Audio Object Bit Allocation by Perceptual Importance
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Solution Overview
Problem
Current bit allocation methods for audio objects in 3D audio technology result in low overall quality and encoding efficiency due to evenly distributing bits among multiple audio objects, failing to consider perceptual differences.
Innovation Solution
A method that allocates bits based on the perceptual importance parameters of individual audio objects, such as energy intensity and spectrum change, to enhance the quality and efficiency of the encoding process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If bits are evenly allocated to multiple audio objects, then the allocation process is simple, but the overall quality and encoding efficiency of reconstructed audio objects deteriorate
Solution Approach 1:
The patent applies local quality by allocating different bit quantities to different audio objects based on their individual perceptual importance parameters. Instead of uniform allocation, each audio object receives bits proportional to its energy intensity and spectrum change characteristics, thereby improving reconstruction quality where it matters most while maintaining manageable complexity through automated parameter-based distribution
Solution Approach 2:
The patent changes the bit allocation parameter from a fixed equal value to a dynamic value determined by perceptual importance parameters (energy intensity and spectrum change). This parameter transformation enables the system to adapt bit distribution to the actual characteristics of each audio object, resolving the contradiction between allocation simplicity and reconstruction quality
2Ease of operation
If bits are evenly allocated to multiple audio objects, then the encoding process is straightforward, but the encoding efficiency deteriorates
Solution Approach 1:
The patent transforms the encoding process by introducing perceptual importance parameters (energy intensity and spectrum change) that automatically determine bit allocation. This parameter-driven approach maintains operational simplicity while dramatically improving encoding efficiency, as the system adapts to audio characteristics without requiring complex manual intervention
Solution Approach 2:
The encoding system performs self-optimization by automatically calculating perceptual importance parameters and distributing bits accordingly. This self-service mechanism eliminates the need for complex external optimization processes, maintaining ease of operation while achieving high encoding efficiency through automated adaptation to audio content characteristics
Data Source
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AI summary
A bit allocation method and apparatus for an audio object are disclosed, which relate to the field of audio encoding and decoding technologies, to help improve overall quality and encoding efficiency of a reconstructed audio object. The method includes: separately pre-rendering a plurality of audio objects to be pre-rendered in an audio frame, to obtain a plurality of pre-rendered audio objects; obtaining respective perceptual importance parameter values of the plurality of pre-rendered audio objects, where a perceptual importance parameter value of a current pre-rendered audio object indicates a perceptual importance degree of the current pre-rendered audio object in the plurality of pre-rendered audio objects; obtaining a bit allocation parameter value of a current audio object to be pre-rendered based on the respective perceptual importance parameter values of the plurality of pre-rendered audio objects; and determining, based on the bit allocation parameter value of the current audio object to be pre-rendered and a total quantity of to-be-allocated bits corresponding to the plurality of audio objects to be pre-rendered, a target quantity of bits allocated to the current audio object to be pre-rendered. The method may be applied to a stereo encoder or a multi-channel encoder.