Adaptive SMR Tuning for Audio Encoding Bitrate Stability
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Solution Overview
Problem
Existing audio encoding methods, such as Constant Bitrate (CBR) and Variable Bitrate (VBR), face challenges in maintaining quality and predictability, particularly in Average Bitrate (ABR) encoding, where post-processing requires numerous iterations to achieve a target bitrate, which is computationally intensive.
Innovation Solution
The method involves tuning the Signal to Mask Ratio (SMR) parameter within a perceptual model based on the encoded bitrate and target bitrate to compute a masking threshold for quantizing the signal, reducing the need for extensive post-processing by adjusting the SMR parameter every few frames, thereby stabilizing the bitrate and improving encoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If Variable Bitrate (VBR) encoding is used to respond to signal complexity and allocate more bits to complex passages, then audio quality is improved, but bitrate becomes unpredictable and receiver buffer management becomes difficult
Solution Approach 1:
The patent applies dynamics by making the bitrate adjustable and adaptive rather than fixed. The bitrate is dynamically controlled based on the difference between actual and target bitrates, allowing the system to respond to signal complexity while maintaining overall predictability through controlled variation around a target bitrate.
Solution Approach 2:
The patent changes the bitrate parameter dynamically based on signal complexity analysis. By adjusting the bitrate parameter in response to measured signal characteristics and comparing actual bitrate to target bitrate, the system achieves variable quality allocation while maintaining predictable average bitrate behavior.
2Manufacturing precision
If Average Bitrate (ABR) encoding is used to maintain target average bitrate with flexibility in bit allocation, then audio quality is improved compared to CBR, but numerous iterative post-processing adjustments are required which are computationally intensive
Solution Approach 1:
The patent applies preliminary action by performing signal complexity analysis and bitrate prediction before the main encoding process. By analyzing the signal in advance and predicting the bitrate requirements, the system prepares encoding parameters upfront, reducing the need for iterative post-processing adjustments and improving encoding efficiency.
Solution Approach 2:
The patent implements feedback by continuously monitoring the actual bitrate and comparing it to the target bitrate, then using this information to adjust encoding parameters. This feedback mechanism allows the system to converge to the target bitrate more quickly with fewer iterations, reducing computational intensity while maintaining audio quality.
3Reliability
If Constant Bitrate (CBR) encoding is used to match fixed bandwidth, then streaming reliability is improved, but audio quality suffers in complex passages due to limited bit allocation
Solution Approach 1:
The patent applies dynamics by transitioning from a static bitrate (CBR) to a dynamic bitrate that can adjust within bounds. The system maintains a target average bitrate suitable for fixed bandwidth streaming while allowing dynamic variation to allocate more bits to complex passages when available, improving audio quality without sacrificing streaming reliability.
Solution Approach 2:
The patent changes the bitrate parameter from a fixed constant to a variable that adjusts based on signal complexity. By modifying the bitrate parameter dynamically while maintaining an average target suitable for fixed bandwidth, the system achieves both streaming reliability and improved audio quality in complex passages.
Data Source
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AI summary
Methods of encoding a signal using a perceptual model are described in which a signal to mask ratio parameter within the perceptual model is tuned. The signal to mask ratio parameter is tuned based ona function ofthe bitrate of the part of the signal which has already been encoded and the target bitrate for the encoding process.The tuned signal to 5 mask ratio parameter is used to compute a masking threshold for the signal which is then used to quantise the signal.