Digital Assistant Task Reversal Using App Context and Session State
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Solution Overview
Problem
Existing digital assistants struggle with efficiently reversing tasks based on generic and ambiguous user inputs, requiring multiple inputs and increasing power consumption.
Innovation Solution
A digital assistant system that detects user speech inputs to perform and reverse tasks across different applications, determining task reversals based on the current application display and ongoing session, allowing for efficient task reversal with reduced input requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the digital assistant requires multiple inputs to reverse tasks, then the task reversal can be accurately identified, but the user interaction becomes more complex and power consumption increases
Solution Approach 1:
The system performs preliminary analysis by detecting the current displayed application and recent task history before receiving the reversal command. This preliminary action enables the digital assistant to automatically identify which task should be reversed without requiring multiple clarifying inputs from the user, thus reducing input complexity while maintaining accurate task reversal.
Solution Approach 2:
The digital assistant uses its own internal state information (current application display and recent task history) to automatically determine the target task for reversal. This self-service approach eliminates the need for multiple user inputs to disambiguate which task should be reversed, reducing interaction complexity while maintaining reliability.
2Reliability
If the digital assistant uses multiple inputs to determine task reversal, then the correct task can be identified, but power consumption increases
Solution Approach 1:
The system performs preliminary detection of the current displayed application and recent task history before processing the reversal command. This preliminary action leverages already-available system state information, avoiding the need to request additional user inputs that would consume extra power, while still achieving accurate task identification.
Solution Approach 2:
The digital assistant leverages its own internal tracking of application state and task history to automatically identify the target task for reversal. This self-service approach eliminates the need for additional user inputs and associated power consumption, while maintaining reliable task identification through the use of pre-collected system state data.
3Ease of operation
If the digital assistant reverses tasks without considering the current application display, then the reversal process is simpler, but the accuracy of task reversal decreases
Solution Approach 1:
The system uses feedback from the current displayed application and recent task history to automatically determine the correct task for reversal. This feedback mechanism enables simple user interaction (single reversal command) while maintaining high accuracy by using the system's own state information to disambiguate which task should be reversed.
Solution Approach 2:
The digital assistant uses its own internal state (current application display and task history) to automatically identify the target task for reversal. This self-service approach maintains both simplicity in user interaction and accuracy in task reversal by leveraging pre-existing system state information without requiring additional user inputs.
Data Source
AI summary
Systems and processes for reversing performance of tasks with different types of inputs are described. An example method includes, determining whether to reverse performance of a task based on a displayed application and/or a current session of a digital assistant and reversing the determined tasks when the appropriate determination is reached. An example method includes, performing a task in response to detecting a first type of input and reversing performance of the task in response to detecting a second type of input indicating reversal of the task.