Ambient Speech Command Paths for Privacy-Preserving Device Control
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Solution Overview
Problem
Conventional computing device control methods require manual user intervention and can be time-consuming or interruptive, lacking efficient background operation and privacy preservation.
Innovation Solution
A computing device analyzes ambient audio signals using machine-learned models to identify semantic entities and generate a command path for automated control actions, allowing user confirmation and correction, while preserving privacy through local processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual user intervention is used to control computing devices, then user control and precision are improved, but user efficiency and time consumption are worsened
Solution Approach 1:
The system enables self-service by automatically analyzing ambient audio signals and executing commands without requiring manual user intervention. The machine-learned model autonomously identifies semantic entities, determines command paths, and performs actions based on spoken input, allowing the system to serve itself rather than requiring continuous user control.
Solution Approach 2:
The patent replaces manual mechanical interaction (typing, clicking, navigating menus) with acoustic field-based interaction through speech recognition. The machine-learned model processes audio signals to extract commands, substituting the mechanical control system with an acoustic sensing and processing system that improves efficiency while maintaining control precision.
2Productivity
If ambient audio analysis is performed continuously in background, then user efficiency is improved, but device complexity and energy consumption are worsened
Solution Approach 1:
The system implements periodic action by analyzing ambient audio signals at scheduled intervals rather than continuously monitoring all audio data at full processing capacity. The machine-learned model periodically evaluates audio segments for command opportunities, reducing computational complexity and energy consumption while maintaining the ability to respond to user needs efficiently.
Solution Approach 2:
The system performs preliminary action by pre-processing and filtering ambient audio signals to identify potential commands before full analysis. The machine-learned model prepares by detecting speech patterns and semantic entities in advance, organizing data structures and command paths preliminarily, which reduces the complexity of real-time decision-making and lowers instantaneous energy requirements.
3Reliability
If data is processed locally for privacy preservation, then privacy protection is improved, but computational requirements and device complexity are worsened
Solution Approach 1:
The patent applies segmentation by dividing the processing architecture into distinct functional modules: audio signal acquisition, speech recognition, semantic entity identification, command path determination, and action execution. This modular segmentation allows privacy-sensitive processing to occur locally on the device while enabling energy-efficient distributed computation where appropriate, balancing privacy protection with energy consumption through architectural division.
Data Source
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AI summary
A computing system can provide enhanced control responsive to ambient interactions from a user. The computing system can obtain context data including an ambient audio signal. The computing system can generate a command path based at least in part on the context data. The command path can include an ordered one or more command actions. The computing system can provide an interactive user interface element depicting the command path to the user. The interactive user interface element can enable the user to select a selected command action of the ordered one or more command actions for performance by the computing system. The computing system can, in response to providing the command path to the user, receive, from the user, the selected command action of the ordered one or more command actions. In response to receiving, from the user, a selected command action of the ordered one or more command actions, the computing system can perform the selected command action to control the computing system based on the selected command action.