Local Voice Command Prediction for Privacy-Aware Device Control
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Solution Overview
Problem
Existing digital assistants face challenges with privacy concerns due to voice data being sent to the cloud for processing, limited local processing capacity, and the need for wake words, which can detract from user experience.
Innovation Solution
A system that analyzes device state information to predict voice commands and intended devices within a localized network, leveraging interconnected devices for processing and minimizing cloud reliance, using local knowledge graphs and voice shortcuts to enhance accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If voice data is sent to cloud for processing, then processing capability is improved, but privacy is compromised
Solution Approach 1:
The patent segments voice processing into multiple stages: local preprocessing (wake word detection, basic command recognition) and selective cloud processing (complex queries, ambiguous commands). This segmentation allows the system to maintain privacy by keeping sensitive processing local while still leveraging cloud capabilities when necessary.
Solution Approach 2:
The patent introduces an intermediary layer (local processing unit) between the microphone and cloud server. This intermediary filters and pre-processes voice data locally, sending only necessary data to the cloud, thereby reducing privacy exposure while maintaining processing effectiveness.
2Object-affected harmful factors
If all voice commands are processed locally, then privacy is improved, but processing capacity is limited
Solution Approach 1:
The patent implements dynamic processing capacity allocation where the system adapts between local-only mode, hybrid mode, and cloud-dependent mode based on device state, command complexity, and network availability. This dynamic approach allows the system to maximize local processing for privacy-critical operations while leveraging cloud resources when needed.
Solution Approach 2:
The patent performs preliminary processing actions locally (wake word detection, basic intent recognition) before determining whether cloud processing is needed. This preliminary action reduces the burden on cloud resources and maintains privacy for routine operations.
3Reliability
If wake word is required for activation, then false triggering is reduced, but user experience is degraded
Solution Approach 1:
The patent applies different activation requirements to different devices and contexts: wake words are required for some devices but not others, and the requirement can change based on device state and environmental context. This localized approach maintains reliability where needed while improving ease of operation where appropriate.
Solution Approach 2:
The patent dynamically adjusts wake word requirements based on device state, user behavior patterns, and environmental context. The system learns when wake words are necessary and when they can be omitted, adapting to provide optimal balance between reliability and user experience.
4Measurement precision
If device state information is monitored continuously, then command prediction accuracy is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic sampling of device state information rather than continuous monitoring. The system checks device states at intervals and triggers processing only when state changes occur or when prediction confidence thresholds are met, reducing energy consumption while maintaining prediction accuracy.
Solution Approach 2:
The patent performs preliminary analysis of device state information to determine whether full processing is needed. The system identifies key state changes that warrant processing and filters out routine updates, reducing computational overhead and energy consumption while maintaining prediction accuracy for significant events.
Data Source
AI summary
Systems and methods are described for causing a device to perform an action based on a voice command. Devices connected to a localized network and capable of performing one or more actions based on one or more voice inputs may be identified, and device state information for each of the devices may be determined. The systems and methods may determine, based at least in part on the device state information, a predicted voice command, and a particular device of the plurality of devices for which the predicted voice command is intended. A voice input may be received, and based on receiving the voice input, the particular device may be caused to perform an action related to the predicted voice command.