AI Digital Assistant Task Recognition During Conversations
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Solution Overview
Problem
Current digital assistants lack the ability to seamlessly recognize and execute spoken tasks during ongoing conversations, requiring users to manually note reminders or instructions, which can be inconvenient and disruptive.
Innovation Solution
An AI-powered digital assistant that can identify spoken tasks within conversations and either perform them immediately or store them for later action, using contextual recognition and opt-in modes to determine when to intervene or defer task completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a digital assistant manually notes reminders or instructions during conversations, then task accuracy is improved, but conversation flow is disrupted and user convenience deteriorates
Solution Approach 1:
The patent introduces an AI system as an intermediary between the user and the task management process. The AI autonomously listens to conversations, identifies task requests, and manages them without requiring the user to manually interrupt or note tasks. This intermediary role resolves the contradiction by maintaining conversation flow while ensuring accurate task recognition through the AI's natural language processing capabilities.
Solution Approach 2:
The digital assistant is enhanced with self-service capabilities where the AI automatically detects, captures, and manages task requests from conversations without user intervention. The system autonomously processes task identification, categorization, and scheduling, eliminating the need for users to manually note tasks while preserving conversation naturalness.
2Productivity
If an AI system autonomously identifies and executes tasks during conversations, then productivity is improved, but system complexity increases
Solution Approach 1:
The patent integrates multiple functions into a single AI system architecture that can handle conversation analysis, task identification, task categorization, and task execution autonomously. By making the digital assistant universal and multi-functional, the system achieves high productivity without proportionally increasing complexity, as the same AI core performs diverse functions through natural language processing and contextual understanding.
Solution Approach 2:
The AI system performs preliminary actions by pre-processing conversation data in real-time, identifying task requests before users would need to manually note them. The system proactively captures task information, prepares it for execution, and manages task queues in advance, improving productivity by eliminating delays while the modular AI architecture manages complexity through automated preprocessing pipelines.
3Ease of operation
If users manually note reminders during conversations, then task management control is improved, but time consumption increases
Solution Approach 1:
The patent implements self-service functionality where the AI automatically detects, records, and manages task requests without requiring user action. The system autonomously transcribes spoken tasks, categorizes them, schedules them, and tracks their completion, eliminating the time users would spend manually noting tasks while maintaining control through user-configurable preferences and confirmation mechanisms.
Solution Approach 2:
The AI system enables continuous task management by operating throughout the entire conversation without interruption. The useful action of task recognition and recording continues seamlessly in the background, capturing tasks in real-time as they are mentioned, rather than requiring discrete manual intervention moments. This continuous operation eliminates time loss while maintaining user control through opt-in/opt-out mechanisms.
Data Source
AI summary
An indication associated with an AI mode enabled by an AI system is received from a user with an affirmative opt-in status. A first task request associated with the user is identified. One or more instructions associated with the first task request are contextually recognized. The first task request is completed based on the contextually recognized one or more instructions.