Perceptual Spatial Audio Quantization for Bitrate-Quality Balance
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Solution Overview
Problem
Existing parametric stereo coding methods face challenges in balancing bit stream compression and audio quality, as high compression leads to unacceptable sound quality due to information loss, while low compression results in capacity issues.
Innovation Solution
The proposed method employs non-uniform scalar quantization schemes for audio parameters, using smaller step-sizes where human sound perception is most sensitive and larger step-sizes where it is less sensitive, and applies a scaling function to adjust quantization based on perceived sensitivity, reducing average bit consumption without compromising sound quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If high compression is applied to the bit stream, then bit stream capacity is improved, but audio quality deteriorates due to information loss
Solution Approach 1:
The patent applies different quantization step-sizes to different parameter ranges based on perceptual sensitivity. Critical parameters (like those affecting spatial positioning) use smaller step-sizes to preserve quality, while less critical parameters use larger step-sizes to reduce bit consumption. This local differentiation resolves the contradiction by optimizing both compression and quality in their respective domains.
Solution Approach 2:
The patent changes the quantization parameters (step-sizes) based on the specific parameter being encoded and its perceptual importance. By dynamically adjusting these parameters rather than using fixed uniform quantization, the system achieves better rate-distortion performance, allowing higher compression while maintaining acceptable audio quality.
2Loss of information
If low compression is applied to the bit stream, then audio quality is maintained, but bit stream capacity deteriorates
Solution Approach 1:
By applying finer quantization only where perceptually necessary and coarser quantization elsewhere, the system maintains audio quality in critical regions while reducing overall bit consumption, thus improving capacity without sacrificing perceived quality.
Solution Approach 2:
The patent applies full precision quantization only partially - specifically to parameters and ranges where human perception is most sensitive. For other parameters and ranges, reduced precision is sufficient, avoiding excessive bit consumption while maintaining acceptable quality.
3Device complexity
If uniform quantization is used for all parameters, then device complexity is reduced, but measurement precision deteriorates in perceptually sensitive ranges
Solution Approach 1:
The patent implements non-uniform quantization where the step-size varies according to the parameter value and perceptual sensitivity. This creates local precision optimization - high precision where needed, lower precision where acceptable - improving measurement precision without requiring uniformly high precision across all parameters.
Solution Approach 2:
The quantization scheme is dynamic rather than static - step-sizes are selected based on the current parameter value and perceptual considerations. This dynamic adaptation allows the system to optimize precision locally without the complexity of fully adaptive schemes.
Data Source
AI summary
The present disclosure provides methods, devices and computer program products for non-uniform quantization of parameters relating to parametric spatial coding of audio signals. 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.