Spatial Audio Parameter Quantization Using Energy-Dependent Rules
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Solution Overview
Problem
Existing multi-channel audio compression techniques, such as Binaural Cue Coding and Parametric Stereo, inefficiently represent spatial audio parameters, leading to sub-optimal quantization and increased bandwidth usage for channels with low energy, which are often masked during playback, resulting in wasted bandwidth and reduced perceptual quality.
Innovation Solution
A parameter quantizer and dequantizer system that generates energy-dependent quantization rules based on the energy measures of individual channels and the multi-channel signal, allowing for coarser quantization of low-energy channels without affecting perceptual quality, as high-energy signals mask low-energy signals during playback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform quantization is applied to all channels, then quantization simplicity is maintained, but bandwidth efficiency deteriorates due to wasted bits on low-energy masked channels
Solution Approach 1:
The patent applies different quantization rules to different channels based on their energy levels and masking conditions. High-energy channels receive finer quantization while low-energy masked channels receive coarser quantization, optimizing bandwidth usage according to local signal characteristics rather than applying uniform quantization across all channels.
2Loss of energy
If coarse quantization is applied to low-energy channels, then bandwidth efficiency improves, but manufacturing precision deteriorates due to increased quantization error
Solution Approach 1:
The patent dynamically changes quantization parameters based on signal energy and masking conditions. The quantization step size is adjusted according to the local signal characteristics, applying coarser quantization to low-energy masked channels and finer quantization to high-energy channels, thereby optimizing the trade-off between bandwidth efficiency and reconstruction accuracy.
3Reliability
If fine quantization is applied to all channels, then perceptual quality is maintained, but bandwidth consumption increases due to unnecessary precision for masked channels
Solution Approach 1:
The patent applies different quantization precision to different channels based on their perceptual importance. Channels that are masked by higher-energy signals receive coarser quantization since their contribution to perceptual quality is minimal, while unmasked high-energy channels receive finer quantization to maintain overall perceptual quality, thereby reducing total bandwidth consumption.
4Loss of energy
If energy-dependent quantization is implemented, then bandwidth efficiency improves, but device complexity increases due to additional energy calculation and rule selection logic
Solution Approach 1:
The patent calculates signal energy and determines appropriate quantization rules in advance during the encoding process. By pre-computing energy levels and selecting quantization parameters before actual quantization occurs, the system prepares optimization strategies ahead of time, reducing the computational burden during real-time processing while maintaining bandwidth efficiency.
Data Source
AI summary
Parameters being a measure for a characteristic of a channel or of a pair of channels, wherein the parameter is a measure for a characteristic of the channel or of the pair of channels with respect to another channel of a multi-channel signal can be quantized more efficiently using a quantization rule that is generated based on a relation of an energy measure of the channel or the pair of channels and an energy measure of the multi-channel signal. With generation of the quantization rule taking into account a psycho acoustic approach, the size of an encoded representation of the multi-channel signal can be decreased by coarser quantization without significantly disturbing the perceptual quality of the multi-channel signal when reconstructed from the encoded representation.