AI Character Model Augmented Parameter Retrieval
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Solution Overview
Problem
Existing virtual character models lack the ability to dynamically adjust conversations based on changing contextual environments, such as user emotions or events, due to fixed parameters, limiting their interaction capabilities across different applications and environments.
Innovation Solution
A system and method for retrieving and generating augmented parameters for AI-based character models using keywords, which allows for real-time updates and integration of additional information from data sources, enabling the AI character to evolve and respond appropriately to changing contexts through the use of large language models and multimodal interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional virtual character models use fixed parameters for the duration of conversation, then the model structure remains simple and stable, but the character cannot dynamically adjust conversations based on changing contextual environments
Solution Approach 1:
The patent implements dynamic parameters that can change during conversation based on contextual environment changes, user emotions, and events. The system retrieves augmented parameters from data sources in real-time and updates character model parameters dynamically, transforming the static parameter structure into a dynamic one that adapts to changing conditions.
Solution Approach 2:
The patent introduces an intermediary component that retrieves augmented parameters from external data sources based on keywords extracted from conversation context. This intermediary layer enables the character to access additional information and adjust parameters without fundamentally restructuring the entire model, resolving the complexity issue.
2Adaptability or versatility
If virtual character models are developed for specific applications with specific rules, then the model development process is straightforward, but the models lack ability to integrate with other applications and environments
Solution Approach 1:
The patent creates a universal framework where character models can operate across multiple applications and environments. By using a standardized parameter retrieval mechanism that works with any data source and any conversation context, the system enables single character models to be deployed in diverse applications without redeveloping from scratch.
Solution Approach 2:
The system performs preliminary retrieval of augmented parameters from data sources before conversations begin or when context changes occur. This preliminary action prepares the character model with relevant information in advance, enabling seamless integration across different applications without requiring complex real-time adaptations during deployment.
3Reliability
If virtual character models maintain constant parameters throughout conversation, then the computational resources required are minimal, but the models cannot respond appropriately to changing contexts such as user emotions or environmental events
Solution Approach 1:
The patent implements periodic retrieval of augmented parameters at key moments during conversation - initially to establish context and then when contextual changes are detected (such as emotion shifts or environmental events). This periodic update approach ensures context-appropriate responses while minimizing unnecessary computational resource consumption compared to continuous parameter changes.
Solution Approach 2:
The system automatically detects contextual changes in the conversation environment and triggers parameter retrieval only when needed. The character model monitors its own conversation state and autonomously decides when to update parameters based on detected changes, eliminating the need for constant external control and optimizing computational resource usage.
Data Source
AI summary
Systems and methods for retrieval of augmented parameters for an artificial intelligence (AI)-based character are provided. An example method includes receiving, from a user via a user interface, at least one keyword describing the AI-based character; retrieving, from at least one data source and based on the at least one keyword, the augmented parameters describing the AI-based character; and generating, based on the augmented parameters, an AI-based character model corresponding to the AI-based character. The at least one data source includes a database configured to store records associated with the AI-based character, an online search service, and a set of clusters associated with a type of a feature of the AI-based character and at least one hidden prompt corresponding to the type of the feature. The type of the feature includes one of the following: a voice, a dialog style, an emotional state, an age, and temperament.