Hot Word-Free Assistant Adaptation With Personalized Intent Detection
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Solution Overview
Problem
Existing automated assistants often require explicit invocation through hot words or phrases, which can be awkward and inefficient, leading to false positives and negatives that waste resources and erode user confidence.
Innovation Solution
Adapt automated assistant functions based on vision data analysis, determining user intent without hot words, using personalized parameters for each user to mitigate false positives and negatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hot word free adaptation is implemented using vision data analysis, then user input duration is reduced and interaction efficiency is improved, but false positives and false negatives increase leading to resource waste and reduced reliability
Solution Approach 1:
The system dynamically adjusts detection parameters (gaze duration threshold, mouth movement sensitivity, confidence thresholds) based on user-specific characteristics and contextual factors. This allows the system to adapt its sensitivity to balance between reducing false positives and minimizing false negatives, thereby maintaining reliability while improving interaction efficiency.
Solution Approach 2:
The system incorporates feedback mechanisms where detection results and user responses are used to continuously refine the vision data analysis parameters. By analyzing patterns from previous interactions and adjusting detection thresholds accordingly, the system learns to reduce false positives while maintaining high detection accuracy for genuine user intent.
2Measurement precision
If personalized parameters are used for each user to mitigate false positives and negatives, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring user profiles with default personalized parameters during initial setup or enrollment phases. By establishing baseline parameters in advance based on user characteristics, the system reduces the complexity of real-time parameter management while maintaining high detection accuracy through user-specific configurations.
Solution Approach 2:
The system implements a universal parameter management framework that handles multiple user profiles and parameter types through a unified architecture. This multi-functional approach allows the same system components to manage diverse personalized parameters across different users, reducing overall system complexity while maintaining measurement precision.
Data Source
AI summary
Hot word free adaptation, of one or more function(s) of an automated assistant, responsive to determining, based on gaze measure(s) and/or active speech measure(s), that a user is engaging with the automated assistant. Implementations relate to various techniques for mitigating false positive occurrences of and/or false negative occurrences, of hot word free adaptation, through utilization of personalized parameter(s) for at least some user(s) of an assistant device. The personalized parameter(s) are utilized in determining whether condition(s) are satisfied, where those condition(s), if satisfied, indicate that the user is engaging in hot word free interaction with the automated assistant and result in adaptation of function(s) of the automated assistant.