Audio Encoder Context Mapping for Transform Length Switching
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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 reset the context, leading to sub-optimal codebook selection and reduced adaptation to signal characteristics.
Innovation Solution
Implement a context mapping mechanism that derives new contexts for coefficients with changing resolutions by using interpolation, extrapolation, sub-sampling, or up-sampling of previous context information, allowing for more frequent switching between different time/frequency resolutions without compromising coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If context is reset when switching between different time/frequency resolutions, then coding efficiency is maintained through simplified context management, but coding efficiency deteriorates significantly when switching occurs frequently
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple contexts (first context for first resolution, second context for second resolution) before switching occurs. When resolution switching is detected, the appropriate pre-defined context is activated, avoiding the need to reset and rebuild context from scratch. This prepares the coding system in advance for different resolution scenarios, maintaining coding efficiency during frequent switches.
Solution Approach 2:
The patent implements dynamics by making the context selection adaptive and dynamic based on the current resolution state. The system dynamically switches between different contexts (first context or second context) depending on whether the current segment uses first or second resolution, allowing the context to adapt to changing signal characteristics without resetting, thus maintaining coding efficiency during resolution transitions.
2Adaptability or versatility
If frequent switching between different time/frequency resolutions is implemented, then adaptation to signal characteristics is improved, but coding efficiency deteriorates due to context loss
Solution Approach 1:
The patent prepares multiple contexts in advance (first context for first resolution, second context for second resolution) corresponding to different signal characteristics. When switching between resolutions occurs, the appropriate pre-defined context is activated, allowing frequent adaptation to signal characteristics without losing coding efficiency, as the context information is preserved and selectively applied.
Solution Approach 2:
The patent changes the context parameter based on the resolution parameter. When the resolution switches between first and second types, the corresponding context parameter switches between first and second contexts. This parameter coupling allows the system to adapt to different signal characteristics through resolution changes while maintaining coding efficiency by using the appropriate context for each resolution level.
3Productivity
If context is maintained across resolution switches, then coding efficiency is improved through better codebook selection, but device complexity increases due to context mapping requirements
Solution Approach 1:
The patent defines and prepares multiple contexts in advance (first context, second context, etc.) corresponding to different resolutions before runtime switching occurs. This preliminary setup avoids the need for complex real-time context mapping and transformation operations, reducing device complexity while maintaining coding efficiency through appropriate context selection.
Solution Approach 2:
The patent extracts and separates the context management complexity by creating distinct, independent contexts for different resolutions. Instead of implementing complex mapping and transformation between contexts, the system extracts the essential context information for each resolution level into separate predefined contexts, simplifying the overall system architecture while maintaining coding efficiency.
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.


