Spherical Harmonic Coefficient Compression via Energy Analysis
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Solution Overview
Problem
Current audio coding technologies face challenges in efficiently compressing multi-channel audio data, particularly with higher-order spherical harmonic coefficients, which are essential for representing three-dimensional soundfields, while maintaining backward compatibility and adaptability to various speaker geometries.
Innovation Solution
The method involves performing an energy analysis on spherical harmonic coefficients to determine a reduced version, dynamically applying thresholds based on energy volumes, and generating a bitstream, which adapts to the significance of each coefficient, thereby reducing data while ensuring quality and compatibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If higher-order spherical harmonic coefficients are used to represent three-dimensional soundfields, then the accuracy and quality of spatial audio representation is improved, but the data size and processing complexity increase
Solution Approach 1:
The patent extracts only the salient spherical harmonic coefficients that contribute significantly to spatial audio quality. By performing energy analysis and comparing coefficient magnitudes against thresholds, the system identifies and retains only those coefficients above the threshold, discarding redundant information while preserving perceptual quality.
Solution Approach 2:
The patent dynamically adjusts the energy threshold parameter based on the characteristics of the audio signal and speaker configuration. By changing the threshold parameter adaptively, the system optimizes the balance between retaining sufficient spatial information and reducing data size, allowing flexible compression ratios while maintaining quality.
2Measurement precision
If higher-order spherical harmonic coefficients are used to represent three-dimensional soundfields, then the accuracy and quality of spatial audio representation is improved, but the processing complexity increases
Solution Approach 1:
The patent extracts only the salient spherical harmonic coefficients that contribute significantly to spatial audio quality. By performing energy analysis and comparing coefficient magnitudes against thresholds, the system identifies and retains only those coefficients above the threshold, discarding redundant information while preserving perceptual quality.
Solution Approach 2:
The patent applies partial action by processing only the necessary subset of coefficients rather than all higher-order coefficients. By selectively analyzing and retaining only those coefficients that exceed the energy threshold, the system reduces computational load while maintaining sufficient spatial representation accuracy.
3Quantity of substance
If spherical harmonic coefficients are compressed by eliminating non-salient coefficients, then the data size is reduced, but the perceived sound quality may be impacted
Solution Approach 1:
The patent dynamically adjusts the energy threshold parameter based on the characteristics of the audio signal and speaker configuration. By changing the threshold parameter adaptively, the system optimizes the balance between retaining sufficient spatial information and reducing data size, allowing flexible compression ratios while maintaining quality.
Solution Approach 2:
The patent uses energy analysis feedback to identify which coefficients contribute significantly to the soundfield representation. By continuously analyzing the energy distribution across coefficients and adjusting retention decisions based on this feedback, the system ensures that only non-impactful coefficients are removed, preserving perceived quality.
4Productivity
If spherical harmonic coefficients are compressed to reduce data size, then the storage and transmission efficiency is improved, but the adaptability to various speaker geometries may be reduced
Solution Approach 1:
The patent dynamically adjusts the energy threshold parameter based on the characteristics of the audio signal and speaker configuration. By changing the threshold parameter adaptively, the system optimizes the balance between retaining sufficient spatial information and reducing data size, allowing flexible compression ratios while maintaining quality.
Data Source
AI summary
In general, techniques are described for coding of spherical harmonic coefficients representative of a three dimensional soundfield. A device comprising a memory and one or more processors may be configured to perform the techniques. The memory may be configured to store a plurality of spherical harmonic coefficients. The one or more processors may be configured to perform an energy analysis with respect to the plurality of spherical harmonic coefficients to determine a reduced version of the plurality of spherical harmonic coefficients.