Audio Parameter Dequantization for Low-Bitrate Stereo Decoding
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Solution Overview
Problem
Existing audio coding systems face challenges in minimizing bit stream information while maintaining audio quality, as high compression leads to poor sound quality due to complex calculations or lost information, and low compression results in capacity issues.
Innovation Solution
The implementation of a non-uniform scalar quantization scheme for audio parameters in parametric stereo coding, where smaller step-sizes are used for ranges of high human sound perception sensitivity and larger step-sizes for less sensitive ranges, along with a scaling function to adjust quantization based on perceived sound characteristics, reducing average bit consumption without degrading sound quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If uniform quantization with fixed step-sizes is used, then the quantization process is simple and fast, but audio quality deteriorates in perceptually sensitive regions
Solution Approach 1:
The patent applies dynamics by making the quantization step-sizes adaptive rather than fixed. The step-sizes are scaled based on the local signal characteristics (energy and perceptual importance), allowing the quantizer to dynamically adjust its precision to match the perceptual requirements of different audio regions.
Solution Approach 2:
The patent changes the parameter of quantization step-size from a fixed value to a variable that depends on signal energy and perceptual importance. This is achieved through scaling functions that modify the step-sizes according to local signal conditions, optimizing the trade-off between bit-rate and perceived quality.
2Productivity
If high compression is applied to minimize bit stream information, then transmission efficiency improves, but audio quality becomes unacceptable due to lost information
Solution Approach 1:
The patent applies local quality by differentiating the quantization precision across different regions of the audio signal. Perceptually important regions (such as those with low energy or high masking threshold) receive finer quantization, while less important regions use coarser quantization. This ensures that bit-rate is allocated efficiently according to perceptual needs.
Solution Approach 2:
The patent modifies the quantization parameters (step-sizes) based on local signal characteristics including energy and perceptual importance. Scaling functions adjust these parameters dynamically, allowing the system to achieve high compression ratios while preserving audio quality in perceptually critical regions.
3Manufacturing precision
If low compression is applied to maintain audio quality, then sound quality is preserved, but bit stream capacity problems occur
Solution Approach 1:
The patent optimizes the quantization parameters to achieve the minimum necessary bit-rate for acceptable quality. By using scaling functions that adapt step-sizes to local signal characteristics, the system avoids unnecessary bits in imperceptible regions while maintaining quality where needed.
Solution Approach 2:
The patent applies partial action by using fine quantization only where perceptually necessary and coarser quantization elsewhere. This selective approach to quantization precision reduces the overall bit-rate requirement while maintaining acceptable audio quality across the entire signal.
4Quantity of substance
If perceptually optimized non-uniform quantization is used, then bit consumption is reduced, but quantization complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-computing scaling functions based on signal characteristics such as energy and perceptual importance. These scaling functions are prepared in advance and then applied during quantization, avoiding the need for complex real-time calculations and simplifying the actual quantization process.
Solution Approach 2:
The patent introduces scaling functions as intermediary elements between the uniform quantizer and the perceptual model. These scaling functions translate perceptual requirements into adjusted step-sizes, allowing the use of simple uniform quantization hardware while achieving perceptually optimized results.
Data Source
AI summary
The present disclosure provides methods, devices and computer program products for non-uniform quantization of parameters. The disclosure further relates to a method and apparatus for reconstructing an audio object in an audio decoding system taking the non-uniformly quantized parameters into account. According to the disclosure, such an approach renders it possible to reduce bit consumption without substantially reducing the quality of the reconstructed audio object.