Context-Aware Conference Call Disconnection After Silence Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing telecommunication systems struggle to accurately and efficiently terminate calls, particularly in complex scenarios like large conference calls or presentations, leading to inefficient resource allocation and consumption, which affects productivity and system performance.
Innovation Solution
A method and apparatus that utilize a network element to monitor silence thresholds, analyze call transcriptions, metadata, and sound patterns to determine call termination, employing a Random Forest model for decision-making, and release resources accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If silence detection is used to terminate calls, then resource allocation efficiency is improved, but call termination accuracy deteriorates in complex scenarios like conference calls or presentations
Solution Approach 1:
The patent segments the call termination detection process into multiple independent analysis components: silence detection, transcription analysis, metadata analysis, and sound pattern analysis. Each component operates independently and contributes to the overall termination decision, allowing the system to handle complex scenarios accurately while maintaining resource efficiency.
Solution Approach 2:
The system implements feedback mechanisms where analysis results from transcription, metadata, and sound patterns are continuously evaluated to determine whether to terminate the call. This multi-layered feedback approach ensures accurate termination decisions by cross-validating multiple data sources before releasing resources.
2Measurement precision
If multiple analysis methods are used to improve call termination accuracy, then processing complexity increases
Solution Approach 1:
The patent divides the complex analysis process into separate modular components: silence detection module, transcription analysis module, metadata analysis module, and sound pattern analysis module. This segmentation reduces processing complexity by allowing each module to operate independently and be managed separately.
Solution Approach 2:
The system performs analysis at different levels of depth based on the situation. For example, silence detection provides a quick initial assessment, while transcription and metadata analysis provide deeper contextual understanding when needed. This partial action approach balances accuracy requirements with processing complexity.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A telecommunication apparatus and method can be configured to facilitate disconnection for conference calls. Embodiments can include the monitoring of an ongoing call (e.g. conference call or other type of call involving multiple parties), detecting a possible termination of the call based on a period of silence during the call for triggering an analysis of at least a portion of the call and evaluating the analysis results to determine whether the call is to be terminated or not. In the event termination occurs, resources can be unassigned to the call to free up resources. In the event it is determined that the call is not yet terminated, monitoring of the call can resume. In some embodiments, the conducted analysis can involve analyzing context specific aspects of the call (e.g. at least a portion of a transcript of the call, metadata related to the call, sound patterns, etc.).