Ambisonic Audio Encoder Spatial Parameter Ordering

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Solution Overview

Problem

Current 3D sound scene coding techniques fail to optimize bit rate adaptability based on spatial resolution, leading to suboptimal degradation of sound source localization and lack of compatibility with various sound rendering systems.

Innovation Solution

A method that orders spectral parameters of surround sound components by their contribution to spatial precision, using Gerzon's criteria to identify and prioritize the least relevant elements for coding, ensuring minimal impact on spatial precision during bit rate reduction, and adapts the quantization rate accordingly.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional 3D sound scene coding techniques are used to achieve bit rate adaptability, then bit rate can be adjusted during compression, but spatial precision of sound source localization is not optimized and degrades suboptimally

Engineering Contradiction:
Improvebit rate adaptabilityVSAvoidspatial precision
Core Design Contradiction:
Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent segments the spectral parameters into different subsets (first subset and second subset) with different priorities for spatial precision. The first subset contains parameters critical for spatial localization that are preserved even at low bit rates, while the second subset contains less critical parameters that can be reduced or removed. This segmentation allows bit rate adaptability while protecting spatial precision by ensuring critical parameters remain coded regardless of overall bit rate constraints.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies different coding priorities to different spectral parameters based on their local importance to spatial precision. Certain spectral parameters are identified as having higher contribution to spatial localization accuracy and are assigned higher coding priority. This local quality approach ensures that parameters most critical for spatial precision maintain higher fidelity even when overall bit rate is reduced, thereby optimizing spatial precision under bit rate constraints.

Inventive Principle:
Principle #3Local quality

2Ease of manufacture

If spectral parameters are coded with uniform priority, then coding simplicity is maintained, but spatial precision degradation cannot be minimized during bit rate reduction

Engineering Contradiction:
Improvecoding simplicityVSAvoidspatial precision
Core Design Contradiction:
Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent performs preliminary analysis to determine the priority of each spectral parameter before the actual coding process. The encoder identifies which spectral parameters contribute most to spatial precision and assigns them higher priorities in advance. This preliminary classification allows the coding process to simply apply the predetermined priorities during compression, maintaining coding simplicity while ensuring spatial precision is optimized by preserving high-priority parameters even at reduced bit rates.

Inventive Principle:
Principle #10Preliminary action

3Measurement precision

If all spectral parameters are preserved during compression, then spatial precision is maintained, but bit rate efficiency is reduced and adaptability to different networks is limited

Engineering Contradiction:
Improvespatial precisionVSAvoidbit rate efficiency
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent implements dynamic spectral parameter selection where the encoder adaptively determines which spectral parameters to code based on current bit rate constraints and their relative importance to spatial precision. The system dynamically adjusts the set of coded parameters - preserving critical spatial parameters while removing or coarsely coding less critical ones when bit rate is limited. This dynamic approach maintains spatial precision for essential parameters while improving bit rate efficiency by not wasting bits on redundant or less important parameters.

Inventive Principle:
Principle #15Dynamics

4Adaptability or versatility

If conventional coding techniques are used, then compatibility with standard systems is achieved, but adaptability to sound rendering systems with different configurations is limited

Engineering Contradiction:
Improvecompatibility with sound rendering systemsVSAvoidspatial precision
Core Design Contradiction:
Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent creates a universal coding framework that identifies and preserves spectral parameters universally important for spatial precision across different sound rendering system configurations. By determining which spectral parameters contribute to spatial localization in a configuration-agnostic manner, the encoder produces coded data that maintains spatial precision adaptability across various rendering systems (headphones, stereo speakers, surround systems). This universal approach ensures both compatibility with diverse systems and optimization of spatial precision through selective parameter preservation.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP2143102B1Audio encoding and decoding method and associated audio encoder, audio decoder and computer programs
Publication Date: 2018.08.29 ORANGE SA
  • EP2143102B1 patent drawingFigure 1~2
  • EP2143102B1 patent drawingFigure 4
  • EP2143102B1 patent drawingFigure 5~6

AI summary

The invention relates to a method for ordering spectral parameters of ambisonic components to be encoded (A1,..., AQ) originating from an audio scene comprising N signals (Sii=1 to N), in which N>1, comprising the following steps: calculation of the respective influence of at least some spectral parameters, taken from a set of spectral parameters to be ordered, on an angle vector defined as a function of energy and velocity vectors associated with Gerzon's criteria and calculated as a function of a reverse ambisonic transformation in relation to said quantified ambisonic components; and allocation of a predence order to at least one spectral parameter as a function of the influence calculated for said spectral parameter compared to the other calculated influences.