Contextual Device Pairing via Audio Analysis
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Solution Overview
Problem
Existing device pairing technologies, such as Bluetooth and NFC, are inadequate for automatically identifying and pairing user devices in group settings where not all co-located users are interested in pairing or within close proximity, limiting efficient content sharing among group members.
Innovation Solution
A method and system that performs contextual analysis of discussions using natural language processing and voice recognition to identify topics and users interested in sharing content, creating a communication group and initiating device pairing between user devices for seamless content sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional device pairing technologies (Bluetooth, NFC) are used, then devices can establish direct communication links, but manual device selection and close proximity are required, reducing ease of operation in group settings
Solution Approach 1:
The system performs automatic device pairing without user intervention by analyzing audio streams from discussions, identifying users and devices contextually, and initiating pairing processes autonomously based on conversation content and participant identification
Solution Approach 2:
The patent replaces manual mechanical pairing actions (touching devices for NFC, selecting devices for Bluetooth) with acoustic field-based identification through audio stream analysis and voice recognition to automatically determine which devices should be paired
2Productivity
If device pairing is performed manually, then user control is maintained, but time is lost in device selection and pairing initiation
Solution Approach 1:
The system performs preliminary identification of users and devices through audio stream analysis and voice recognition before the pairing is actually needed, so that when content sharing is desired, the devices are already identified and ready for immediate pairing
Solution Approach 2:
The system autonomously monitors discussion audio streams, identifies when content sharing is desired through contextual analysis, and automatically initiates pairing without requiring users to spend time manually selecting and pairing devices
3Ease of operation
If all co-located users are paired automatically, then content sharing is simplified, but unwanted pairings occur with users not interested in sharing
Solution Approach 1:
The system applies different pairing actions to different devices based on local contextual analysis of the audio stream, identifying specific users who express interest in content sharing and pairing only those devices while leaving others unpaired
Solution Approach 2:
The system continuously analyzes audio stream feedback from discussions to determine user interest in content sharing, adjusting pairing decisions based on real-time conversation content and participant responses
Data Source
AI summary
Pairing user devices includes receiving an indication of a group of co-located users, receiving information indicative of a topic of conversation of a subgroup of the co-located users, and determining a topic of the discussion using contextual analysis. One or more users of the subgroup of co-located users are identified. Each of the one or more users has a user device associated therewith. The one or more users is added to a communication group associated with the topic. A subset of the user devices for a pairing between the user devices are determined. The pairing between the subset of the user devices is initiated.