WebRTC Presence Status Triggering for Addressed Participants
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Solution Overview
Problem
Existing webRTC-based communication and collaboration sessions face challenges in identifying the presence status of participants, especially in conferences with many participants or when using devices with small displays, leading to confusion and inconvenience when questions go unanswered due to participants being absent or muted.
Innovation Solution
A computer-implemented method and platform that utilizes AI speech recognition and machine learning to detect and present the presence status of participants through a feature activation mechanism, minimizing disruption by only displaying status when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If presence status is continuously displayed for all participants, then participant availability is always visible, but communication flow is disrupted and participants are distracted
Solution Approach 1:
The system performs preliminary detection of when presence information becomes necessary by monitoring speech content for references to participant names. This triggers the display only at the appropriate moment before the participant needs to respond, rather than continuously displaying all presence information.
Solution Approach 2:
The presence status display is activated periodically and temporarily only when a participant is referenced in speech, rather than being continuously active. The display appears for a limited duration (e.g., 5 seconds) and then disappears, creating a rhythmic, event-driven display pattern that minimizes distraction.
2Ease of operation
If presence status is displayed only when referenced, then communication flow is maintained, but presence information may be lost when needed
Solution Approach 1:
The system uses speech-to-text conversion and natural language processing to detect when a participant's name is mentioned in the conversation. This feedback mechanism triggers the appropriate display of presence status information, ensuring that the information is provided exactly when it becomes relevant to the communication.
Solution Approach 2:
The patent replaces manual monitoring of participant presence with automated speech recognition and text analysis systems. The AI-based speech-to-text conversion and natural language processing automatically detect participant references and trigger appropriate displays without requiring manual intervention.
3Measurement precision
If manual checking of participant list is required, then accurate presence information can be obtained, but time is lost and communication efficiency decreases
Solution Approach 1:
The system automatically monitors and tracks participant presence status without requiring users to manually check the participant list. The presence information is self-updated and automatically displayed when relevant, allowing participants to obtain accurate presence information instantly without interrupting the communication flow.
Solution Approach 2:
Manual checking of participant lists is replaced with automated speech-to-text conversion and natural language processing systems that continuously monitor the conversation and automatically retrieve and display presence status information when participant names are referenced.
4Loss of information
If presence monitoring feature is always active, then presence status is always available, but device resources are consumed and battery life is reduced
Solution Approach 1:
The presence monitoring and display feature is activated periodically only when triggered by speech content analysis, rather than running continuously. This event-driven approach significantly reduces processor usage and energy consumption while still providing presence information when it becomes relevant to the conversation.
Solution Approach 2:
The system uses preliminary speech-to-text conversion and natural language processing to detect potential triggers before activating the full presence display feature. This preliminary detection mechanism allows the system to remain in a low-power state until speech analysis indicates that presence information is needed.
Data Source
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AI summary
The present invention relates to a computer-implemented method of performing a webRTC-based communication and collaboration session with a plurality of predefined participants (7, 7', 7", 7"'), wherein each participant from the plurality of predefined participants (7, 7', 7", 7''') has a status of either being present of being absent or present but muted, wherein the method comprises a detection step of detecting that a participant from the plurality of predefined participants (7, 7', 7", 7"') is addressed by another participant from the plurality of predefined participants (7, 7', 7", 7''') for answering a question or for submitting a comment during the communication and collaboration session; a presence status verification step of verifying whether a presence status of the participant to answer the question or to submit a comment is required to be presented to the plurality of predefined participants (7, 7', 7", 7'''); and if it is verified that the presence status of the participant to answer the question or to submit a comment needs to be presented, a feature activation step of activating a feature for presenting presence information to the plurality of predefined participants (7, 7', 7", 7'''). Further, the present invention relates to a communication and collaboration platform for carrying out the computer-implemented method of performing a webRTC-based communication and collaboration session.