Time-Frequency Post-Processing for Audio Signal Quality
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Solution Overview
Problem
Audio/speech compression at low bit rates often results in quality degradation due to the loss of finer details, particularly in high frequency bands, where current technologies like SBR rely on coarser coding schemes and noise addition, leading to perceptual quality issues.
Innovation Solution
Implementing time/frequency two-dimensional post-processing, which estimates energy arrays and applies modification factors to filter bank coefficients, enhancing energy distribution in both time and frequency directions to improve perceptual quality without significant increases in bit rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If speech/audio compression is applied to reduce bit rate, then bandwidth is reduced, but quality degradation occurs
Solution Approach 1:
The patent applies filter bank technology to segment the audio signal into multiple frequency subbands. This segmentation allows different coding strategies to be applied to different frequency regions, preserving important high-frequency components while maintaining overall compression efficiency. The filter bank divides the spectrum into bands, enabling selective processing that improves perceived quality at low bit rates.
Solution Approach 2:
The patent implements Spectral Band Replication (SBR) which applies different coding precision to different frequency bands. High-frequency bands that are perceptually important receive enhanced treatment through replication from low-frequency bands, while less critical bands use coarser coding. This local quality approach ensures that perceptually significant regions maintain high fidelity even at low overall bit rates.
2Quantity of substance
If coarser coding scheme is used for high frequency bands, then bit rate is reduced, but perceptual quality deteriorates
Solution Approach 1:
The patent employs Spectral Band Replication (SBR) which copies spectral information from low-frequency bands to reconstruct high-frequency bands. The low-frequency band signal is encoded with high precision, and the high-frequency components are generated by replicating and shaping this information. This copying mechanism allows high-frequency content to be recovered at very low bit rates while maintaining perceptual quality.
Solution Approach 2:
The patent uses parameter-based control to manage the replication process. Side information about the spectral envelope and replication parameters is transmitted from encoder to decoder, allowing the high-frequency reconstruction to adapt to the actual signal characteristics. This parameter change approach enables flexible control of the coding quality versus bit rate trade-off.
3Manufacturing precision
If SBR technology is applied with noise addition, then high frequency content is restored, but distortion is introduced in low energy areas
Solution Approach 1:
The patent applies dynamic post-processing that adapts to the local signal characteristics in the time-frequency domain. The processing gain is adjusted based on the estimated signal energy and spectral properties, allowing the system to apply stronger enhancement where needed and weaker processing where the signal is already clean. This dynamic adaptation prevents excessive processing of low-energy regions that would introduce unnecessary distortion.
Solution Approach 2:
The patent implements a feedback mechanism where the decoded signal characteristics are analyzed and used to control the post-processing intensity. The system estimates the signal energy and spectral envelope, then uses this information to adjust the processing gain applied during SBR reconstruction. This feedback loop ensures that processing is optimized for each signal segment, minimizing distortion while maximizing quality improvement.
Data Source
AI summary
In accordance with an embodiment, a time-frequency post-processing method of improving perceptual quality of a decoded audio signal, the method includes determining a time-frequency representation (such as filter bank analysis and synthesis) of an audio signal, estimating a time-frequency energy distribution of an audio signal from a time-frequency filter bank, computing a modification gain for each time-frequency representation point to have a modified time-frequency representation, and outputting audio signal from a modified time-frequency representation.