Spherical Audio Mapping Resolves Distance Direction Uncertainty
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Solution Overview
Problem
Existing audio scene analysis technologies face challenges in effectively mapping and interpreting auditory scenes due to infinite object distances, uncertainty in source direction with distance, and discontinuities in feature extraction, particularly in reverberant environments.
Innovation Solution
A method and system for creating a spatial audio scene analysis by generating electrical signals, extracting spatial angle and diffusivity information, and mapping these onto a closed two-dimensional surface, such as a hemisphere, to represent object positions and distances in a compact and consistent feature space, avoiding singularities and discontinuities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional spatial mapping is used with infinite object distances, then the feature space becomes unbounded and complex, but this leads to singularities and discontinuities in the mapping
Solution Approach 1:
The patent applies spherical geometry to map spatial audio features onto a closed spherical surface. This curvature-based mapping transforms the traditional unbounded Euclidean space into a compact spherical manifold, eliminating singularities and discontinuities while maintaining consistent feature representation across all spatial regions.
Solution Approach 2:
The patent introduces a new dimensional framework by mapping traditional 2D spatial coordinates (azimuth, elevation) onto a 3D spherical surface. This dimensional transformation adds a radial component that naturally handles distance information, converting the unbounded 2D plane into a bounded 3D spherical space that resolves the singularity problem.
2Adaptability or versatility
If object distance is allowed to be infinite, then the spatial representation covers all possible distances, but this creates uncertainty in source direction as distance increases
Solution Approach 1:
The spherical mapping naturally couples direction and distance through the geometry of the sphere. As objects move farther away, their representation naturally converges toward the horizon region of the sphere, where angular precision is inherently reduced. This geometric constraint mirrors the physical uncertainty in distant source localization, providing a consistent representation that adapts precision to distance.
Solution Approach 2:
The patent transforms the traditional parameterization of spatial position by using spherical coordinates (radius, azimuth, elevation) instead of Cartesian coordinates. This parameter change allows the system to represent infinite distances in a bounded manner, where the radial parameter handles distance information separately from angular parameters, thus preserving direction accuracy for near-field sources while providing a consistent representation for distant sources.
3Device complexity
If a closed two-dimensional surface mapping is used, then the feature space becomes compact and bounded, but this requires transformation from traditional infinite spatial coordinates
Solution Approach 1:
The patent implements the closed surface mapping by transitioning from 2D planar coordinates to 3D spherical coordinates. This dimensional elevation provides a natural framework for creating a compact bounded space while maintaining a relatively simple transformation process based on standard spherical coordinate mathematics, making the implementation tractable despite the topological change.
Data Source
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AI summary
In one embodiment, a sound field is mapped by extracting spatial angle information, diffusivity information, and optionally, sound level information. The extracted information is mapped for representation in the form of a Riemann sphere, wherein spatial angle varies longitudinally, diffusivity varies latitudinally, and level varies radially along the sphere. A more generalized mapping employs mapping the spatial angle and diffusivity information onto a representative region exhibiting variations in direction of arrival that correspond to the extracted spatial information and variations in distance that correspond to the extracted diffusivity information.