Audio Encoder Context Mapping for Transform-Length Switching
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Solution Overview
Problem
Conventional audio coding methods experience a significant loss in coding efficiency when frequently switching between different time/frequency resolutions, as they reset the context, leading to sub-optimal codebook selection and reduced adaptation to signal characteristics.
Innovation Solution
Implementing a context mapping mechanism that derives new contexts for coefficients with changing resolutions using interpolation, extrapolation, sub-sampling, or up-sampling, allowing for more frequent switching between time/frequency resolutions without compromising coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If context is reset when switching between different time/frequency resolutions, then switching between resolutions can be implemented, but coding efficiency decreases significantly
Solution Approach 1:
The patent introduces a context mapping mechanism that acts as an intermediary between the old context (from previous resolution) and the new context (for current resolution). Instead of directly resetting the context when switching resolutions, the mapping mechanism transforms and adapts the old context to the new resolution requirements, thereby maintaining coding efficiency while enabling resolution switching.
Solution Approach 2:
The patent changes the parameters of the context by applying mapping functions that adapt the old context parameters (based on old resolution) to new context parameters (for new resolution). This involves transforming statistical properties and codebook selections to match the new resolution requirements, allowing the system to maintain optimal coding efficiency across different resolutions.
2Productivity
If context mapping mechanism is implemented, then coding efficiency is maintained during switching, but device complexity increases
Solution Approach 1:
The context mapping mechanism is segmented into distinct functional components: identification of old context, selection of mapping function, application of mapping, and generation of new context. This segmentation allows each component to be optimized independently and facilitates implementation in existing audio coding frameworks with minimal disruption to the overall system architecture.
Solution Approach 2:
The context mapping mechanism is designed to be dynamic and adaptive, selecting appropriate mapping functions based on the specific resolution switching scenario. The system can adaptively choose from multiple mapping strategies (interpolation, extrapolation, sub-sampling, up-sampling) depending on the signal characteristics and resolution change requirements, optimizing performance while managing complexity.
Data Source
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AI summary
An audio encoder (100) for encoding segments of coefficients, the segments of coefficients representing different time or frequency resolutions of a sampled audio signal, the audio encoder (100) comprising a processor (110) 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 (100) further comprises an entropy encoder (120) for entropy encoding the current coefficient based on the coding context to obtain an encoded audio stream.