Audio Decoding with Non-Uniform Dequantization for Lower Bit Use
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Solution Overview
Problem
Existing parametric stereo coding methods face challenges in minimizing bit stream information while maintaining good audio quality, as high compression levels can lead to unacceptable sound quality due to information loss, and low compression levels can result in capacity problems.
Innovation Solution
The proposed solution involves a method for encoding and decoding audio signals using non-uniform scalar quantization schemes for parametric spatial coding. This method selects smaller step-sizes for ranges where human sound perception is most sensitive and larger step-sizes for less sensitive ranges, reducing average bit consumption without compromising sound quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If high compression levels are applied to minimize bit stream information, then bit consumption is reduced, but sound quality deteriorates due to information loss
Solution Approach 1:
The patent applies non-uniform quantization where different step-sizes are used for different ranges of quantized parameters based on human sound perception sensitivity. Ranges with higher perception sensitivity use smaller step-sizes to maintain quality, while less sensitive ranges use larger step-sizes to reduce bit consumption. This local adaptation resolves the contradiction by optimizing the balance between compression and quality for each parameter range individually.
Solution Approach 2:
The patent changes the quantization step-sizes based on the range of quantized parameters and human perception sensitivity. By dynamically selecting step-sizes (a parameter change) rather than using a fixed uniform step-size, the system achieves better rate-distortion performance, reducing bit consumption while maintaining sound quality in perceptually critical regions.
2Reliability
If low compression levels are applied to maintain sound quality, then information is preserved, but bit stream capacity problems occur
Solution Approach 1:
The patent applies non-uniform quantization where different step-sizes are used for different ranges of quantized parameters based on human sound perception sensitivity. Ranges with higher perception sensitivity use smaller step-sizes to maintain quality, while less sensitive ranges use larger step-sizes to reduce bit consumption. This local adaptation resolves the contradiction by optimizing the balance between compression and quality for each parameter range individually.
Solution Approach 2:
The patent changes the quantization step-sizes based on the range of quantized parameters and human perception sensitivity. By dynamically selecting step-sizes (a parameter change) rather than using a fixed uniform step-size, the system achieves better rate-distortion performance, reducing bit consumption while maintaining sound quality in perceptually critical regions.
3Ease of manufacture
If uniform quantization step-sizes are used for all parameter ranges, then implementation is simple, but bit consumption increases in perceptually less sensitive ranges
Solution Approach 1:
The patent applies non-uniform quantization where different step-sizes are used for different ranges of quantized parameters based on human sound perception sensitivity. Ranges with higher perception sensitivity use smaller step-sizes to maintain quality, while less sensitive ranges use larger step-sizes to reduce bit consumption. This local adaptation resolves the contradiction by optimizing the balance between compression and quality for each parameter range individually.
Solution Approach 2:
The patent changes the quantization step-sizes based on the range of quantized parameters and human perception sensitivity. By dynamically selecting step-sizes (a parameter change) rather than using a fixed uniform step-size, the system achieves better rate-distortion performance, reducing bit consumption while maintaining sound quality in perceptually critical regions.
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.


