Spatial Audio Parameter Grouping for Low-Bitrate Metadata Encoding
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Solution Overview
Problem
Existing spatial audio encoding technologies face challenges in efficiently compressing directional metadata at various bit rates, particularly at lower bitrates, leading to high raw bitrates and the need for optimizing codec performance.
Innovation Solution
The proposed solution involves analyzing time-frequency-based directional metadata, forming groups with perceptually similar metadata, combining these representations, and signaling group information to reduce the number of directional metadata parameters, with optional quantization and sub-grouping for further reduction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If directional metadata parameters are encoded for each time-frequency tile separately, then measurement precision is improved, but bitrate increases
Solution Approach 1:
The patent combines directional metadata parameters across multiple time-frequency tiles by identifying perceptually similar tiles and encoding them with shared parameters. This merging approach reduces the total number of parameters that need to be transmitted, thereby lowering bitrate while maintaining perceptual accuracy of the spatial audio representation.
Solution Approach 2:
The patent transforms the encoding approach by changing from tile-by-tile parameter encoding to a hierarchical encoding scheme where parameters are defined at group levels. This parameter reorganization allows redundant information to be eliminated and only essential directional metadata to be transmitted, resolving the contradiction between precision and bitrate.
2Quantity of substance
If the number of directional metadata parameters is reduced, then bitrate is decreased, but measurement precision deteriorates
Solution Approach 1:
The patent applies local quality by differentiating between time-frequency tiles based on their perceptual importance and characteristics. Important tiles retain full parameter precision while similar or less critical tiles use shared or reduced parameters. This selective approach maintains measurement precision where needed while reducing bitrate overall.
Solution Approach 2:
The patent implements partial action by encoding directional metadata parameters for only the necessary time-frequency tiles rather than all tiles. By identifying and encoding only the most perceptually relevant parameters, the system achieves acceptable precision with reduced bitrate, applying the principle of doing enough rather than everything.
3Quantity of substance
If directional metadata is compressed aggressively, then bitrate is reduced, but audio quality deteriorates
Solution Approach 1:
The patent incorporates feedback mechanisms where the encoder analyzes the characteristics of directional metadata and adjusts compression strategies accordingly. By evaluating the perceptual importance of different time-frequency regions, the system applies appropriate compression levels that maintain audio quality for critical information while allowing greater compression for less important data, thus resolving the contradiction between bitrate reduction and quality preservation.
Solution Approach 2:
The patent implements dynamic compression strategies that adapt to the content being encoded. Rather than applying uniform compression, the system dynamically adjusts the level of parameter sharing and compression based on the perceptual similarity and importance of time-frequency tiles, maintaining audio quality where needed while achieving bitrate reduction overall.
Data Source
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AI summary
An apparatus comprising means configured to: obtain at least one parameter value (106) associated with at least two time-frequency parts of at least one audio signal (104); obtain at least one similarity value based on the at least one parameter value (106) associated with the at least two time-frequency parts of at least one audio signal (104); determine at least one group of time-frequency parts from the at least two time-frequency parts of at least one audio signal (104), the at least one group of time-frequency parts based on the at least one similarity value; and generate for the at least one group of time-frequency parts at least one associated group parameter (204), the at least one group parameter (204) based on the at least one parameter value (106) associated with the time-frequency parts.