Time-Varying Recursive Filters for Low-Cost Virtual Acoustic Rendering
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Solution Overview
Problem
Existing virtual acoustic rendering systems struggle to efficiently simulate sound emission and reception characteristics of objects in time-varying and interactive contexts, requiring large memory storage, high computational cost, and inflexible processing due to fixed-size filter structures and FIR filter arrays, which are inadequate for modeling frequency-dependent directivity and propagation effects.
Innovation Solution
A method and system using time-varying recursive filters with mutable state-space structures that adapt to the number of sound signals and attributes, allowing flexible trade-offs between cost and perceptual quality, enabling efficient simulation of sound objects with frequency-dependent directivity and propagation-induced attenuation without explicit physical modeling or block-based convolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fixed-size FIR filter arrays are used for HRTF simulation, then directional sound reception can be modeled, but computational cost increases linearly with the number of incoming wavefronts and memory bandwidth requirements become prohibitively large
Solution Approach 1:
The patent applies dynamics by transitioning from fixed-size FIR filter arrays to time-varying recursive filter structures. The filter order and structure adapt dynamically based on the number of incoming wavefronts and directional requirements, allowing the system to maintain high directional accuracy while reducing computational overhead when fewer wavefronts are present. This dynamic adaptation resolves the contradiction by making the computational resources proportional to actual needs rather than fixed maximum requirements.
Solution Approach 2:
The patent changes key parameters of the filter structure including order, coefficients, and configuration based on incoming wavefront characteristics. By adjusting these parameters dynamically according to the number and direction of wavefronts, the system achieves accurate directional modeling only when necessary, thereby reducing overall computational cost while maintaining precision where required.
2Productivity
If time-invariant state-space filters are used for HRTF simulation, then interactive simulation can be achieved, but the system requires a large number of inputs regardless of the actual number of arriving wavefronts
Solution Approach 1:
The patent implements dynamics by making the filter structure time-varying rather than time-invariant. The number of active inputs and filter configuration changes based on the actual number of arriving wavefronts at each time step, enabling interactive simulation with adaptive complexity. This allows the system to maintain low input requirements when few wavefronts are present while still supporting interactive updates when needed.
Solution Approach 2:
The patent segments the filter input structure into multiple possible inputs that are selectively activated based on the number of arriving wavefronts. Rather than requiring all inputs to be present simultaneously, the system activates only the necessary subset, reducing device complexity while maintaining interactive simulation capability through selective input engagement.
3Power
If recursive filters with time-varying structure are used, then computational cost and memory bandwidth are reduced, but the filter structure becomes more complex to implement
Solution Approach 1:
The patent applies dynamics by implementing time-varying recursive filters where the structure adapts based on incoming signal characteristics. This dynamic approach reduces computational cost and memory bandwidth by processing only necessary data at each time step, while the complexity is managed through systematic updates of filter coefficients and order based on predefined criteria rather than full reconfiguration.
Solution Approach 2:
The patent applies preliminary action by pre-calculating and storing filter coefficient sets and configuration parameters for different wavefront scenarios. This allows the time-varying filter to switch between pre-computed configurations rather than calculating everything in real-time, reducing runtime computational complexity while maintaining the benefits of adaptive filtering.
4Measurement precision
If large databases of directional impulse responses are stored for HRTF simulation, then high fidelity directional accuracy is achieved, but memory storage requirements and data retrieval bandwidth become prohibitively large
Solution Approach 1:
The patent changes parameters by representing directional impulse responses through compact parametric models rather than storing complete impulse response data. By storing only essential parameters that define the directional characteristics, the system achieves high fidelity accuracy while dramatically reducing memory storage requirements and data retrieval bandwidth compared to full impulse response databases.
Solution Approach 2:
The patent applies copying by using parametric representations that can generate complete impulse responses on-demand rather than storing them all. This virtual copying approach maintains accuracy by regenerating responses from compact parameter sets, reducing storage requirements while preserving the ability to retrieve high-fidelity directional data when needed.
Data Source
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AI summary
Simulation of sound objects and attributes based on time-varying recursive filter structures each comprising a vector of one or more state variables and a mutable number of sound input and/or sound output signals. For simulating sound reception, the recursive update of at least one state variable involves adding an input term obtained by linearly combining input sound signals being received, wherein said combination involves time-varying coefficients adapted in response to input reception coordinates associated with said input sound signals. For simulating sound emission, state variables are linearly combined wherein said combination involves time-varying coefficients adapted in response to output emission coordinates associated with said output sound signals. Attenuation or other effects induced by sound propagation and/or interaction with obstacles may be incorporated during sound emission and/or reception through scaling the time-varying coefficients involved therein. Sound propagation may be simulated by treating state variables of sound object simulations as propagating waves.