Voice Assistant Augmented by Smart Lens Oculesics
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Solution Overview
Problem
Current voice assistance systems require a verbal wakeup command and do not account for nonverbal user information such as emotional state or facial cues, limiting their ability to provide contextually appropriate responses.
Innovation Solution
The integration of oculesics data from smart contact lenses, which captures eye behavior and emotional states, is used to augment voice commands with command augmentation indicators, allowing the voice assistance system to generate aggregated commands that consider both verbal and nonverbal inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voice assistance systems only process verbal commands, then the system complexity remains low, but the contextual understanding and response accuracy deteriorate
Solution Approach 1:
The patent combines multiple input modalities (verbal commands, eye tracking data, facial expressions, physiological signals) into a unified command processing system. The data aggregator merges these diverse data sources to create a comprehensive contextual understanding, resolving the contradiction by integrating additional sensors and data streams while maintaining systematic organization through defined processing pipelines.
Solution Approach 2:
The voice assistance system is enhanced to perform multiple functions by incorporating oculesics data processing, emotional state detection, and contextual analysis capabilities alongside traditional voice command processing. This multi-functionality approach allows the system to maintain versatility while improving contextual understanding through diverse input channels.
2Speed
If the system waits for a verbal wakeup command, then the system activation is simple and reliable, but the response time and user interaction naturalness deteriorate
Solution Approach 1:
The system performs preliminary actions by continuously monitoring oculesics data and maintaining readiness states before verbal commands are issued. Eye tracking data is processed in advance to detect user intent, and the system prepares to execute commands based on pre-analyzed contextual information, reducing actual response time while maintaining reliable activation through staged processing.
3Loss of information
If the system processes only explicit verbal commands, then the processing accuracy is high, but the ability to infer user intent and emotional state deteriorates
Solution Approach 1:
The system implements feedback mechanisms by continuously analyzing oculesics data, emotional states, and contextual information to refine command interpretation. The data aggregator provides feedback loops that adjust command processing based on detected user intent, emotional context, and environmental factors, reducing information loss about user intent while managing processing complexity through iterative refinement.
Data Source
AI summary
An approach is provided in which the approach captures a voice command spoken by a user along with a set of data generated from a smart contact lens worn by the user. The approach matches the set of data to a command augmentation indicator that identifies an augmentation to the voice command. The approach aggregates the command augmentation indicator with the voice command into an aggregated command and executes the aggregated command accordingly.