DRC Gain Spline Encoding With Fewer Nodes and Lower Error
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Solution Overview
Problem
Current methods for encoding Dynamic Range Control (DRC) gain values into spline representations for audio signals face challenges in minimizing bitrate and approximation error, with brute-force approaches being excessively complex due to the vast number of possible combinations of spline nodes.
Innovation Solution
A heuristic method is introduced that optimizes spline node placement and slope steepness to reduce the number of nodes while maintaining accurate representation, involving strategies such as removing redundant nodes, adjusting slope steepness, and inserting nodes to minimize approximation errors, thereby reducing bitrate and avoiding overshoots.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the number of spline nodes is reduced to minimize bitrate, then the amount of data transmitted decreases, but the approximation error between reference gain and interpolation values increases
Solution Approach 1:
The patent changes parameters such as node positions, gain values, and slope steepness to optimize the spline representation. By adjusting these parameters strategically, the system achieves accurate gain curve representation with fewer nodes, thereby reducing bitrate while maintaining approximation precision.
Solution Approach 2:
The patent performs preliminary smoothing of DRC gain values to eliminate fast gain changes before encoding. This preprocessing step reduces the complexity of the gain curve, allowing for fewer spline nodes to accurately represent the smoothed curve, thus reducing bitrate without significantly increasing approximation error.
2Measurement precision
If a brute-force method is used to evaluate all possible combinations of DRC spline nodes, then the best configuration can be found, but the computational complexity becomes extremely high
Solution Approach 1:
The patent segments the DRC gain curve into multiple sections and processes each section independently to place spline nodes. This segmentation approach divides the complex optimization problem into smaller, more manageable sub-problems, reducing computational complexity while still achieving good optimization results.
Solution Approach 2:
Instead of evaluating all possible combinations (excessive action), the patent uses a heuristic method that evaluates only a selected subset of candidate node configurations (partial action). This approach achieves satisfactory optimization results with significantly reduced computational complexity compared to exhaustive search.
3Loss of energy
If spline nodes are removed to reduce bitrate, then the number of nodes decreases, but overshoots may occur in the interpolated gain curve
Solution Approach 1:
The patent incorporates feedback mechanisms to detect and correct overshoots in the interpolated gain curve. By monitoring the interpolated values and comparing them against expected ranges, the system can identify overshoots and adjust node placements or slope values to eliminate them, maintaining gain curve accuracy while using fewer nodes.
Solution Approach 2:
The patent applies preliminary anti-action by setting slope steepness constraints and adjusting node placements in advance to prevent overshoots before they occur. This proactive approach modifies the spline construction process to inherently avoid overshoot conditions, ensuring reliable gain curve representation with reduced node density.
Data Source
AI summary
A system and method is provided for converting Dynamic Range Control/Compression (DRC) gain values into a spline representation that is compatible with the current standards. The system and method may: 1) minimize the bitrate for encoding and/or 2) minimize the approximation error between reference gain and interpolation values. A strategy for bitrate minimization may be the reduction of the number of spline nodes since gain and slope information must be transmitted for each node. Accordingly, an efficient heuristics based approach is provided that reduces the number of spline nodes needed to represent a series of DRC gain values using interpolation while accounting for overshoots and other inaccuracies.