Virtual Assistant Task Planning with Dynamic Content Curation
Solution Overview
Problem
Current voice assistants (VAs) are limited in understanding user intent and ensuring successful task execution, as they lack multi-turn conversation capabilities, dynamic task-specific instruction curation, robust failure detection, and personalization, restricting their ability to handle complex tasks and user preferences effectively.
Innovation Solution
The system employs user-specific knowledge for personalization and domain-specific knowledge for context adaptation, enabling dynamic content curation and fault-tolerant execution, with proactive monitoring and recovery options, and learning user preferences over time to provide personalized and effective task assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current voice assistants use fixed dialogue trees for narrow topics, then device complexity is reduced, but adaptability and versatility deteriorate
Solution Approach 1:
The patent implements a universal task planning framework that enables the voice assistant to handle multiple types of tasks (information gathering, step-by-step instructions, shopping lists, reminders) through a single unified system rather than separate dialogue trees for each topic, thereby improving adaptability while managing complexity
Solution Approach 2:
The system dynamically generates task-specific plans based on user intent rather than following fixed predetermined dialogue paths, allowing the assistant to adapt to new topics and tasks on-the-fly through dynamic plan creation and modification
2Adaptability or versatility
If voice assistants provide fixed instructions for tasks, then ease of operation is improved, but adaptability to user preferences deteriorates
Solution Approach 1:
The system incorporates feedback mechanisms that monitor user responses and reactions during task execution, using this feedback to adapt and personalize future instructions based on individual user preferences and behaviors while maintaining operational consistency
Solution Approach 2:
The system performs preliminary analysis of user profiles and preferences before generating task instructions, preparing personalized instruction sets in advance that balance consistency with individual user preferences
3Reliability
If voice assistants have limited failure detection capabilities, then device complexity is reduced, but reliability deteriorates
Solution Approach 1:
The system proactively identifies potential failures before they occur by analyzing task plans and predicting where issues might arise, preparing recovery strategies in advance rather than reacting to failures after they happen
Solution Approach 2:
The system implements error handling and recovery mechanisms that are built into the task execution framework from the beginning, cushioning against potential failures through predefined recovery options and alternative approaches
4Productivity
If voice assistants use single-turn instructions, then device complexity is reduced, but productivity deteriorates
Solution Approach 1:
The patent segments complex tasks into smaller sub-tasks and steps that can be executed sequentially through multi-turn conversations, breaking down productivity-enhancing complex tasks into manageable components while maintaining overall task effectiveness
Data Source
AI summary
The disclosure deals with a system and method for improved general task-oriented virtual assistants (VAs). The presently disclosed framework incorporates discovery of knowledge from online sources to accomplish tasks (open world), user-specific knowledge for personalization, and domain-specific knowledge for context adaptation to recommend and assist the users over procedural tasks such as cooking and Do-it-Yourself (DIY) tasks. The approach also focuses on content curation for fault-tolerant execution to ensure the end goal is reached despite common failures.