Audio Decoder With Modulo Differential Parameter Coding
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Solution Overview
Problem
Existing audio coding systems, particularly object-based audio systems, face inefficiencies in encoding and decoding audio signals while maintaining quality, as methods like MPEG SAOC rely on complex mathematical processes and assumptions about audio objects, leading to suboptimal bitrate and quality.
Innovation Solution
A method and apparatus for encoding and decoding audio signals using entropy coding with modulo differential encoding and shared probability tables for upmix matrices, reducing memory requirements and bit rate by aligning probability distributions and using a single Huffman codebook.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If MPEG SAOC parametric coding is used to reduce bitrate, then bandwidth efficiency is improved, but decoding complexity and quality increase due to complex mathematical processes and assumptions
Solution Approach 1:
The patent transforms the complex parametric coding parameters into a simplified probability distribution model. By representing audio object parameters as probability distributions and using entropy coding, the system maintains bitrate efficiency while dramatically reducing decoding complexity. The key is changing from direct parametric reconstruction to probability-based symbolic representation.
Solution Approach 2:
The patent replaces complex mathematical reconstruction processes with a probabilistic modeling approach. Instead of using heavy mathematical operations to reconstruct audio objects, the system uses entropy coding with probability tables, substituting mechanical/mathematical complexity with statistical modeling that is computationally lighter.
2Measurement precision
If separate probability tables are used for each audio object to maintain accuracy, then coding precision is improved, but memory requirements increase
Solution Approach 1:
The patent merges separate probability tables into a single shared probability table that serves all audio objects. By combining the probability distributions and using a unified Huffman codebook, the system reduces memory requirements from multiple separate tables to one shared table, while maintaining coding precision through the unified probabilistic model.
Solution Approach 2:
The single shared probability table serves multiple functions for different audio objects simultaneously. The universal probability distribution model can represent parameters for any audio object, making the memory structure multi-functional and eliminating the need for object-specific tables.
3Measurement precision
If multiple Huffman codebooks are maintained for different parameter types to ensure accuracy, then coding accuracy is improved, but device complexity and memory usage increase
Solution Approach 1:
The patent combines multiple parameter-specific Huffman codebooks into a single unified Huffman codebook. By merging the codebooks and using a single probability distribution model for all parameters, the system reduces codebook management complexity from maintaining multiple separate codebooks to managing one unified codebook, while preserving coding accuracy through the universal probabilistic approach.
Data Source
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AI summary
The present disclosure provides methods, devices and computer program products for encoding and decoding of a vector of parameters in an audio coding system. The disclosure further relates to a method and apparatus for reconstructing an audio object in an audio decoding system. According to the disclosure, a modulo differential approach for coding and encoding a vector of a non-periodic quantity may improve the coding efficiency and provide encoders and decoders with less memory requirements. Moreover, an efficient method for encoding and decoding a sparse matrix is provided.