the versatile customization options, shielding users from the underlying complexity while maintaining full adaptability.
Solution Approach 2:
The system replaces complex mechanical navigation through numerous customization menus with an automated interpretation system. The machine learning model directly processes natural language input to determine appropriate settings across multiple customization dimensions, maintaining versatility while eliminating interface complexity.
3Manufacturing precision
If manual customization navigation is required, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary interpretation of user intent through natural language processing before the actual customization generation. The machine learning model pre-processes the user's spoken or typed input to extract desired characteristics, preparing the customization parameters in advance, which significantly reduces the time required compared to manual navigation while maintaining accurate customization results.
Solution Approach 2:
The patent replaces time-consuming manual navigation through customization menus with automated natural language interpretation. Users can express their customization desires in a single speech or text input, and the system automatically processes this to generate accurate customization settings, reducing customization time from potentially minutes of menu navigation to a single natural language input.
Data Source
AI summary
Systems and methods for generating chat-based user-generated content. The system may receive a chat-based communication over a communication network from a user device of a user and interpret the chat-based communication using a machine learning model. This may include identifying a meaning of content within the chat-based communication and predicting that the content within the chat-based communication indicates one or more virtual characteristics. A custom character for use within a virtual environment may be generated based on the identified meaning and the predicted virtual characteristics. The custom character may include the predicted virtual characteristics. The system may present the custom character to the user via a user interface of the user device.