Audio Channel Time Alignment Verification Using RMS Metrics
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Solution Overview
Problem
As the number of audio channels increases and loudspeaker layouts transition from 2D to 3D, audio data synchronization becomes increasingly complex, particularly in broadcast networks, leading to challenges in time alignment and data transmission between media processing nodes.
Innovation Solution
A method involving the reception of audio data blocks with metadata, where reference audio samples are used to determine synchronization by comparing values corresponding to audio samples, utilizing metrics such as root mean square (RMS) and loudness, to ensure alignment between audio channels and metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of audio channels increases from 2D to 3D layout, then audio reproduction quality is improved, but time alignment complexity increases
Solution Approach 1:
The patent segments the time alignment verification process into multiple independent components: extracting reference audio samples from metadata, computing audio metrics (RMS, zero-crossing rate, peak detection) for both reference and current blocks, and comparing these metrics to determine synchronization status. This segmentation allows complex 3D audio alignment to be broken down into manageable computational steps for each channel and time block.
Solution Approach 2:
The patent introduces audio metrics (RMS, zero-crossing rate, peak detection) as intermediary parameters that mediate between the raw audio signals and the synchronization determination. These metrics serve as intermediaries to compare reference and current audio blocks without requiring direct complex signal processing, simplifying the verification of time alignment across multiple channels.
2Productivity
If audio data is transmitted between media processing nodes in broadcast networks, then audio distribution is enabled, but synchronization issues arise
Solution Approach 1:
The patent performs preliminary extraction of reference audio samples from metadata before transmission, and pre-computation of audio metrics for both reference and current audio blocks. This preliminary action enables the receiving node to verify synchronization status without requiring complex real-time processing during transmission, maintaining reliability while enabling efficient audio distribution.
Solution Approach 2:
The patent implements a feedback mechanism where the receiving node compares audio metrics from current audio blocks against reference samples to determine synchronization status. This feedback loop allows continuous monitoring and verification of time alignment during transmission, enabling the system to detect and correct synchronization drift in broadcast networks.
3Ease of operation
If metadata is associated with audio data blocks, then audio processing control is improved, but data processing complexity increases
Solution Approach 1:
The patent extracts only the necessary reference audio samples from the metadata associated with audio data blocks, rather than processing the entire metadata structure. This extraction approach maintains the control benefits of metadata association while reducing processing complexity by focusing only on the critical synchronization information needed for time alignment verification.
Data Source
AI summary
Some methods may involve receiving a block of audio data, the block including N pulse code modulated (PCM) audio channels, including audio samples for each of the N channels, receiving metadata associated with the block of audio data and receiving a first set of values corresponding to reference audio samples. A second set of values, corresponding to audio samples from the block of audio data, may be determined. The first and second set of values may be compared. Based on the comparison, it may be determined whether the block of audio data is synchronized with the metadata.