Context-Aware Notification Triggering via Voice Co-Presence Detection
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Solution Overview
Problem
Existing notification systems on electronic devices rely on date and time-based triggers, which can lead to overwhelming reminders and inefficient resource usage, as they do not account for the user's co-presence with other individuals.
Innovation Solution
A method and apparatus that determine co-presence using audible sounds captured by a mobile device, allowing notifications to be triggered based on the presence of specific individuals, utilizing voice recognition and location data to invoke appropriate actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If date and time-based triggers are used for notifications, then notifications can be delivered at scheduled times, but users may be overwhelmed with reminders and device resources are consumed inefficiently
Solution Approach 1:
The system continuously monitors audio input to detect the presence of specific individuals, using this feedback to dynamically trigger or suppress notifications. This real-time feedback mechanism allows the system to adapt notification delivery based on actual user context rather than relying solely on pre-scheduled time-based triggers, thereby reducing wasted resource consumption on unnecessary repeated notifications.
2Reliability
If notifications are sent at scheduled times regardless of user context, then reminder delivery is simple and reliable, but users may not be in a position to address the reminders
Solution Approach 1:
The system changes the triggering parameter for notifications from purely time-based to context-based, specifically detecting the audio presence of designated individuals. This parameter change allows the system to determine the appropriate moment to deliver reminders, ensuring users are actually present and able to address them, thereby improving both reliability and ease of operation.
3Loss of information
If reminders are presented multiple times due to inappropriate timing, then users may eventually notice the reminder, but more device resources and network communication resources are consumed
Solution Approach 1:
The system performs preliminary audio analysis to detect the presence of specific individuals before triggering notifications. By taking this preliminary action to assess user context, the system可以避免 delivering notifications at inappropriate times, thereby preventing the need for repeated notifications and reducing overall device and network resource consumption.
4Adaptability or versatility
If co-presence detection using audio samples is implemented, then notifications can be triggered based on actual user context, but the device complexity increases
Solution Approach 1:
The system uses audio samples as an intermediary to detect the presence of specific individuals. Rather than implementing complex direct identification systems, the patent leverages existing audio capture and comparison capabilities to determine co-presence, thereby achieving context-aware notification triggering while minimizing the increase in device complexity.
Data Source
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AI summary
Methods, apparatus and computer-readable media (transitory and non-transitory) are disclosed for receiving audio information based on sensing of one or more audible sounds; identifying one or more voice profiles, wherein each of the voice profiles is associated with an individual and indicates one or more voice characteristics of the associated individual; determining at least a given voice profile of the one or more voice profiles matches the audio information; determining co-presence of the user with at least the individual associated with the given voice profile based on determining the given voice profile matches the audio information; identifying an action that includes a trigger based on co-presence of the user and the individual associated with the given voice profile; and invoking the action based on the determined co-presence of the user with at least the individual associated with the given voice profile.