On-Device Context Analysis for Voice Assistant Suggestions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users of digital devices may not be aware of the tasks that can be performed by digital assistants and how to request them, and existing solutions fail to provide relevant suggestions based on user context.
Innovation Solution
An electronic device receives context data to determine tasks that can be performed by a digital assistant and provides personalized suggestions when certain criteria are met, ensuring the suggestions are relevant to the user's current activity and knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the digital assistant provides suggestions for tasks that can be performed, then user awareness and engagement with the digital assistant improves, but the device consumes more power due to additional processing and display operations
Solution Approach 1:
The system performs preliminary analysis of context data, user activity, and suggestion criteria before generating suggestions. By pre-evaluating whether suggestion criteria are satisfied based on received context data and current user activity, the system avoids unnecessary suggestion generation and display, thereby reducing power consumption while maintaining effective user engagement when suggestions are truly relevant.
2Adaptability or versatility
If the digital assistant provides personalized suggestions based on context data, then suggestion relevance and user engagement increases, but the processing time and computational resources increase
Solution Approach 1:
The system implements partial action by selectively generating suggestions only when specific criteria are satisfied, rather than continuously analyzing all context data. The processor evaluates suggestion criteria against current user activity and context data, and only provides personalized suggestions when the criteria indicate high relevance, thereby reducing overall processing time while maintaining personalization quality for meaningful interactions.
3Measurement precision
If the device continuously monitors context data to provide relevant suggestions, then suggestion accuracy improves, but the energy consumption and processing load increase
Solution Approach 1:
The system employs periodic action by monitoring context data and user activity at specific intervals or triggered by particular events, rather than continuously analyzing all inputs. The processor periodically evaluates whether suggestion criteria are satisfied based on received context data, providing accurate suggestions when criteria are met while consuming less energy compared to continuous monitoring approaches.
Data Source
AI summary
Systems and processes for providing personalized suggestions indicating that a task may be performed using a digital assistant of an electronic device are provided. An example method includes, at an electronic device with a display, receiving context data associated with the electronic device; determining, based on the context data, a task that may be performed by a digital assistant of the electronic device in response to a natural-language expression; determining, based on the context data, whether suggestion criteria associated with the determined task are satisfied; and in accordance with a determination that the suggestion criteria are satisfied, providing a suggestion indicating that the determined task may be performed using the digital assistant of the electronic device.