Context-Aware Voice Command Disambiguation
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Solution Overview
Problem
Mobile computing devices face challenges in disambiguating user input, particularly with voice commands, due to homophones, background noise, and increased complexity of recognized commands, leading to incorrect interpretations and user frustration.
Innovation Solution
The system determines a current context for the mobile device, including location, motion, and recent activity, to disambiguate ambiguous user input by selecting the most likely intended command, thereby reducing the need for specific input and improving user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If voice input recognition is expanded to recognize more commands, then the device's functionality and versatility improve, but the accuracy of input interpretation deteriorates due to increased ambiguity and homophones
Solution Approach 1:
The system performs preliminary context analysis before finalizing command interpretation. By examining context indicators (location, time, recent activities) in advance, the system pre-filters possible interpretations and prepares the most likely meaning before the user completes their input, thereby resolving ambiguity proactively rather than reactively
Solution Approach 2:
Context indicators serve as intermediary elements between the ambiguous voice input and the final command interpretation. Rather than directly mapping voice input to commands, the system introduces context analysis as a mediating layer that bridges the gap, using contextual clues to disambiguate homophones and select the intended meaning
2Measurement precision
If the system requests more specific input to resolve ambiguity, then input interpretation accuracy improves, but ease of operation deteriorates due to increased user effort
Solution Approach 1:
The system performs self-service by automatically analyzing context indicators and disambiguating input without requiring user intervention. Instead of asking users to rephrase or clarify their input, the system independently examines contextual clues (location, time, recent activities) and selects the most likely intended meaning, making the disambiguation process transparent and effortless for the user
3Measurement precision
If context analysis is performed to disambiguate input, then input interpretation accuracy improves, but device complexity increases due to additional sensing and processing requirements
Solution Approach 1:
The system leverages multi-functionality by repurposing existing device components for context analysis. Sensors originally designed for other purposes (GPS for location, accelerometer for motion detection, calendar for time-based context) are reused to provide contextual clues for disambiguation, avoiding the need for dedicated context-sensing hardware and reducing overall system complexity
Solution Approach 2:
The system merges context analysis with the existing command processing pipeline. Rather than creating a separate, standalone context analysis subsystem, the patent integrates contextual clue examination into the existing speech recognition and command interpretation workflows, combining multiple functions into unified processing stages that share computational resources and reduce overhead
Data Source
AI summary
In one implementation, a computer-implemented method includes receiving, at a mobile computing device, ambiguous user input that indicates more than one of a plurality of commands; and determining a current context associated with the mobile computing device that indicates where the mobile computing device is currently located. The method can further include disambiguating the ambiguous user input by selecting a command from the plurality of commands based on the current context associated with the mobile computing device; and causing output associated with performance of the selected command to be provided by the mobile computing device.