Spatial Audio Direction Quantization Using Average-Difference Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing spatial audio encoding technologies face challenges in efficiently compressing and encoding spatial audio parameters, particularly direction parameters, to minimize the number of bits required for representation, especially when dealing with various input types such as microphone-array captured signals, loudspeaker signals, and Ambisonic signals.
Innovation Solution
A method and apparatus for quantizing and indexing spatial audio direction parameters, including averaging and weighting across time subframes and frequency subbands, followed by Golomb Rice encoding to reduce the bit rate required for transmitting spatial metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spatial audio direction parameters are encoded with high precision for each time sub frame and frequency sub band, then the accuracy of spatial representation is improved, but the number of bits required for transmission increases
Solution Approach 1:
The patent segments the spatial audio direction parameters by separating them into a common average direction parameter (applicable across multiple sub-frames) and individual difference parameters (specific to each sub-frame). This segmentation allows the majority of parameters to share common information while only encoding deviations, significantly reducing the total bit count while preserving spatial accuracy.
Solution Approach 2:
The patent performs preliminary averaging of spatial audio direction parameters across multiple time sub-frames and frequency sub-bands to establish a common reference value before encoding individual deviations. This preliminary action identifies redundant information that can be encoded once and reused, reducing the bits needed for subsequent parameter encoding.
2Adaptability or versatility
If spatial audio parameters are encoded for multiple input types (microphone arrays, loudspeakers, Ambisonics), then the versatility of the encoder is improved, but the device complexity increases
Solution Approach 1:
The patent implements a universal encoding framework that processes spatial audio parameters from multiple input types (microphone arrays, loudspeaker signals, Ambisonic signals) through a common parameter extraction and encoding pipeline. The system adapts to different input formats while maintaining the same core encoding logic, achieving multi-functionality without proportionally increasing complexity.
Solution Approach 2:
The patent handles different input types by adjusting parameter extraction methods and transformations rather than implementing separate encoding systems. For example, it transforms Ambisonic B-format signals and microphone array data into common spatial parameters (azimuth, elevation, energy ratios) that are then encoded using the same quantization and differential encoding processes, reducing complexity through parameter standardization.
Data Source
AI summary
There is inter alia disclosed an apparatus for spatial audio encoding configured to quantise and index a spatial audio direction parameter to form a quantised spatial audio direction index, wherein the spatial audio direction parameter is associated with a time sub frame of a frequency sub band of an audio frame; and determine a quantised spatial audio difference index by calculating the difference between the quantised spatial audio direction index and a quantised average spatial audio direction index.