In-Vehicle Voice Assistant Context Routing for Personalized Responses
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing voice assistants in vehicles often fail to provide personalized responses to user prompts due to a lack of consideration for environmental context and user intent, leading to inefficient use of computing resources and repeated user interactions.
Innovation Solution
A master language model agent processes user prompts with environmental data to determine intermediate actions, iteratively evaluates these actions to ensure they satisfy the user's intent, and generates tailored responses, reducing the need for repetitive user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a voice assistant processes user prompts without environmental context, then computing resources are conserved, but personalization and response accuracy deteriorate
Solution Approach 1:
The system performs preliminary actions by continuously collecting environmental data from sensors (microphones, cameras, temperature sensors, etc.) before user prompts are processed. This pre-collection of contextual information about the vehicle environment, user preferences, and current state allows the voice assistant to quickly generate personalized responses without extensive real-time processing, thus conserving computing resources while maintaining personalization capability
Solution Approach 2:
The patent introduces an intermediary layer between the voice assistant and environmental data - a context management system that pre-processes and structures environmental information. This intermediary organizes sensor data, user profile data, and vehicle state information into readily accessible formats, allowing the voice assistant to efficiently retrieve relevant context without direct complex processing of raw environmental data, balancing resource usage with personalization quality
2Measurement precision
If the voice assistant requires repeated user interactions to clarify intent, then response accuracy improves, but user time and productivity deteriorate
Solution Approach 1:
The system implements feedback mechanisms where the voice assistant continuously monitors user responses, environmental context, and interaction patterns. By analyzing this feedback in real-time alongside pre-collected environmental data, the system can infer user intent more accurately across fewer interactions. The feedback loop allows the assistant to learn from each interaction and improve subsequent responses, reducing the need for repeated clarifying questions and saving user time while maintaining high response accuracy
3Adaptability or versatility
If environmental data is collected and processed, then personalization improves, but device complexity increases
Solution Approach 1:
The patent segments the complex task of personalization into distinct modular components: environmental data collection modules (sensors), data processing modules (context analysis), user profile management modules, and response generation modules. Each segment handles a specific aspect of personalization independently, making the overall system more manageable despite the increased complexity. This modular segmentation allows for easier maintenance, debugging, and updates while delivering comprehensive personalization capabilities
Data Source
AI summary
Methods, computing systems, and technology for personalizing a user experience in a vehicle. For example, a computing system may be configured to receive a user prompt from a user, wherein the user prompt is input into a voice assistant on-board the vehicle. The computing system may be configured to process the user prompt with a master language model agent. The master language model agent may determine, based on environmental data, one or more intermediate actions responsive to the user prompt. The master language model agent may evaluate, based on the environmental data, whether each intermediate action of the one or more intermediate actions satisfies the user prompt. The computing system may be configured to output one or more command instructions to the voice assistant, wherein the one or more command instructions cause the voice assistant to provide, using one or more human-machine interfaces, a response to the user prompt.