Multi-Stage Scalefactor Estimation for Audio Encoder Bottlenecks
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Solution Overview
Problem
Current approaches for selecting scalefactors in adaptive quantization for audio encoders are computationally complex and processor cycle intensive, affecting the efficiency of audio compression and quality.
Innovation Solution
A multi-stage approach for estimating scalefactors, involving distortion level estimation, interim process value generation, and scalefactor calculation based on statistically predetermined fractions, to optimize bit allocation and reduce distortion in audio signal encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If current approaches for selecting scalefactor are used, then audio quality and compression are improved, but computational complexity and processor cycle usage increase
Solution Approach 1:
The patent segments the scalefactor selection process into multiple stages: a first stage that performs coarse scalefactor selection and a second stage that refines the selection. This segmentation allows the system to achieve accurate audio quality results while reducing overall computational complexity by dividing the complex problem into manageable parts with different computational requirements.
Solution Approach 2:
The patent applies preliminary action by performing initial scalefactor estimation in the first stage before finalizing the scalefactor in the second stage. This preliminary estimation provides a good starting point that reduces the search space and computational effort required in the subsequent refinement stage, thereby reducing overall computational complexity while maintaining audio quality.
2Manufacturing precision
If current approaches for selecting scalefactor are used, then audio quality and compression are improved, but processor cycle intensity increases
Solution Approach 1:
By segmenting the scalefactor selection into two stages with different computational intensities, the patent reduces peak processor cycle usage. The first stage uses simpler computations to establish a baseline, while the second stage performs more intensive refinement only where needed, thereby improving audio quality while reducing overall processor cycle intensity and power consumption.
Solution Approach 2:
The patent applies partial action by performing full refinement only for certain scalefactor bands rather than all bands. The multi-stage approach allows the system to apply computationally intensive refinement selectively where it provides the most benefit, rather than uniformly across all frequency bands, thus reducing total processor cycle intensity while maintaining audio quality.
Data Source
AI summary
An efficient approach for estimating scalefactors for use in the quantization of audio signal spectrum values is described. The scalefactor estimation approach can be implemented in multiple stages. A first stage estimates a distortion level for a selected scalefactor band spectrum value based on a received maximum tolerant distortion threshold and the spectrum values in the scalefactor band. A second stage determines an interim process value based on the previously estimated distortion level and generates a scalefactor for a selected scalefactor band spectrum value based on the generated interim process value and a statistically predetermined fraction. A third stage generates a scalefactor that applies to the whole scalefactor band based on the scalefactor generated for the selected scalefactor band spectrum value. The approach provides a performance gain of 40% over previous techniques, thereby reducing device power requirements and audio encoder bottlenecks.