HRTF Sequence Generation with B-Spline Modeling for Real-Time Spatial Audio
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Solution Overview
Problem
Existing spatial audio rendering technologies face challenges in achieving high spatial resolution and real-time performance due to the need for densely sampled head-related transfer function (HRTF) databases, leading to inefficient and inaccurate interpolation methods that cause spatial discontinuities and audio-video sync errors in virtual reality (VR), augmented reality (AR), and mixed reality (MR) applications.
Innovation Solution
A variational approach using B-spline basis functions for modeling head-related filters, allowing for efficient generation of HR filters at arbitrary locations with improved accuracy and reduced computational effort, enabling real-time VR/AR/MR systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If densely sampled HRTF databases are used, then spatial resolution is improved, but computational complexity and memory requirements increase
Solution Approach 1:
The patent uses B-spline basis functions to create a parametric model that copies the essential characteristics of densely sampled HRTF data without requiring the actual dense data. The basis functions serve as a compact representation that can generate accurate HRTF estimates at arbitrary locations through mathematical evaluation, eliminating the need to store and process large dense databases.
Solution Approach 2:
The patent transforms the HRTF representation from a fixed dense grid format to a parametric form using B-spline basis functions. By changing the representation parameters from discrete sampled values to continuous basis function coefficients, the system achieves high spatial resolution through mathematical evaluation rather than dense sampling, significantly reducing computational complexity and memory requirements.
2Measurement precision
If densely sampled HRTF databases are used, then spatial resolution is improved, but memory requirements increase
Solution Approach 1:
Instead of storing actual dense HRTF database values in memory, the patent stores compact B-spline basis function definitions and coefficients. These basis functions serve as a mathematical copy that can generate any required HRTF value on-demand, dramatically reducing memory requirements while maintaining the ability to achieve high spatial resolution when needed.
Solution Approach 2:
The patent changes the storage parameter from storing numerous discrete HRTF samples to storing a small set of basis function coefficients. This parameter transformation allows the system to maintain high spatial resolution capability through mathematical evaluation while requiring minimal memory to store the compact parametric representation.
3Productivity
If traditional interpolation methods are used, then computational effort is reduced, but spatial discontinuities and audio-video sync errors occur
Solution Approach 1:
The patent replaces traditional mechanical interpolation methods (which connect discrete points) with a mathematical field-based approach using B-spline basis functions. This substitution eliminates the discontinuities inherent in point-to-point interpolation by providing a smooth continuous mathematical surface that naturally transitions between locations, ensuring spatial continuity while maintaining computational efficiency.
Solution Approach 2:
The patent changes the interpolation parameter from discrete point connections to continuous basis function evaluation. By evaluating B-spline basis functions at any desired location, the system achieves smooth spatial transitions without the discontinuities of traditional methods, while the efficient mathematical evaluation maintains computational productivity.
4Adaptability or versatility
If parametric HRTF representation is used, then integration with audio coders is improved, but filtering accuracy may be reduced
Solution Approach 1:
The patent uses B-spline basis functions to create a parametric representation that naturally integrates with audio coding systems. The basis function coefficients serve as compact parameters that can be efficiently encoded and transmitted, while the mathematical evaluation of these parameters at any location maintains high filtering accuracy through the properties of B-spline interpolation.
Data Source
AI summary
A method for audio signal filtering. The method includes generating a pair of filters for a certain location specified by an elevation angle ϑ and an azimuth angle φ, the pair of filters consisting of a right filter (ĥr(ϑ, φ)) and a left filter (ĥl(248 , φ)); filtering an audio signal using the right filter; and filtering the audio signal using the left filter. Generating the pair of filters comprises: i) obtaining at least a first set of elevation basis function values at the elevation angle; ii) obtaining at least a first set of azimuth basis function values at the azimuth angle; iii) generating the right filter using: a) at least the first set of elevation basis function values, b) at least the first set of azimuth basis function values, and c) right filter model parameters; and iv) generating the left filter using: a) at least the first set of elevation basis function values, b) at least the first set of azimuth basis function values, and c) left filter model parameters.