Three-Metric Audio Video Quality Diagnostic Model
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Solution Overview
Problem
Current objective quality measurement systems for packet-based audio and video applications provide only a single Mean Opinion Score (MOS) value, which does not offer insight into the specific factors affecting the quality of the transmitted signal, making it difficult to diagnose quality issues effectively.
Innovation Solution
A passive objective quality model that uses three diagnostic metrics (Q0, Q1, Q2) to quantify the quality of audio and video transmissions, measuring reductions in quality due to lossy media transmission, packet loss concealment, and long periods of silence or frozen video, respectively, providing detailed insights into the sources of quality problems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single MOS value is used to measure quality, then the measurement is simple and fast, but it does not provide insight into specific quality factors
Solution Approach 1:
The patent segments the single MOS quality metric into three distinct diagnostic components: Q0 (inherent signal quality), Q1 (packet loss impact), and Q2 (jitter/freeze impact). This segmentation allows each aspect of quality to be measured and analyzed separately, providing detailed insight into specific quality factors while maintaining the overall quality assessment framework.
2Loss of information
If three diagnostic metrics are used to measure quality, then insight into quality factors is provided, but the measurement system becomes more complex
Solution Approach 1:
The measurement system is segmented into three independent metric calculations (Q0, Q1, Q2), each focusing on a specific quality aspect. This segmentation provides detailed quality factor information while keeping each individual metric relatively simple to calculate and interpret.
Solution Approach 2:
The three-metric framework serves multiple functions simultaneously: it provides overall quality assessment, identifies specific quality degradation sources, and enables targeted remediation. This multi-functionality justifies the increased complexity by delivering comprehensive diagnostic capabilities.
3Measurement precision
If subjective testing is used to measure quality, then user perception is captured, but the testing takes a long time and is influenced by many factors
Solution Approach 1:
The patent replaces the mechanical human subjectivity assessment process with an automated objective measurement system that calculates Q0, Q1, and Q2 metrics based on signal analysis. This substitution maintains the ability to capture quality perception while dramatically increasing testing speed and eliminating human variability factors.
Solution Approach 2:
The system transforms subjective quality perception into objective measurable parameters (Q0, Q1, Q2 metrics) that can be automatically calculated from signal characteristics. This parameter transformation enables fast, repeatable measurements while preserving the essential quality assessment functionality.
Data Source
AI summary
Systems and methods are described for determining a set of three quality metrics for audio and/or video signals transmitted through a packet network. The set of three metrics provide more insight into which factors are affecting the quality of the received signal as perceived by the end-user. These three quality metrics measure reductions in quality due to lossy media transmission, packet loss concealment from packet loss and/or packet/frame jitter, and long periods of silence and/or frozen video. Because each metric quantifies a different aspect of transmitted quality, a deficiency in the transmitted signal can be identified by reference to the set.