Conference Speech Pattern Analysis for Interruption Management
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Solution Overview
Problem
Existing videoconferencing systems fail to analyze speech patterns to distinguish between a user pausing during speech and terminating speech, leading to interruptions and frustration among participants, and lack features that intelligently manage interruptions based on speech content.
Innovation Solution
Implementing speech pattern analysis to identify unique patterns for each user, distinguishing between affirmative and negative interjections, and activating/deactivating conferencing features like mute or highlight based on these patterns to manage interruptions effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If user-activated mute features are provided without speech pattern analysis, then system simplicity is maintained, but interruption management effectiveness deteriorates
Solution Approach 1:
The system automatically analyzes speech patterns and activates/deactivates conferencing features without requiring user activation. The speech processing system independently determines when users are pausing versus terminating speech, and automatically manages mute and highlight features based on this analysis, eliminating the need for manual user intervention.
Solution Approach 2:
The patent replaces manual user activation of mute features with an automated speech recognition system that analyzes speech patterns, identifies pauses versus terminations, and automatically controls conferencing features. This substitutes the mechanical user-action-based system with an intelligent automated system that processes speech content and patterns.
2Reliability
If speech pattern analysis is implemented to distinguish pauses from speech termination, then interruption management improves, but system complexity increases
Solution Approach 1:
The speech processing system independently performs speech pattern analysis, identifies unique speech patterns for each user, distinguishes between pauses and speech terminations, and automatically manages conferencing features without requiring external intervention or complex manual control mechanisms.
Solution Approach 2:
The system continuously analyzes speech patterns in real-time, uses this feedback to determine whether a user is pausing or terminating speech, and dynamically adjusts conferencing feature activation accordingly. This closed-loop feedback mechanism enables intelligent automatic management of interruptions based on actual speech behavior.
3Productivity
If conferencing features are automatically activated based on speech patterns, then participant engagement improves, but processing requirements increase
Solution Approach 1:
The system focuses speech pattern analysis on critical moments when speech termination or pausing is detected, rather than continuously analyzing all speech content. By applying speech pattern recognition selectively at decision points and using pre-established unique speech patterns for each user, the system achieves effective participant engagement management while minimizing unnecessary processing overhead.
Data Source
AI summary
Methods, systems, and apparatus are described herein for enhanced conferencing. A computing device monitor user participation. One or more conference features may be activated or deactivated based on speech patterns of conference participants.