Audio Quality Feedback Analysis for Live Transmission Sessions
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Solution Overview
Problem
During teleconferencing, participants often experience poor audio quality due to various issues such as bad transmission, reception, or speaker positioning, which can disrupt meetings and require time-consuming troubleshooting.
Innovation Solution
A computer-implemented method and system that analyzes audio quality feedback from multiple audience devices, classifying common factors affecting audio quality and providing dynamic feedback to both audience devices and the source device to identify and address issues in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If audio quality feedback analysis is implemented across multiple audience devices, then audio quality issues can be identified and resolved, but system complexity and processing requirements increase
Solution Approach 1:
The system segments audience devices into subsets based on common factors (device type, network connection, location, audio configuration) and analyzes audio quality feedback within each subset separately. This segmentation allows the system to identify specific causes of audio quality issues without requiring complex analysis of all devices simultaneously, thereby maintaining reliability while managing system complexity.
Solution Approach 2:
The server acts as an intermediary that collects audio quality feedback from multiple audience devices, performs centralized analysis by comparing feedback across device subsets, and generates diagnostic information. This intermediary approach consolidates complex processing at the server level while keeping individual audience devices simple, resolving the contradiction between comprehensive analysis and system complexity.
2Loss of time
If real-time audio quality feedback is provided to all audience devices, then audio issues can be quickly addressed, but network bandwidth and processing resources are consumed
Solution Approach 1:
The system provides targeted audio quality feedback only to audience devices that exhibit specific quality issues or represent particular device subsets with common problems. Rather than sending feedback to all devices uniformly, the system identifies which devices need attention based on their audio quality metrics and common factor classifications, reducing unnecessary network traffic while maintaining quick response times for affected devices.
Solution Approach 2:
The system performs partial analysis by focusing on representative subsets of devices rather than analyzing every single device in real-time. By selecting subsets based on common factors and analyzing these subsets, the system achieves sufficient audio quality monitoring with reduced processing and network resource consumption, while still enabling timely issue resolution.
3Measurement precision
If detailed audio signal parameter data is collected from all audience devices, then comprehensive audio quality analysis is achieved, but data processing load and privacy concerns increase
Solution Approach 1:
The system extracts only the essential audio quality metrics and device configuration parameters needed for diagnosis, rather than collecting and processing complete raw audio signals from all devices. By extracting specific measurable parameters (audio quality scores, device type, network connection type, audio configuration settings), the system achieves sufficient measurement precision while significantly reducing data processing overhead and privacy concerns.
Solution Approach 2:
The system performs preliminary classification of audience devices into subsets based on common factors before conducting detailed audio quality analysis. This preliminary action organizes devices by device type, network connection, location, or audio configuration, allowing subsequent analysis to focus on specific subsets with similar characteristics. This approach reduces overall data processing requirements while maintaining comprehensive coverage of audio quality issues across different device categories.
Data Source
AI summary
Method and system are provided for audio quality feedback during live transmission from a source that is received at multiple audience devices. The method carried out at a server includes: obtaining audio information of an audio signal as received by at least some of the audience devices in a transmission session; classifying one or more subsets of the audience devices by one or more common factors per subset; and analyzing the obtained audio information from the audience devices in conjunction with the classifications of the subsets of the audience devices to determine one or more common factors that affect received audio quality at an identified subset of the audience devices classified by the one or more common factors. The method provides feedback of the one or more common factors to at least one of the audience devices in the identified subset or to the source device, or to both.