HR Filter Segmentation for Accurate Spatial Audio Interpolation
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Solution Overview
Problem
Existing HR filter interpolation methods for spatial audio rendering in VR/AR/MR/XR systems suffer from spatial discontinuities and inefficiencies, particularly when using coarsely sampled HR filter sets, leading to audio-video sync errors and reduced immersion due to computational complexity and inaccurate interpolation.
Innovation Solution
A method for efficient HR filter modeling through automatic segmentation of index ranges, using variational characteristics to determine filter models for each segment, allowing accurate and efficient interpolation at arbitrary locations, suitable for real-time VR/AR/MR/XR systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If coarsely sampled HR filter sets are used, then device complexity is reduced, but spatial continuity and interpolation accuracy deteriorate
Solution Approach 1:
The patent divides the HR filter data sequence into multiple segments based on variational characteristics. Each segment is modeled separately using appropriate filter models, allowing accurate representation of different temporal regions while reducing overall complexity. This segmentation enables the system to handle coarse sampling more effectively by focusing computational resources on critical segments.
Solution Approach 2:
Different filter models are applied to different segments based on their specific variational characteristics. The patent uses discriminative mapping to match segment complexity with appropriate modeling approaches, ensuring that each region is represented with the optimal level of detail. This local optimization maintains interpolation accuracy without requiring uniformly high complexity across all segments.
2Productivity
If traditional interpolation methods are used with coarsely sampled filters, then computational effort is reduced, but spatial discontinuities and audio-video sync errors increase
Solution Approach 1:
The patent performs preliminary segmentation and characterization of HR filter segments before interpolation. By pre-identifying variational characteristics and selecting appropriate models for each segment, the system prepares optimized representations that enable accurate real-time interpolation without excessive computational burden during audio rendering.
Solution Approach 2:
The patent transforms the interpolation problem by changing parameters from uniform filtering to segment-specific modeling. By varying the modeling approach based on segment characteristics rather than applying a single method uniformly, the system achieves both computational efficiency and spatial continuity, preventing audio-video sync errors while maintaining reliability.
3Manufacturing precision
If uniformly complex filter models are applied to all segments, then interpolation accuracy is improved, but computational effort increases
Solution Approach 1:
The patent dynamically adjusts model parameters based on segment characteristics rather than using fixed high-complexity models. By changing the modeling parameters to match the actual variability in each segment, the system achieves accurate interpolation only where needed, significantly reducing overall computational effort while maintaining precision.
Solution Approach 2:
The patent applies complex modeling only to segments that require it based on their variational characteristics, rather than uniformly applying high complexity everywhere. This partial application of complex models to only the necessary segments maintains interpolation accuracy while avoiding the excessive computational effort that would result from uniform high-complexity modeling across all segments.
Data Source
AI summary
A method for modelling of a set of filters is provided. The method comprises acquiring a set of feature values each of which is associated with an index within an index range of the filters and dividing the index range into multiple segments using the acquired set of feature values. The method also comprises determining a filter model for at least one segment of the multiple segments and outputting the determined filter model.