Audio Object Coding with Modulo Differential Matrix Encoding
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Solution Overview
Problem
Existing object-based audio systems face inefficiencies in encoding and decoding audio signals, leading to reduced quality and increased bitrate, particularly in representing and reconstructing audio objects with MPEG SAOC, which relies on complex mathematical processes and assumptions about audio object properties.
Innovation Solution
The proposed solution involves encoding and decoding methods that use modulo differential coding for entropy coding of upmix matrix parameters, reducing the number of symbols and probability table size, and employing sparse encoding for upmix matrices to decrease bitrate by transmitting only essential elements, thereby improving coding efficiency and quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If parametric coding methods like MPEG SAOC are used to represent audio objects, then the required bitrate is reduced, but the coding complexity and mathematical processing requirements increase
Solution Approach 1:
The patent transforms the coding approach by changing parameters from direct audio object representation to difference value encoding. By encoding the difference between adjacent quantization units instead of absolute values, and applying modulo operation to limit the range, the system achieves lower bitrate while managing complexity through standardized transformation operations.
Solution Approach 2:
The patent applies different encoding strategies to different parts of the audio data. By identifying that adjacent quantization units often have similar values, it locally exploits this redundancy by encoding only the difference values, thereby reducing overall bitrate without uniformly increasing complexity across all data.
2Measurement precision
If difference values are encoded without modulo operation to preserve precision, then measurement precision is improved, but the size of code book increases
Solution Approach 1:
The patent applies modulo operation to the difference values to constrain them within a fixed range (e.g., 0-7). This parameter transformation maintains sufficient precision for audio coding while limiting the number of possible values, thereby keeping the code book size manageable without requiring exponentially larger tables.
3Measurement precision
If separate probability tables are used for different elements in the vector, then coding precision is improved, but memory requirements increase
Solution Approach 1:
The patent merges the probability tables for different elements in the vector by recognizing that their difference value distributions are similar. Instead of maintaining separate large tables, it uses a single shared probability table that works for all elements, thereby reducing memory requirements while preserving coding precision through the standardized difference encoding approach.
Data Source
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.