Audio Entropy Coding Context Mapping Across Transform Lengths
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional audio coding techniques experience a significant loss in coding efficiency when frequent switching between different time/frequency resolutions occurs, as they resort to sub-optimal codebook selection due to context resetting, which is inadequate for frequent signal adaptations required at lower data rates.
Innovation Solution
The implementation of a context mapping mechanism that derives new contexts for coefficients with changing resolutions by using interpolation, extrapolation, sub-sampling, or up-sampling from previous contexts, allowing for more frequent switching between time/frequency resolutions without compromising coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If context resetting is used when switching between different time/frequency resolutions, then synchronization between encoder and decoder is maintained, but coding efficiency deteriorates significantly due to sub-optimal codebook selection
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple codebooks corresponding to different time/frequency resolutions before encoding begins. When a resolution switch occurs, the system can immediately select the appropriate pre-prepared codebook without resetting the context, thus maintaining both synchronization and coding efficiency. The codebooks are prepared in advance for different block lengths (e.g., 128 or 1024 coefficients) and window sizes, allowing seamless adaptation to signal characteristics.
Solution Approach 2:
The patent implements dynamics by making the codebook selection dynamic based on the current signal characteristics and required time/frequency resolution. Instead of a static context reset approach, the system dynamically adapts by selecting from multiple available codebooks according to the current encoding needs, allowing frequent switching between resolutions while maintaining optimal coding performance through context-based probability distribution adaptation.
2Adaptability or versatility
If frequent switching between different transform lengths is performed to adapt to signal characteristics at lower data rates, then adaptability improves, but coding efficiency deteriorates due to repeated context resetting
Solution Approach 1:
The patent applies universality by creating a universal coding framework that handles multiple time/frequency resolutions within a single unified context structure. Multiple codebooks are maintained that can serve different resolution requirements, allowing the system to frequently switch between transform lengths (128 or 1024 coefficients) while maintaining consistent context-based probability distributions. This multi-functional approach enables the same context mechanism to serve various resolution needs without resetting.
Solution Approach 2:
The patent implements parameter changes by allowing the codebook selection parameter to change dynamically based on the current transform length and window size requirements. When switching between different resolutions, the system changes which codebook is active rather than resetting the entire context, thus maintaining adaptability to signal characteristics while preserving coding efficiency through continuous context utilization across different parameter settings.
3Reliability
If context is built up from scratch after resetting, then synchronization is ensured, but loss of information occurs due to discarding previously learned statistical properties
Solution Approach 1:
The patent applies copying by maintaining copies of context information across different codebooks and resolution levels. Instead of discarding context when switching resolutions, the system copies or references relevant statistical properties from previously learned contexts to the current codebook selection process. This allows the encoder and decoder to stay synchronized through shared codebook structures while preserving valuable statistical information across resolution transitions.
Solution Approach 2:
The patent implements nesting by organizing codebooks in a hierarchical structure where contexts at different resolution levels are nested within a unified framework. The context information is not discarded but nested across multiple codebook layers, allowing the system to access and utilize statistical properties from coarser or finer resolutions as needed. This nested organization ensures synchronization while preventing information loss across resolution switches.
Data Source
AI summary
An audio encoder for encoding segments of coefficients, the segments of coefficients representing different time or frequency resolutions of a sampled audio signal, the audio encoder including a processor for deriving a coding context for a currently encoded coefficient of a current segment based on a previously encoded coefficient of a previous segment, the previously encoded coefficient representing a different time or frequency resolution than the currently encoded coefficient. The audio encoder further includes an entropy encoder for entropy encoding the current coefficient based on the coding context to obtain an encoded audio stream.