Audio DRC Inversion for Unknown Compression Parameter Recovery
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Solution Overview
Problem
Current dynamic range control (DRC) technologies face challenges in accurately reproducing the behavior of unknown DRC models and reversing over-compression in audio signals, particularly in scenarios where access to the original DRC model is limited, leading to degraded audio quality and the inability to effectively declip or delimit signals.
Innovation Solution
A method is developed to determine DRC parameters for a known DRC model by feeding an audio signal through a second DRC model, selecting pairs of samples in the logarithmic domain, and adjusting parameters to approximate the behavior of the unknown model, allowing for the reproduction of the original signal's dynamic range and reversing compression effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If DRC parameters are determined using heuristic and analytic techniques without access to original metadata, then the ability to reproduce unknown DRC model behavior is improved, but the accuracy of parameter determination deteriorates due to lack of ground truth information
Solution Approach 1:
The patent uses an intermediary signal processing approach by analyzing the relationship between input and output signals of the unknown DRC model. Instead of directly accessing the original metadata, the system uses the observable signal transformations to infer DRC parameters through heuristic and analytic techniques, acting as a mediator between the compressed signal and the original dynamic range characteristics
Solution Approach 2:
The system determines DRC parameters by analyzing changes in signal characteristics before and after compression. By examining how the unknown DRC model transforms input signals into output signals, the system infers parameters such as compression ratio, threshold, and make-up gain through parameter change analysis rather than direct metadata access
2Productivity
If multiple compressors are applied to audio content, then the dynamic range is reduced to fit playback devices, but the audio recording quality deteriorates due to heavy compression and artifacts
Solution Approach 1:
The patent applies inversion by reversing the compression process. Instead of continuing to compress the already compressed signal, the system inverts the DRC operation to restore the original dynamic range. This is achieved by determining the compression parameters and applying the inverse transformation to expand the dynamic range back to its original state
Solution Approach 2:
The system discards the harmful compression artifacts by inverting the compression process. By determining the original DRC parameters and applying the inverse operation, the system recovers the original audio signal characteristics, effectively discarding the degradation caused by heavy compression while maintaining the benefits of dynamic range control
3Measurement precision
If DRC parameters are determined by feeding audio signal through a second DRC model and selecting sample pairs, then the determination process becomes more accurate, but the computational complexity increases
Solution Approach 1:
The patent segments the parameter determination process into distinct phases: feeding the audio signal through a second DRC model, selecting specific pairs of samples from the input and output signals, and determining parameters based on these selected pairs. This segmentation allows for more accurate parameter determination by focusing computational resources on critical sample pairs rather than processing all samples uniformly
Solution Approach 2:
The system applies partial action by selecting only the most informative sample pairs for parameter determination rather than using all available samples. This selective approach maintains high accuracy while reducing computational complexity, as only a subset of samples that provide the most critical information for parameter estimation is processed
Data Source
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AI summary
The present disclosure relates to a method of determining parameters for use by a first dynamic range control, DRC, model. The method comprises feeding a first audio signal to a second DRC model and receiving a second audio signal from the second DRC model, the second audio signal being a dynamic range controlled version of the first audio signal, rule-based selecting one or more pairs of samples of the first audio signal and corresponding samples of the second audio signal, and determining parameters of a first set of parameters among the parameters for use by the first DRC model based on the one or more selected pairs of samples. The present disclosure further relates to a method of reversing DRC of a dynamic range controlled audio signal and to a method of declipping a clipped audio signal that has been clipped by a DRC model. The present disclosure yet further relates to corresponding apparatus and computer-readable media.