Audio Envelope RMS Power Double-Windowing Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current digital audio workstations (DAWs) face challenges in accurately evaluating loudness during transitions between signal and background noise, leading to underestimated loudness levels and artifacts such as higher signal levels, which affect the quality of audio processing and mixing.
Innovation Solution
The implementation of a double-windowing analysis method that discards low-loudness sub-windows and evaluates the RMS power or weighted mean of remaining sub-windows, providing a more accurate envelope evaluation and reducing artifacts during transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single-windowing analysis is used to evaluate loudness, then the processing is simple and fast, but the loudness evaluation accuracy deteriorates during transitions between signal and background noise
Solution Approach 1:
The audio signal is divided into multiple sub-windows within each analysis window, allowing the system to evaluate loudness at different temporal resolutions. This segmentation enables accurate detection of transitions between signal and background noise by examining individual sub-windows, while still providing comprehensive coverage through the larger window structure.
Solution Approach 2:
The patent introduces a hierarchical windowing structure with multiple levels (main windows containing sub-windows), adding a temporal dimension to the analysis. This multi-scale approach allows simultaneous evaluation of both short-term fluctuations (within sub-windows) and long-term trends (across main windows), resolving the contradiction between simplicity and accuracy.
2Reliability
If all sub-windows are included in loudness evaluation, then the evaluation covers the entire signal, but artifacts appear during transitions due to inclusion of low-loudness background noise sub-windows
Solution Approach 1:
The patent extracts and identifies sub-windows with loudness below a predetermined threshold, separating them from the main evaluation set. By taking out these low-loudness background noise sub-windows, the system prevents them from contributing to the overall loudness calculation, thereby eliminating the artifacts that would otherwise appear during transitions between signal and background noise.
Solution Approach 2:
The patent applies different evaluation criteria to different regions of the audio signal. Sub-windows above the threshold are evaluated with full weight, while those below the threshold are excluded or given reduced weight. This local differentiation ensures that high-quality signal portions contribute maximally to the evaluation while problematic background noise portions are minimized.
Data Source
AI summary
A method comprising determining an envelope of an audio file based on a double-windowing analysis of the audio file.